CN119010054B - A park energy optimization method, device, electronic equipment and storage medium - Google Patents
A park energy optimization method, device, electronic equipment and storage medium Download PDFInfo
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- CN119010054B CN119010054B CN202411488481.5A CN202411488481A CN119010054B CN 119010054 B CN119010054 B CN 119010054B CN 202411488481 A CN202411488481 A CN 202411488481A CN 119010054 B CN119010054 B CN 119010054B
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- 230000005611 electricity Effects 0.000 claims abstract description 90
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/12—Circuit arrangements for AC mains or AC distribution networks for adjusting voltage in AC networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for AC mains or AC distribution networks for adjusting voltage in AC networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
- H02J3/144—Demand-response operation of the power transmission or distribution network
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
- H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/10—The network having a local or delimited stationary reach
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Abstract
The invention provides a park energy optimization method, a device, electronic equipment and a storage medium, and relates to the technical field of power systems, wherein the park energy optimization method comprises the steps of obtaining the load rate of output nodes and the state information of power utilization nodes in a park, wherein the state information comprises the load power and the running time of equipment; the method comprises the steps of determining energy consumption coefficients corresponding to equipment according to load power and running time corresponding to the equipment, determining node weights of the electricity utilization nodes according to the load power and the corresponding energy consumption coefficients of all the equipment in the electricity utilization nodes, judging whether the load rates of output nodes corresponding to the electricity utilization nodes are larger than a second preset threshold value when the node weights of the electricity utilization nodes are larger than the first preset threshold value, determining migration equipment according to comparison results of the energy consumption coefficients of all the equipment if the load rates of the output nodes are larger than the second preset threshold value, determining migration output nodes according to comparison results of the load rates of all the output nodes, and migrating the migration equipment to be powered by the migration output nodes. The invention can effectively improve the utilization rate of energy sources in the park.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a park energy optimization method, a device, electronic equipment and a storage medium.
Background
In the modernization process, electricity is not an alternative to the basic stone of industrial park development. The industrial park is used as a region for centralized production and service, stable and reliable power supply can ensure that enterprises in the industrial park smoothly develop various economic activities, the production efficiency is improved, and the operation cost is reduced.
However, the power distribution mode of the traditional industrial park is relatively fixed, when the power demand of the equipment changes, the fixed power distribution may not be capable of timely adjusting the power distribution along with the change of the power demand of the equipment, so that the park has poor adaptability to the change of the power demand of the equipment, and the utilization rate of electric energy is affected.
Disclosure of Invention
The invention solves the problem of how to improve the utilization rate of energy sources in a park.
In order to solve the problems, the invention provides a park energy optimization method, a device, electronic equipment and a storage medium.
In a first aspect, the invention provides a method for optimizing energy of a campus, comprising:
Acquiring the load rate of an output node in a park and the state information of a corresponding power utilization node, wherein the state information comprises the load power and the corresponding running time of each device in the power utilization node;
determining an energy consumption coefficient corresponding to the equipment according to the product of the load power corresponding to the equipment and the running time;
Determining node weights of the electricity utilization nodes according to the load power of all the equipment in the electricity utilization nodes and the corresponding energy consumption coefficients through a preset weight relation;
when the node weight of the power utilization node is greater than a first preset threshold, judging whether the load rate of the output node corresponding to the power utilization node is greater than a second preset threshold;
If yes, determining migration equipment according to comparison results of the energy consumption coefficients of all the equipment, and determining migration output nodes according to comparison results of the load rates of all the output nodes;
And migrating the migration equipment to be powered by the migration output node.
Optionally, the weight relationship satisfies:
;
Wherein β is the node weight, α i is the energy consumption coefficient of the ith device in the electricity node, q i is the load power of the ith device in the electricity node, and N is the number of devices in the electricity node.
Optionally, the determining the migration device according to the comparison result of the energy consumption coefficients of all the devices includes:
Obtaining the output power of the output node;
determining deviation power according to the output power, the load rate and a second preset threshold value corresponding to the output node through a preset deviation relation;
And sequencing all the devices according to the corresponding energy consumption coefficients from small to large, superposing the load powers of the devices one by one according to a sequencing result to obtain a superposition total power, and determining all the devices subjected to superposition as the migration device until the superposition total power is greater than or equal to the deviation power.
Optionally, the deviation relationship satisfies:
;
Wherein a is the deviation power corresponding to the output node, Q is the output power of the output node, p is the load factor corresponding to the output node, and γ is the second preset threshold corresponding to the output node.
Optionally, the determining the migration output node according to the comparison result of the load rates of all the output nodes includes:
Determining all the output nodes with the load rate smaller than the second preset threshold value as target nodes;
Obtaining target node output power and target node load rate corresponding to all the target nodes;
Determining surplus power corresponding to each target node through a preset surplus relation according to the target node output power, the target node load rate and a second preset threshold value corresponding to the target node;
and determining the migration output node according to the comparison result of the surplus power corresponding to all the target nodes.
Optionally, the determining the migration output node according to the comparison result of the surplus power corresponding to all the target nodes includes:
Determining the maximum surplus power in all the surplus powers as migration power;
When the migration power is larger than the total superposition power, determining the corresponding target node as the migration output node;
And when the migration power is smaller than or equal to the total superposition power, selecting the largest surplus power from the rest surplus power as the migration power, comparing the surplus power with the total superposition power, repeating the steps until the determined migration power is larger than the total superposition power, and determining the target node corresponding to the determined migration power as the migration output node.
Optionally, the surplus relation satisfies:
;
wherein B is the surplus power, M is the target node output power, M is the target node load rate, and γ is the second preset threshold.
