Optimal operation scheduling of household energy hub: A multi-objective optimization model considering integrated demand response

Abstract

This paper proposes the multi-energy co-optimization of a household energy hub (EH) from the perspective of the supply side. In this paper, firstly, a household load optimization model is established with the minimization problem of the volatility of each load after participating in the integrated demand response. Secondly, to make this study more relevant to reality, an EH multi-objective optimization scheduling model is established in three dimensions: operation cost, carbon emission, and energy efficiency. Finally, a new α-constrained dominated differential evolution algorithm is proposed to obtain the Pareto optimal solution set for EH multi-objective optimization. Then, a compromise optimal day-ahead scheduling scheme is obtained using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. The algorithm used in this paper has better convergence and distributivity than the traditional non-dominant classification genetic algorithm II (NSGA-II) method with constrained internal penalty functions. The results show that users’ cost has dropped by an average of 30%, and energy efficiency has improved by 4.8%. The reduction in run time also allows for handling more significant amounts of load data.

Keywords

• Household energy hub
• Two-stage multi-objective
• Collaborative optimization scheduling
• Integrated demand response (IDR)