A multi-objective hybrid game pricing strategy for integrated energy operator-load aggregator alliances considering integrated demand response

In recent years, with significant changes in electricity demand, load aggregators have begun to integrate customer demand-side resources and participate market transactions as independent entities. This study aims establish an alliance of integrated energy service providers integrators, which optimizes the operation system maximizes order tothe interests all participants through collaborative mechanism new Power Gas (P2G) Interruptible Demand Response (IDR). To this end, we first constructed a master-slave game model that considers bargaining between integrators large number photovoltaic users model, solve problem competition cooperation. We multi-objective address low-carbon economic equilibrium faced by comprehensive process, use Conditional Value at Risk (CVaR) theory measure uncertainty renewable energy. Secondly, achieve cooperation aggregators, Nash decompose cooper-ative into two subproblems: maximizing benefits allocating benefits. Finally, Alternative Direction Method Multipliers (ADMM) algorithm combined dichotomy compromise programming maximize parties continuous interaction process. The research results indicate after considering trading carbon emission targets are protected, fully promoting exchange producers sellers, alleviating supply pressure IESO. At same time, comparison Multi-objective Evolutionary Algorithm Based on Decomposition (MOEA/D) shows fuzzy used paper has faster solving speed smoother