In a second aspect, the present invention provides a campus energy optimization device comprising:
The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring the load rate of an output node in a park and the state information of a corresponding power utilization node, and the state information comprises the load power and the corresponding running time of each device in the power utilization node;
the first processing module is used for determining an energy consumption coefficient corresponding to the equipment according to the product of the load power and the corresponding running time;
the second processing module is used for determining node weights of the electricity utilization nodes through preset weight relations according to the load power of all the equipment in the electricity utilization nodes and the corresponding energy consumption coefficients;
the judging module is used for judging whether the load rate of the output node corresponding to the power utilization node is larger than a second preset threshold value or not when the node weight of the power utilization node is larger than a first preset threshold value;
The comparison module is used for determining migration equipment according to comparison results of the energy consumption coefficients of all the equipment and determining migration output nodes according to comparison results of the load rates of all the output nodes;
And the migration module is used for migrating the migration equipment to be supplied with power by the migration output node.
In a third aspect, the present invention provides an electronic device comprising a memory and a processor;
the memory is used for storing a computer program;
the processor is configured to implement the campus energy optimization method of the first aspect when executing the computer program.
In a fourth aspect, the present invention provides a computer readable storage medium having a computer program stored thereon which, when executed by a processor, implements the campus energy optimization method of the first aspect.
The park energy optimization method, the device, the electronic equipment and the storage medium have the beneficial effects that the running condition of the whole park power system can be accurately mastered by acquiring the load rate of the output node and the state information of the power utilization node. The energy consumption coefficient is determined according to the product of the load power and the running time of the equipment in the output node, and the actual demand condition of each equipment in the output node for energy can be accurately judged through the energy consumption coefficient, so that the node weight of the electricity utilization node is calculated according to the demand condition of all the equipment for energy and the corresponding load power, the node weight not only comprises the actual electric energy demand information of the equipment, but also comprises the power information of the equipment, and the electricity demand condition of the electricity utilization node can be accurately judged. When the node weight of the electricity consumption node is greater than a first preset threshold value, the fact that the electricity consumption node exceeds a set standard value is indicated, namely the current electricity consumption requirement of the electricity consumption node is higher, and a larger power supply pressure possibly exists for an output node powered by the electricity consumption node, so that whether equipment migration is needed by the electricity consumption node is judged through comparison of the load ratio of the output node corresponding to the electricity consumption node and a second preset threshold value, namely whether the load power of the electricity consumption node exceeds the power supply capacity of the corresponding output node, if the load power is also greater than the second preset threshold value, the fact that the equipment in the electricity consumption node is needed to be migrated is indicated, so that the power supply pressure of the corresponding output node is reduced, the energy consumption coefficient of each equipment in the output node is compared, the proper equipment is selected as migration equipment, meanwhile, the proper output node is selected as the migration output node according to the load ratio of the different output nodes, and the migration equipment needed to be migrated to the power supplied by the selected migration output node. The load balance distribution is realized through the equipment migration, the overload risk of a single output node is reduced, the stable operation of the power system is ensured, the power failure and equipment loss caused by overload are avoided, the energy is reasonably distributed, the excessive concentration of the energy consumption area is avoided, and the utilization rate of the energy is improved.
Drawings
FIG. 1 is a schematic flow chart of a method for optimizing energy of a campus according to an embodiment of the invention;
FIG. 2 is a schematic structural diagram of a campus energy optimization device according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. While the invention is susceptible of embodiment in the drawings, it is to be understood that the invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided to provide a more thorough and complete understanding of the invention. It should be understood that the drawings and embodiments of the invention are for illustration purposes only and are not intended to limit the scope of the present invention.
It should be understood that the various steps recited in the method embodiments of the present invention may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the invention is not limited in this respect.
The term "comprising" and variations thereof as used herein is meant to be open-ended, i.e., "including but not limited to," based at least in part on, "one embodiment" means "at least one embodiment," another embodiment "means" at least one additional embodiment, "some embodiments" means "at least some embodiments," and "optional" means "optional embodiment. Related definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this disclosure are only used to distinguish between different devices, modules or units, and are not intended to limit the order or interdependence of functions performed by these devices, modules or units.
It should be noted that references to "a" and "an" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.
The names of messages or information interacted between the devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of such messages or information.
In the related art, in an industrial park, a plurality of output nodes and a plurality of power utilization nodes together form a complex power transmission and distribution network. The output node plays a vital role as a supply source of electric energy. The output end of the transformer is one of common output nodes, and the transformer converts high-voltage electric energy into voltage levels suitable for various devices in a park, so that the electric energy can be safely and stably conveyed to the power utilization node. The energy storage equipment can also be used as an output node, for example, when the power supply of a power grid is insufficient or faults occur, the energy storage equipment can release electric energy, emergency power supply is provided for key equipment, and basic production and operation of a park are ensured. However, due to objective reasons such as park construction, the power supply in the park is relatively fixed, and along with the change of the power demand of the equipment, the power supply is possibly excessively supplied when the power consumption node is in low load and the power supply is insufficient when the power consumption node is in high load, so that the power resource utilization rate is low, the energy is wasted, the production efficiency is influenced, even the equipment is damaged, meanwhile, the voltage instability is caused, the harmonic interference is increased, the performance of the equipment is negatively influenced, and the equipment aging is accelerated. At the system level, reduced system reliability and flexibility, easily break down and power failure problem, and can not satisfy the diversified power consumption demand in garden, influence the utilization ratio to the electric power energy.
Aiming at the problems of the related art, the embodiment provides a park energy optimization method, a device, electronic equipment and a storage medium.
As shown in fig. 1, the method for optimizing energy of a park according to the embodiment of the invention includes:
s100, acquiring the load rate of an output node in a park and the state information of a corresponding power utilization node, wherein the state information comprises the load power and the corresponding running time of each device in the power utilization node.
