Intelligent Bidding Strategy of Energy Hub in Under Multiple Electricity Market Environments

With the promotion of power system (PS) reform in China and development of Energy hub (EH) technology, the research of Energy hub bidding strategy participating in the electricity market at distribution level emerges a great requirement. In view of this, the paper proposes a bi-level bidding optimization model of energy hub at distribution level is proposed, which considers the benefits of each participate under the energy market and ancillary service market environment. In the upper level, the Energy hub agent aims to develop an optimal bidding strategy to maximize its total benefits with the consideration of various characteristics of flexible energy resources. In the lower level, the power system owner conducts the electricity market clearing to minimize the operation cost considering the system topology and power flow security. The simulated annealing hybrid genetic algorithm (SA-GA) is adopted to obtain the Energy hub bidding decisions of the proposed bi-level optimization model. The proposed strategy is validated by case studies of a real system and the optimization results and analyses are presented under different scenarios, which indicate a promising application of the proposed Energy hub bidding strategy.