Demand Response and Ancillary Service Strategy using Dynamic Game Model for Aggregator Business Market in Smart Grids
Tung‐Sheng Zhan, Chih‐Cheng Kao, Jian‐Liung Chen, Chao‐Lin Kuo, Chia‐Hung Lin, Shi‐Jaw Chen
Abstract
Open-access reader
Tung‐Sheng Zhan, Chih‐Cheng Kao, Jian‐Liung Chen, Chao‐Lin Kuo, Chia‐Hung Lin, Shi‐Jaw Chen
Abstract
Open-access reader
An aggregator acts as a mediator or broker to a group of customers to participate in demand responses (DRs) in an electricity market. Key green policies have encouraged green financial loans to construct distributed generations (DGs) as a virtual power plant. Hence, an innovative business market integrates load management and ancillary services into a demand and generation aggregator. This controllable entity can reduce demands with incentive and contractual controls and dispatch the ancillary power. This study proposes DR programs and ancillary services using the dynamic game model in an aggregator business market. This strategy impartially dispatches reserve energy sources with customers’ dynamic demands, such as onsite generations and storage energy. The aim is to achieve the demand reduction from the main grid, further increasing system flexibility to activate active-duty DGs. A small customer group is selected to demonstrate the effectiveness of the proposed model. Benefits for billing charges may arise.
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An aggregator acts as a mediator or broker to a group of customers to participate in demand responses (DRs) in an electricity market. Key green policies have encouraged green financial loans to construct distributed generations (DGs) as a virtual power plant. Hence, an innovative business market integrates load management and ancillary services into a demand and generation aggregator. This controllable entity can reduce demands with incentive and contractual controls and dispatch the ancillary power. This study proposes DR programs and ancillary services using the dynamic game model in an aggregator business market. This strategy impartially dispatches reserve energy sources with customers’ dynamic demands, such as onsite generations and storage energy. The aim is to achieve the demand reduction from the main grid, further increasing system flexibility to activate active-duty DGs. A small customer group is selected to demonstrate the effectiveness of the proposed model. Benefits for billing charges may arise.
Key concepts: News aggregator, Demand response, Smart grid, Business model, Electricity market, Incentive, Energy market, Computer science