Specifically, the industrial park comprises a plurality of output nodes, continuous and stable electric energy is provided for electric equipment in different power utilization nodes, and the load rates of the output nodes are key indexes for measuring the running state and the use efficiency of the output nodes. By installing intelligent monitoring equipment such as a high-precision power sensor and a data acquisition device, parameters such as current, voltage and the like of the output node can be monitored in real time, and the actual output power of the output node can be calculated according to the parameters. The load factor is the ratio of the actual output power to the rated power of the output node, for example, if the rated power of one output node is 1000 kw and the current actual output power is 800 kw, the load factor is 80%. Obtaining the load rate of the output node helps to know how tight the power supply is across the campus, and when the load rate is too high, it may mean that the output node is approaching or exceeding its load capacity, and measures need to be taken to adjust the load or increase the power supply to prevent overload-induced faults and power outage risks. When the load rate is too low, the condition of energy waste may be indicated, and the optimization of power distribution and the improvement of energy utilization efficiency can be considered.
Further, each power utilization node includes a plurality of power utilization devices, and the power acquired from the corresponding output node is distributed to each corresponding power utilization device through the power utilization node. For each device in the electricity consumption node, the accurate load power, namely the power of the electricity consumption device, can be obtained by installing a power sensor on the device or obtaining real-time power data through a monitoring system of the device. For example, the load power of an industrial motor during operation may change along with the change of production tasks, and by monitoring the changes, whether the equipment has abnormal high power consumption or not can be timely found, so that fault diagnosis and energy saving optimization can be performed. The running time corresponding to the electric equipment is obtained, and the running time of the equipment can be recorded to help analyze the electricity utilization rule and the energy consumption mode. For example, some devices may only operate for a specific period of time, while some devices need to operate continuously, and by knowing the operating time of the device, the power consumption of the device in the power consumption node can be known. By acquiring the load rate of the output node and the state information of the corresponding power utilization node in the park, important data support can be provided for power management and optimization of the park, and the method is beneficial to improving the energy utilization efficiency, guaranteeing the reliability of power supply and reducing the operation cost.
And S200, determining an energy consumption coefficient corresponding to the equipment according to the product of the load power corresponding to the equipment and the running time.
Specifically, the load power of the device can reflect the actual power consumption rate of the device in the operation process, and different types of devices have great differences in load power due to different functions, performances and working principles, for example, a large mechanical device generally has higher load power, while a small electronic device has relatively lower load power, and the magnitude of the load power directly affects the energy consumption level of the device. The operation time of the equipment can be expressed as the time length of the equipment in a working state in a certain period of time, the operation time of the equipment is influenced by various factors such as production requirements, work flows, equipment maintenance plans and the like, some key equipment may need to be continuously operated to ensure the continuity of production, and other equipment may only be operated in a specific period of time.
Further, the energy consumption coefficient of the equipment is obtained through the product of the load power of the equipment and the corresponding operation time, and the energy consumption condition of the corresponding equipment in the actual production process, namely the condition that the equipment is actually required to be consumed in the whole operation period, can be measured accurately through the corresponding energy consumption coefficient of each equipment, so that the operation conditions of different equipment of the power consumption node and the consumption degree of electric energy can be measured accurately, a more scientific and reasonable energy management strategy can be formulated, and for example, the equipment with lower energy consumption coefficient can be optimized. When the equipment needs to be operated for a long time, in order to keep the stability of the operation of the equipment, the equipment is not suitable for being migrated, and when the load power of the equipment is high, the equipment is generally important and is not suitable for being migrated, so that the operation time and the power of the equipment can be comprehensively considered through the energy consumption coefficient, and the equipment with relatively-intersected operation time and power consumption can be comprehensively selected as the migration equipment according to the energy consumption coefficient.
And S300, determining node weights of the electricity utilization nodes according to the load power of all the equipment in the electricity utilization nodes and the corresponding energy consumption coefficients through a preset weight relation.
Specifically, according to the load power and the energy consumption coefficient corresponding to each device in the electricity consumption node, the node weight of the electricity consumption node is obtained through calculation according to the weight relation, so that the importance degree in the electricity consumption node is reflected through the node weight, and the electric power resource can be distributed more reasonably according to the node weight. For the power utilization node with higher node weight, the explanation of the equipment in the power utilization node is important, and the power supply of the equipment can be preferentially ensured so as to ensure the normal operation and smooth production of key equipment. Meanwhile, the power distribution strategy can be adjusted according to the node weight, so that the power utilization efficiency is improved by avoiding excessive power supply to the low-weight power utilization node. The node weight can provide important basis for energy management decision-making of the industrial park, and a reasonable energy management strategy can be formulated according to the node weight of the electricity utilization node. For example, for the power consumption node with higher node weight, the equipment with lower electric energy consumption can be migrated to other output nodes, so that the energy consumption of the current output node can be reduced, the ionization supply of the residual electric equipment is ensured, and the energy utilization efficiency of the output node in the park is improved. According to the load power and the corresponding energy consumption coefficient of all the equipment in the electricity utilization node, the node weight of the electricity utilization node is determined through a preset weight relation, so that effective decision support can be provided for power management and energy management of an industrial park, and the method is beneficial to improving the power utilization efficiency, reducing the energy cost and guaranteeing smooth production.
And S400, judging whether the load rate of the output node corresponding to the power utilization node is larger than a second preset threshold value or not when the node weight of the power utilization node is larger than a first preset threshold value.
