Day-ahead optimum bidding strategy for sustainable power, heat and natural gas dispatch

Due to deregulation energy market has stimulated the need for optimizing its bidding strategies in order to achieve economic benefit in the competitive market. It is important to investigate bidding strategy of microgrid (MG) in electricity, heat and natural gas market based on MG's clearing price. The paper discusses about optimum day-ahead heat, power and natural gas market bidding strategy for MG assimilated battery swapping stations (BSSs) considering carbon capture. MG includes PVT panels, wind turbine generators, small hydro power plants, biomass fired micro-cogeneration units (BFMCUs), micro pumped hydro energy storage, BSSs, local electricity, heat and natural gas loads. Carbon capture unit, hydrogen storage unit, electrolyzer and methanation unit have been utilized for supplying natural gas demand. Natural gas is generated by utilizing carbon dioxide which is captured from BFMCUs and hydrogen produced by electrolyzer. Demand response program (DRP) is applied to level demand curves. Snow ablation optimizer, self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, differential evolution and grey wolf optimization are used to solve this problem. It is realized that total profit of MG achieved from optimum bidding without DRP is less than that of achieved with DRP. Maximum profit acquired with DRP is almost 9.6% higher than maximum profit acquired without DRP.