Wang et al., 2024 - Google Patents
A hierarchical coordinated control strategy of air‐conditioning loads for peak regulation serviceWang et al., 2024
View HTML- Document ID
- 17560415021854908610
- Author
- Wang W
- Lin S
- Wang L
- Mi Y
- Tan J
- Qian L
- Li D
- Li F
- Publication year
- Publication venue
- IET Generation, Transmission & Distribution
External Links
Snippet
The increased penetration of renewable energy sources and the intensification of peak‐ valley differences present challenges to peak regulation in the power system. Fulfilling the peak regulation needs of the power system solely through generation‐side resources …
- 238000004378 air conditioning 0 title abstract description 127
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce, e.g. shopping or e-commerce
- G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
- G06Q30/0202—Market predictions or demand forecasting
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Communication or information technology specific aspects supporting electrical power generation, transmission, distribution or end-user application management
- Y04S40/20—Information technology specific aspects
- Y04S40/22—Computer aided design [CAD]; Simulation; Modelling
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Systems supporting the management or operation of end-user stationary applications, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
- Y04S20/20—End-user application control systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Vahedipour‐Dahraie et al. | Stochastic security and risk‐constrained scheduling for an autonomous microgrid with demand response and renewable energy resources | |
| Yin et al. | Decentralized electricity market with transactive energy–a path forward | |
| Oprea et al. | Edge and fog computing using IoT for direct load optimization and control with flexibility services for citizen energy communities | |
| Wang et al. | Chance constrained unit commitment considering comprehensive modelling of demand response resources | |
| Latifi et al. | A distributed algorithm for demand-side management: Selling back to the grid | |
| Xiao et al. | Optimal scheduling and energy management of a multi-energy microgrid with electric vehicles incorporating decision making approach and demand response | |
| Guo et al. | The application effect of the optimized scheduling model of virtual power plant participation in the new electric power system | |
| Alferidi et al. | AI-Powered Microgrid Networks: Multi-Agent Deep Reinforcement Learning for Optimized Energy Trading in Interconnected Systems | |
| Wang et al. | A review of air conditioning load aggregation in distribution networks | |
| Yaghmaee et al. | Power consumption scheduling for future connected smart homes using bi-level cost-wise optimization approach | |
| Zarei et al. | Optimal demand response scheduling and voltage reinforcement in distribution grids incorporating uncertainties of energy resources, placement of energy storages, and aggregated flexible loads | |
| Wang et al. | A hierarchical coordinated control strategy of air‐conditioning loads for peak regulation service | |
| Jiang et al. | Competitive Incentive Mechanism for Multi-Agents in Demand Response via a Hierarchical Game Considering Joint Uncertainties | |
| Yi et al. | Robust security constrained energy and regulation service bidding strategy for a virtual power plant | |
| Qiu et al. | Multi‐objective generation dispatch considering the trade‐off between economy and security | |
| Zhang et al. | Game theory-based demand-side management for efficient energy collaboration in smart networks: a neighborhood-scale optimization framework | |
| Ismael et al. | Demand response for indirect load control in smart grid using novel price modification algorithm | |
| Wu et al. | Design of digital low-carbon system for smart buildings based on PPO algorithm | |
| US20140365023A1 (en) | Systems and Methods for Computer Implemented Energy Management | |
| Wu et al. | A hierarchical carbon trading and optimisation scheduling strategy for integrated energy system with electric vehicles | |
| Li et al. | Research on central air‐conditioning control strategy of intelligent building group based on DFT | |
| Pandiyan et al. | Recursive training based physics-inspired neural network for electric water heater modeling | |
| Koukaras et al. | A Tri-Layer Optimization Framework for Day-Ahead Energy Scheduling Based on Cost and Discomfort Minimization, Energies 2021, 14, 3599 | |
| Mamani et al. | Modeling uncertainty energy price based on interval optimization and energy management in the electrical grid | |
| Zheng et al. | A modified affine arithmetic-based interval optimization for integrated energy system with multiple uncertainties |