Specifically, the node weight of the electricity utilization node is a numerical value determined through a preset weight relation after the load power and the corresponding energy consumption coefficient of all equipment in the node are comprehensively considered, so that the relative importance degree of the electricity utilization node in the whole electricity utilization system of the park is reflected through the load power and the energy consumption degree of the electricity utilization node, and the larger the node weight is, the higher the demand and the consumption of the electricity utilization node on the electric power are, namely, the more the load and the longer the running time are, or the running of equipment of the electricity utilization node has more critical effects on the aspects of production, operation and the like of the park. For example, in an industrial park, power nodes on some production lines may have higher node weights due to high equipment power, long run time, and critical to product quality and production progress. The first preset threshold is a value determined according to the actual situation of all power utilization nodes of the park and a power utilization management strategy, and is usually set by taking factors such as power supply capacity of the park, equipment importance grades of all power utilization nodes, historical power utilization data and the like into consideration, and the function of the first preset threshold is to screen out the power utilization nodes which are relatively important, namely power utilization nodes with more loads and longer running time, so that the power supply situation of the power utilization nodes is monitored and distributed more strictly. For example, the first predetermined threshold is determined to be 80 through analysis and evaluation of the electricity usage of the campus. When the node weight of a certain electricity node is greater than 80, the electricity node is considered to have higher importance in the campus.
Further, the output node is a key part for providing power for each power consumption node in the park power supply system, the load rate reflects the current use degree of the output node, the load rate is the ratio of the actual output power to the rated power of the output node, and the power supply pressure and the potential overload risk of the output node can be known by monitoring the load rate of the output node. For example, an output node rated at 1000 kw and currently available at 700 kw, then has a load factor of 700/1000=0.7, i.e. 70%. The second preset threshold is a critical value set for judging whether the output node is in an excessively high load state, and the determination needs to consider the factors such as equipment capacity, reliability requirement, grid stability and the like of the output node. If the load rate of the output node exceeds a second preset threshold, the power supply quality is possibly reduced, equipment is damaged, and even a power failure accident is caused. The second preset threshold value is determined to be 85% for example based on the device characteristics of the output node and the grid requirements. When the load rate of an output node exceeds 85%, it is considered that the output node may be at risk of overload. When the node weight of the electricity node is greater than a first preset threshold, the electricity node is important, and at this time, whether the load rate of the output node corresponding to the electricity node is greater than a second preset threshold needs to be further judged, and the judging process is to ensure the power supply stability and reliability of the important electricity node. Firstly, determining node weight of an electricity utilization node, if the node weight is larger than a first preset threshold, acquiring load rate of an output node corresponding to the electricity utilization node, then comparing the load rate of the output node with a second preset threshold, and if the electricity utilization node is important and the corresponding load rate of the output node exceeds the second preset threshold, indicating that the electricity utilization node may be at risk of insufficient power supply or unstable power supply. In this case, measures need to be taken in time to secure the power supply thereof, such as adjusting the power distribution, starting the backup power supply, and the like. The judging process is helpful for park managers to find potential power supply problems in time, corresponding measures are taken to reasonably distribute electric energy, and utilization efficiency of electric energy in the park is improved.
And S500, if yes, determining migration equipment according to comparison results of the energy consumption coefficients of all the equipment, and determining migration output nodes according to comparison results of the load rates of all the output nodes.
And S600, migrating the migration equipment to be powered by the migration output node.
In particular, when the node weight of the electricity node is greater than the first preset threshold and the load rate of its corresponding output node exceeds the second preset threshold, it means that the electricity node is more important and the output node to which it is currently connected may be at risk of overload. In this case, measures need to be taken to optimize the power distribution to ensure stable power supply of the important power consuming nodes. Firstly, determining migration equipment according to energy consumption coefficients, wherein the energy consumption coefficients can be determined according to the product of the load power of each equipment in the power consumption node and the corresponding operation time, the energy consumption conditions of the equipment in the operation time are reflected, namely the continuous operation time and the energy consumption conditions of the equipment, and by comparing the energy consumption coefficients of different equipment, the equipment which is the main energy consumption equipment and the equipment which is the equipment which needs to operate for a long time can be known. For example, the load power of the equipment a is 5 kw, the running time is 8 hours, the energy consumption coefficient is 5×8=40, the load power of the equipment B is 3 kw, the running time is 10 hours, the energy consumption coefficient is 3×10=30, and by comparison, the equipment a can comprehensively evaluate the condition of the equipment on energy source due to higher consumed power even though the running time is shorter, the energy consumption coefficient is relatively higher, when the power consumption nodes are required to be optimized, the energy consumption coefficients of all the equipment can be compared, the equipment with higher energy consumption coefficient can be selected to be migrated for short time in order to keep stable running of the equipment, the equipment with lower energy consumption coefficient can be stopped, the load of the original power consumption node can not be invisible too much after migration, and fluctuation caused by a power grid in the migration process can be effectively avoided.
Further, the migration output node is determined according to the load rate, the load rate of the output node reflects the use degree and the power supply pressure of the node, the higher the load rate is, the larger the load born by the output node is, the risk of overload is possibly faced, and the output node with lighter relative load can be found out by comparing the load rates of different output nodes to serve as a target node of migration equipment. For example, the load factor of the output node a is 80%, the load factor of the output node B is 60%, and the load factor of the output node C is 70%. As can be seen by comparison, the output node B is relatively lightly loaded. When the equipment migration is determined to be needed, comparing the load rates of all the output nodes, and selecting the output node with lower load rate as the migration output node. Therefore, partial load can be transferred from the output node with higher load to the node with lighter load, and the optimization of power distribution is realized. For example, after determining the migration equipment, the load rate of the output node B is found to be the lowest through comparison, so that the migration equipment can be considered to be connected to the output node B, and the output node B supplies power for the migration equipment, so that the load pressure of the original output node is reduced, the influence on a power grid caused by unbalanced load distribution of the output node due to the change of the power consumption requirement of the equipment is avoided, and the utilization rate of energy sources of all the output nodes in a park is improved. And when determining the migration output node, the capacity, reliability, distance from the power consumption node and other factors of the output node need to be considered. The output nodes which have enough capacity, high reliability and are close to the migration equipment are selected, so that the migration cost and the influence on the power system can be reduced.
