Research On Low-carbon Optimal Scheduling Of Cross-border Integrated Energy System Based On Multi-agen

The area of cross-border economic cooperation between China,Vietnam,Burma,and Laos is growing,and the Belt and Road Initiative is actively promoted,border energy cooperation has become an important booster of China’s economic development.Energy infrastructure in border areas is weak and resource development lags,and the contradiction between the rapid growth of energy demand and the lag of local energy infrastructure has become increasingly prominent.It is of great practical significance to realize cross-border coordination of distributed energy systems and large-scale utilization of new energy through energy networks for border peoples to share the dividends of the Belt and Road Initiative,ensure regional prosperity and stability,and build a "community of shared future for neighboring countries".In this context,aiming at the low-carbon operation and collaborative optimization of cross-border comprehensive energy system with multiple agents,this paper carries out in-depth research from the aspects of cross-border comprehensive energy system modeling,cross-border carbon-green certificate joint trading mechanism,multi-agent collaborative operation optimization of cross-border comprehensive energy system considering demand response,etc.The main summary is as follows:(1)Cross-boundary integrated energy system Physical architecture and modeling researchFirstly,based on fully considering the cross-border energy flow and transformation in the integrated energy system of various countries,the Physical framework of the crossborder integrated energy system is constructed.Secondly,the correlative models of the electric network and thermal networks are established.Finally,the core equipment of the cross-border comprehensive energy system is modeled,including gas turbine,gas boiler,wind turbine,photovoltaic equipment,storage battery,heat storage tank,electric boiler,etc.,and a cross-border comprehensive energy system model considering the loss of heat network and the power grid is proposed.(2)Study on cooperative operation optimization of cross-border comprehensive energy system considering carbon-green certificate joint tradingA collaborative operation optimization method of cross-border integrated energy systems considering carbon-green certificate joint trading is proposed.The carbon emission and green certificate trading quota and transaction cost model are established based on taking into account the optimization model of a cross-border comprehensive energy system,taking the operation cost of each country’s comprehensive energy system as the optimization objective,and taking the balance of electric and thermal power and the operational constraints of each core equipment in each country’s comprehensive energy system as the constraint conditions,introducing the exchange rates of neighboring countries into a joint carbon trading-green certificate market,and the joint trading of carbon tradegreen certificate mechanism is established in the cooperative optimization model of the global comprehensive energy system.Using three cross-border integrated energy systems in China,Laos,and Myanmar as examples,this study explores the joint trading mechanism of the carbon trading-green certificate mechanism to assess its economic impact and environmental protection.(3)Study on master-slave game cooperative optimization operation of cross-border comprehensive energy system considering demand responseA master-slave game cooperative optimization model for a cross-border integrated energy system considering demand response is proposed.For the cross-border integrated energy system,considering the load characteristics and user types of different countries,the comprehensive demand response model of each country is established.Taking the operators of the integrated energy system of each country as leaders and users as followers,the master-slave double-layer game cooperative optimization model of the cross-border integrated energy system considering demand response is established and solved by particle swarm optimization algorithm and CPLEX respectively,Examples demonstrate the importance of the suggested approach in lowering each agent’s operating costs,enhancing system stability,and stabilizing power system fluctuation.