Customised Multi-Energy Pricing: Model and Solutions

With the increasing interdependence among energies (e.g., electricity, natural gas and heat) development of a decentralised energy system, novel retail pricing scheme in multi-energy market is demanded. Therefore, problem designing customised for retailers investigated this paper. In particular, proposed formulated as bilevel optimisation problem. At upper level, retailer (leader) aims to maximise its profit. Microgrids (followers) equipped with converters, storage, renewable sources (RES) demand response (DR) programs are located at lower level minimise their operational costs. Three hybrid algorithms combining metaheuristic (i.e., particle swarm (PSO), genetic algorithm (GA) simulated annealing (SA)) mixed-integer linear program (MILP) developed solve Numerical results verify feasibility effectiveness model solution algorithms. We find that GA outperforms other obtain higher retailer’s profit through comparison. addition, could benefit profitability net margin compared widely adopted uniform due reduction overall purchasing costs wholesale markets. Lastly, negative correlations between rated capacity power storage both microgrid’s cost illustrated.