In this embodiment, the load rate of the output node and the state information of the power consumption node are obtained, so that the operation condition of the power system of the whole park can be accurately grasped. The energy consumption coefficient is determined according to the product of the load power and the running time of the equipment in the output node, and the actual demand condition of each equipment in the output node for energy can be accurately judged through the energy consumption coefficient, so that the node weight of the electricity utilization node is calculated according to the demand condition of all the equipment for energy and the corresponding load power, the node weight not only comprises the actual electric energy demand information of the equipment, but also comprises the power information of the equipment, and the electricity demand condition of the electricity utilization node can be accurately judged. When the node weight of the electricity consumption node is greater than a first preset threshold value, the fact that the electricity consumption node exceeds a set standard value is indicated, namely the current electricity consumption requirement of the electricity consumption node is higher, and a larger power supply pressure possibly exists for an output node powered by the electricity consumption node, so that whether equipment migration is needed by the electricity consumption node is judged through comparison of the load ratio of the output node corresponding to the electricity consumption node and a second preset threshold value, namely whether the load power of the electricity consumption node exceeds the power supply capacity of the corresponding output node, if the load power is also greater than the second preset threshold value, the fact that the equipment in the electricity consumption node is needed to be migrated is indicated, so that the power supply pressure of the corresponding output node is reduced, the energy consumption coefficient of each equipment in the output node is compared, the proper equipment is selected as migration equipment, meanwhile, the proper output node is selected as the migration output node according to the load ratio of the different output nodes, and the migration equipment needed to be migrated to the power supplied by the selected migration output node. The load balance distribution is realized through the equipment migration, the overload risk of a single output node is reduced, the stable operation of the power system is ensured, the power failure and equipment loss caused by overload are avoided, the energy is reasonably distributed, the excessive concentration of the energy consumption area is avoided, and the utilization rate of the energy is improved.
Optionally, the weight relationship satisfies:
;
Wherein β is the node weight, α i is the energy consumption coefficient of the ith device in the electricity node, q i is the load power of the ith device in the electricity node, and N is the number of devices in the electricity node.
In particular, for each device in the electricity node, the product of its energy consumption coefficient and the load power is first calculated, which product can be understood as a quantized contribution of the device to the importance of the electricity node as a whole. For example, a device has a high power consumption coefficient and a high load power, and its contribution to the power consumption node is relatively large. And (3) performing the calculation on all the devices in the electricity utilization node, and accumulating the results to obtain the node weight of the electricity utilization node, wherein the node weight reflects the comprehensive energy consumption and load conditions of all the devices in the whole electricity utilization node. Through the node weight, the importance degree of different electricity utilization nodes in the whole power system can be quickly known, the electricity utilization node with higher node weight can be a key production area, an important equipment concentration area or an area with higher requirement on the stability of power supply, priority needs to be given in power distribution and management, and the power supply of equipment in the electricity utilization node with higher node weight can be preferentially ensured so as to ensure that the power system of the whole park can stably operate.
Optionally, the determining the migration device according to the comparison result of the energy consumption coefficients of all the devices includes:
Obtaining the output power of the output node;
determining deviation power according to the output power, the load rate and a second preset threshold value corresponding to the output node through a preset deviation relation;
And sequencing all the devices according to the corresponding energy consumption coefficients from small to large, superposing the load powers of the devices one by one according to a sequencing result to obtain a superposition total power, and determining all the devices subjected to superposition as the migration device until the superposition total power is greater than or equal to the deviation power.
Optionally, the deviation relationship satisfies:
;
Wherein a is the deviation power corresponding to the output node, Q is the output power of the output node, p is the load factor corresponding to the output node, and γ is the second preset threshold corresponding to the output node.
Specifically, the output power of the output node is a key index for measuring the power supply capacity of the output node, reflects the actual power which can be provided for the power utilization node connected with the output node in the current state, can be obtained in real time by installing power monitoring equipment such as a smart meter, a power sensor and the like at the output node, can measure current and voltage, calculates the output power according to the product of the current and the voltage, and then transmits the measured output power data to a central control system through a data transmission system so as to carry out subsequent analysis and processing.
Further, according to the output power, the load rate and the second preset threshold value, the deviation power of the output node is obtained through calculation according to the deviation relation, so that the power deviation between the current load condition and the safe running state of the output node is determined through the deviation power, and the deviation power is used as an important basis for determining the migration equipment. The deviation relationship may be expressed as deviation power=output power× (load factor—a second preset threshold), where the load factor is the ratio of the current actual load of the output node to the rated load, and the second preset threshold is a preset upper safety load factor limit. Firstly, according to the obtained output power of the output node, the known load rate and a preset second preset threshold value, substituting the obtained output power and the known load rate into a deviation relation formula to calculate, wherein the calculated deviation power is positive because the load rate of the output node exceeds the second preset threshold value, which means that the output node is in an overload or near overload state, and measures are needed to be taken to reduce the load. For example, one output node has an output power of 1000 kw, a current load factor of 80% and a second preset threshold of 70%. Bias power=1000× (80% -70%) =1000×0.1=100 kw. This means that the output node needs to be loaded down by 100 kw to return to safe operation.
