Intelligent Demand Side Energy Management Technology in Smart Grid
* 21PESGM2757, Consensus-based Decentralized Energy Trading for Distributed Energy Resources: Z. WANG, Monash University, H. WANG, Monash University * 21PESGM2758, Price-driven Charging Demand Management for Shared Mobility-on-Demand Fleet: A Deep Reinforcement Learning Approach: Y. SUN, North China Electric Power University, Y. LIANG, North China Electric Power University, Z. DING, North China Electric Power University * 21PESGM2759, Strategic Bidding and Compensation Mechanism for a Load Aggregator With Direct Thermostat Control Capabilities, S. CHEN, Shanghai Jiaotong University * 21PESGM2760, Coordinated Optimization of EVs and Network Reconfiguration for Distribution Network Restoration Considering Uncertainties, L. ZHANG, China Agricultural University * 21PESGM2770, Deep Reinforcement Learning-based Strategy for Charging Station Participating in Demand Response, J. SONG, Peking University
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Members: $5.00PES
IEEE Members: $10.00
Non-members: $20.00
26 Jul 2021
To improve the economic-efficiency and controllability of demand side resources (DSRs), the development of artificial intelligence (AI) and big data enables the transition from the traditional model-based energy management system (EMS) toward an intelligent and adaptive one. In recent years, for example, intelligent building EMS has been developed to autonomously schedule air conditioning and lighting systems by learning customers' preferences. Industrial/commercial parks are using intelligent EMS to optimize the supply chain for energy saving. Some researchers are designing data-driven bidding strategy for utility companies/ DSR aggregators in electricity markets. In a blueprint of future smart grid, intelligent EMS may involve advanced AI and information communication technology, smart building and distributed energy resource control, online learning for market bidding, etc. This panel will focus on: i) Advanced artificial intelligence and big data analytics for DSRs; ii) Infrastructure design for intelligent demand side energy management; iii) Experience in intelligent demand side EMS.
Chairs:
Jianxiao Wang, North China Electric Power University, Guannan He, MIT
Sponsor Committees:
Smart Buildings, Loads &, Customer Systems