According to the determination of the migration equipment, firstly, all the equipment is sequenced from small to large according to the energy consumption coefficient corresponding to each equipment, the energy consumption coefficient generally reflects the energy utilization efficiency of the equipment in the operation process, the smaller the coefficient is, the less energy is consumed by the equipment in the operation period, and through the sequencing, the equipment with low energy consumption can be prioritized for subsequent operation, so that the optimal utilization of the energy is realized, and the whole energy consumption cost is reduced. And then, superposing the load powers corresponding to the devices one by one according to the ordered sequence to obtain the total superposition power, wherein the aim of the superposition one by one is to gradually increase the total superposition power so as to find out the device combination meeting the condition, namely, determining all the superposed devices as migration devices until the total superposition power is greater than or equal to the deviation power. For example, the load power of the device with the smallest energy consumption coefficient arranged at the first is determined as the total superposition power, when the total superposition power is smaller than the deviation power, the load power of the device arranged at the second is added with the load power of the device arranged at the first to obtain the new total superposition power, and the new total superposition power is obtained by pushing until the obtained total superposition power is larger than or equal to the deviation power for the first time, all the devices participating in superposition are determined as migration devices.
It should be noted that the number of the migration devices is not as large as possible, and the minimum number of the migration devices is required to be ensured while the total load power of the migration devices is greater than or equal to the deviation power, so that a large number of device migration is avoided, and the operation stability of the park devices is improved. For example, assuming that the deviation power is 18 kw, firstly, a device with the smallest energy consumption coefficient is selected, the load power is 5 kw, the requirement is not met, then a device with the smallest energy consumption coefficient is selected, the load power is 8 kw, the total superimposed power is 13 kw, the requirement is not met yet, the next device with the smaller energy consumption coefficient is continuously selected, the load power is 10 kw, at this time, the sum of the load powers of the first three devices is 5+8+10=23 kw, that is, the total superimposed power is 23 kw, and the total superimposed power is greater than 18 kw, then a new migration device is not required to be selected, that is, the first three devices are determined to be migration devices.
In this optional embodiment, by combining the obtained output power of the output node with the load rate of the output node and the second preset threshold, the deviation power is determined by using a preset deviation relationship, all devices are ordered according to the energy consumption coefficient from small to large, and then the load powers of the devices are stacked one by one to obtain the total stacking power until the total stacking power meets the condition of the deviation power, so that the device needing to be migrated can be accurately determined. Therefore, the situation of excessive migration or insufficient migration can be avoided, and the accuracy and efficiency of equipment migration decision are improved.
Optionally, the determining the migration output node according to the comparison result of the load rates of all the output nodes includes:
Determining all the output nodes with the load rate smaller than the second preset threshold value as target nodes;
Obtaining target node output power and target node load rate corresponding to all the target nodes;
Determining surplus power corresponding to each target node through a preset surplus relation according to the target node output power, the target node load rate and a second preset threshold value corresponding to the target node;
and determining the migration output node according to the comparison result of the surplus power corresponding to all the target nodes.
Specifically, by comparing the magnitude relation between the load rate of each output node and the second preset threshold, all output nodes with the load rate smaller than the second preset threshold are determined as target nodes, so that output nodes with relatively lighter loads are screened out, the nodes possibly have redundant energy supply capacity or lower use requirements, potential resources are provided for subsequent operations, and when the load rate is lower than the second preset threshold, the nodes are not fully utilized in the current state or have a certain margin for adjustment.
Further, the corresponding target node output power and the target node load rate are obtained, the target node output power reflects the energy actually output by the node, and the target node load rate can help to know the relation between the use degree and the potential capability of the node. And determining surplus power corresponding to each target node according to the target node output power, the target node load rate and a second preset threshold value corresponding to the target node through a preset surplus relation, so that the power which can be output by each target node after the current load equipment power supply requirement is met is quantized through the surplus power. Determining the migration output node based on the comparison of the surplus power corresponding to all of the target nodes may involve ordering or other comparison of the surplus power of the respective target nodes to find the target node that is most suitable as the migration output node. The migration output node is usually a node with higher surplus power, and the node has more energy sources to supply the electric energy required by other migration equipment or can bear more load transfer, so that the optimal distribution of the energy sources and the balanced operation of the system can be realized by selecting the proper migration output node.
In this optional embodiment, the node with potential energy surplus can be accurately screened by determining the output node with the load rate smaller than the second preset threshold as the target node and acquiring parameters such as the output power and the load rate thereof. And calculating surplus power of each target node by using a preset surplus relation, and providing a quantization basis for optimizing and distributing energy. And finally, determining the migration output node according to the comparison result of surplus power, thereby being beneficial to realizing reasonable distribution of system load and efficient utilization of energy.
Optionally, the determining the migration output node according to the comparison result of the surplus power corresponding to all the target nodes includes:
Determining the maximum surplus power in all the surplus powers as migration power;
When the migration power is larger than the total superposition power, determining the corresponding target node as the migration output node;
And when the migration power is smaller than or equal to the total superposition power, selecting the largest surplus power from the rest surplus power as the migration power, comparing the surplus power with the total superposition power, repeating the steps until the determined migration power is larger than the total superposition power, and determining the target node corresponding to the determined migration power as the migration output node.
Specifically, the maximum surplus power is found out from the surplus power of all the target nodes, and is determined to be the migration power, and the maximum available energy can be provided through the target node with the maximum energy surplus. When the migration power is greater than the total superposition power, the currently determined target node with the maximum surplus power is enough to meet the requirement of the system for energy adjustment, the corresponding target node is determined to be a migration output node, and the node becomes a source of energy transfer and provides energy supply for migration equipment. If the migration power is smaller than or equal to the total superposition power, which means that the energy adjustment requirement of the system cannot be met only by the target node with the maximum surplus power, the maximum surplus power is further selected from the rest surplus power to serve as new migration power, the maximum surplus power is continuously selected from the rest surplus power repeatedly to serve as the migration power until the obtained migration power is larger than the total superposition power, the process is to ensure that the finally determined migration output node combination can provide enough energy to meet the requirement of migration equipment, each time the new migration power is selected and the corresponding target node is determined to be the migration output node, the surplus energy of each target node in the system can be utilized to the maximum extent in the mode, and the optimal allocation of the energy and the stable operation of the system are realized.
In the optional embodiment, the migration power is determined by the maximum surplus power, and the migration output node is selected according to the migration power, so that high-efficiency energy allocation can be realized, the surplus energy is quickly transferred to a required place, the energy utilization efficiency is improved, and when the migration power does not meet the requirement, the maximum surplus power is continuously selected from the surplus power as new migration power until the surplus power is larger than the total superposition power, the energy requirement of the system can be accurately matched, the system load distribution and the energy distribution can be optimized, the stability, the reliability and the performance of the system can be improved, the running state and the energy requirement change of different systems can be adapted, and the adaptability is high.
Optionally, the surplus relation satisfies:
;
wherein B is the surplus power, M is the target node output power, M is the target node load rate, and γ is the second preset threshold.
As shown in fig. 2, a campus energy optimization device 700 according to an embodiment of the present invention includes:
An obtaining module 701, configured to obtain a load rate of an output node in a campus and state information of a corresponding power utilization node, where the state information includes a load power and a corresponding running time of each device in the power utilization node;
A first processing module 702, configured to determine an energy consumption coefficient corresponding to the device according to a product of the load power and the corresponding running time;
a second processing module 703, configured to determine a node weight of the electricity node according to a preset weight relationship according to the load power of all the devices in the electricity node and the corresponding energy consumption coefficient;
A judging module 704, configured to judge whether the load factor of the output node corresponding to the power consumption node is greater than a second preset threshold when the node weight of the power consumption node is greater than a first preset threshold;
a comparison module 705, configured to determine a migration device according to a comparison result of the energy consumption coefficients of all the devices, and determine a migration output node according to a comparison result of the load rates of all the output nodes;
A migration module 706, configured to migrate the migration device to be powered by the migration output node
The advantage of the campus energy optimization device according to the embodiment compared with the prior art is the same as that of the above-mentioned campus energy optimization method compared with the prior art, and is not described here again.
As shown in fig. 3, an electronic device 800 according to an embodiment of the present invention includes a memory 810 and a processor 820, where the memory 810 is configured to store a computer program, and the processor 820 is configured to implement the campus energy optimization method described above when executing the computer program.
Alternatively, an electronic device 800 comprises a memory 810 and a processor 820 coupled to the memory 810, the memory 810 being configured to store a computer program, the processor 820 being configured to, when executing the computer program, perform the following:
Acquiring the load rate of an output node in a park and the state information of a corresponding power utilization node, wherein the state information comprises the load power and the corresponding running time of each device in the power utilization node;
determining an energy consumption coefficient corresponding to the equipment according to the product of the load power corresponding to the equipment and the running time;
Determining node weights of the electricity utilization nodes according to the load power of all the equipment in the electricity utilization nodes and the corresponding energy consumption coefficients through a preset weight relation;
when the node weight of the power utilization node is greater than a first preset threshold, judging whether the load rate of the output node corresponding to the power utilization node is greater than a second preset threshold;
If yes, determining migration equipment according to comparison results of the energy consumption coefficients of all the equipment, and determining migration output nodes according to comparison results of the load rates of all the output nodes;
And migrating the migration equipment to be powered by the migration output node.
The embodiment of the invention provides a computer readable storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, the park energy optimization method is realized.
Alternatively, a non-transitory computer readable storage medium having a computer program stored thereon, which when executed by a processor, causes the processor to:
Acquiring the load rate of an output node in a park and the state information of a corresponding power utilization node, wherein the state information comprises the load power and the corresponding running time of each device in the power utilization node;
determining an energy consumption coefficient corresponding to the equipment according to the product of the load power corresponding to the equipment and the running time;
Determining node weights of the electricity utilization nodes according to the load power of all the equipment in the electricity utilization nodes and the corresponding energy consumption coefficients through a preset weight relation;
when the node weight of the power utilization node is greater than a first preset threshold, judging whether the load rate of the output node corresponding to the power utilization node is greater than a second preset threshold;
If yes, determining migration equipment according to comparison results of the energy consumption coefficients of all the equipment, and determining migration output nodes according to comparison results of the load rates of all the output nodes;
And migrating the migration equipment to be powered by the migration output node.
An electronic device 800 that may be a server or a client of the present invention will now be described as an example of a hardware device that may be applied to aspects of the present invention. Electronic device 800 is intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. Electronic device 800 may also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
The electronic device 800 includes a computing unit that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) or a computer program loaded from a storage unit into a Random Access Memory (RAM). In the RAM, various programs and data required for the operation of the device may also be stored. The computing unit, ROM and RAM are connected to each other by a bus. An input/output (I/O) interface is also connected to the bus.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random-access Memory (Random Access Memory, RAM), or the like. In the present application, the units described as separate units may or may not be physically separate, and units displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present application. In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
Although the invention is disclosed above, the scope of the invention is not limited thereto. Various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the invention, and these changes and modifications will fall within the scope of the invention.
Claims (6)
1. A method for optimizing energy for a campus, comprising:
Acquiring the load rate of an output node in a park and the state information of a corresponding power utilization node, wherein the state information comprises the load power and the corresponding running time of each device in the power utilization node;
determining an energy consumption coefficient corresponding to the equipment according to the product of the load power corresponding to the equipment and the running time;
Determining node weights of the electricity utilization nodes according to the load power of all the equipment in the electricity utilization nodes and the corresponding energy consumption coefficients through a preset weight relation;
when the node weight of the power utilization node is greater than a first preset threshold, judging whether the load rate of the output node corresponding to the power utilization node is greater than a second preset threshold;
If yes, determining migration equipment according to comparison results of the energy consumption coefficients of all the equipment, and determining migration output nodes according to comparison results of the load rates of all the output nodes;
migrating the migration device to be powered by the migration output node;
Determining migration equipment according to the comparison result of the energy consumption coefficients of all the equipment, wherein the migration equipment comprises obtaining output power of an output node, determining deviation power according to the output power, the load rate and a second preset threshold corresponding to the output node and through a preset deviation relation, sequencing all the equipment according to the corresponding energy consumption coefficients from small to large, and superposing the load power of the equipment one by one according to the sequencing result to obtain superposition total power until the superposition total power is larger than or equal to the deviation power, and determining all the equipment subjected to superposition as the migration equipment;
The deviation relationship satisfies:
;
Wherein a is the deviation power corresponding to the output node, Q is the output power of the output node, p is the load factor corresponding to the output node, and γ is the second preset threshold corresponding to the output node;
determining migration output nodes according to comparison results of the load rates of all the output nodes, wherein the migration output nodes comprise determining all the output nodes with the load rates smaller than the second preset threshold as target nodes, acquiring target node output power and target node load rates corresponding to the target nodes, determining surplus power corresponding to each target node according to the target node output power, the target node load rates and the second preset threshold and through preset surplus relation, and determining the migration output nodes according to comparison results of the surplus power corresponding to all the target nodes;
The method comprises the steps of determining the maximum surplus power in all surplus power as migration power according to comparison results of the surplus power corresponding to all target nodes, determining the corresponding target node as the migration output node when the migration power is larger than the superposition total power, selecting the maximum surplus power from the rest surplus power as the migration power when the migration power is smaller than or equal to the superposition total power, comparing the surplus power with the superposition total power, repeating the steps until the determined migration power is larger than the superposition total power, and determining the target node corresponding to the determined migration power as the migration output node.
2. The campus energy optimization method according to claim 1, wherein the weight relationship satisfies:
;
Wherein β is the node weight, α i is the energy consumption coefficient of the ith device in the electricity node, q i is the load power of the ith device in the electricity node, and N is the number of devices in the electricity node.
3. The method of campus energy optimization according to claim 1, wherein the surplus relation satisfies:
;
wherein B is the surplus power, M is the target node output power, M is the target node load rate, and γ is the second preset threshold.
4. A campus energy optimization device, comprising:
The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring the load rate of an output node in a park and the state information of a corresponding power utilization node, and the state information comprises the load power and the corresponding running time of each device in the power utilization node;
the first processing module is used for determining an energy consumption coefficient corresponding to the equipment according to the product of the load power and the corresponding running time;
the second processing module is used for determining node weights of the electricity utilization nodes through preset weight relations according to the load power of all the equipment in the electricity utilization nodes and the corresponding energy consumption coefficients;
the judging module is used for judging whether the load rate of the output node corresponding to the power utilization node is larger than a second preset threshold value or not when the node weight of the power utilization node is larger than a first preset threshold value;
The comparison module is used for determining migration equipment according to comparison results of the energy consumption coefficients of all the equipment and determining migration output nodes according to comparison results of the load rates of all the output nodes;
Determining migration equipment according to comparison results of the energy consumption coefficients of all the equipment, wherein the determination comprises the steps of obtaining output power of an output node, determining deviation power according to output power, load rate and a second preset threshold corresponding to the output node and through a preset deviation relation, sequencing all the equipment according to the corresponding energy consumption coefficients from small to large, and superposing the load power of the equipment one by one according to sequencing results to obtain superposition total power until the superposition total power is larger than or equal to the deviation power, and determining all the superposed equipment as the migration equipment;
The deviation relationship satisfies:
;
Wherein a is the deviation power corresponding to the output node, Q is the output power of the output node, p is the load factor corresponding to the output node, and γ is the second preset threshold corresponding to the output node;
determining migration output nodes according to comparison results of the load rates of all the output nodes, wherein the migration output nodes comprise determining all the output nodes with the load rates smaller than the second preset threshold as target nodes, acquiring target node output power and target node load rates corresponding to the target nodes, determining surplus power corresponding to each target node according to the target node output power, the target node load rates and the second preset threshold and through preset surplus relation, and determining the migration output nodes according to comparison results of the surplus power corresponding to all the target nodes;
Determining the migration output node according to the comparison result of the surplus powers corresponding to all the target nodes, wherein the determination comprises the steps of determining the largest surplus power in all the surplus powers as migration power, determining the corresponding target node as the migration output node when the migration power is larger than the superposition total power, selecting the largest surplus power from the rest surplus powers as the migration power when the migration power is smaller than or equal to the superposition total power, comparing the surplus power with the superposition total power, repeating the steps until the determined migration power is larger than the superposition total power, and determining the target node corresponding to the determined migration power as the migration output node;
And the migration module is used for migrating the migration equipment to be supplied with power by the migration output node.
5. An electronic device comprising a memory and a processor;
the memory is used for storing a computer program;
the processor, when executing the computer program, is configured to implement the campus energy optimization method of any one of claims 1 to 3.
6. A computer readable storage medium, wherein the storage medium has stored thereon a computer program which, when executed by a processor, implements the campus energy optimization method of any one of claims 1 to 3.
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| CN117913827A (en) * | 2024-03-18 | 2024-04-19 | 广东电网有限责任公司广州供电局 | Optimization method of complex power distribution network considering trigger function |
| CN118282854A (en) * | 2024-03-25 | 2024-07-02 | 新华三信息技术有限公司 | Service load migration method, device, equipment and machine-readable storage medium |
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