Dynamic Game-Based Trading Strategies And Mechanism For Multi-Energy Microgrids

At present,the contradiction between traditional energy and development needs is becoming more and more intense,and people’s demand for electricity,heat,gas and others is also growing.The transformation of energy consumption pattern and energy structure is imperative.With the characteristics of autonomy and good compatibility,multi-energy microgrids have become an effective way to accept renewable energy.However,the volatility and intermittence of renewable energy generation,randomness of local users’ demand bring great difficulties to the balance of energy supply and demand in multi-energy microgrids.In addition,with the efficient integration of multiple energy,their tight coupling relationship makes the planning and scheduling of multiple energy in multi-energy microgrids more complex,flexible and diverse.To solve the above problems,based on the dynamic game method,this paper establishes real-time energy trading strategies and mechanism.By utilizing the complementary characteristics of energy in different regions,meet diverse energy needs of local users,and improve energy utilization efficiency and supply reliability of each multienergy microgrid.Thus,the following three aspects are studied in this paper:In order to solve the real-time electricity trading problem among multienergy microgrids,a novel energy trading mechanism based on a multileader multi-follower dynamic game model is established,by explicitly considering transmission losses and wheeling cost.Based on the improved water-filling algorithm,the computational complexity caused by the introduction of transmission cost is solved effectively.Moreover,a best response algorithm is proposed to achieve the only equilibrium iteratively.Numerical simulations demonstrate the convergence and practical of the proposed trading mechanism.The most important implication is that transmission cost has a great impact on energy trading and cannot be ignored.For the problem of credit rating management in real-time energy trading among multi-energy microgrids,this paper proposes a scorecard model based on logistic regression.And the concept of trust degree is then introduced for all the retailers as a punitive measure to relate their credit ratings with the reduction in sales profit.With such a strategy,this paper establishes a multi-leader multi-follower dynamic game model.The optimal trading strategy is obtained based on the proposed optimal response algorithm.It is found that default behaviors of selfish retailers can be greatly constrained with only a slight degradation of the interests of other participants,thereby promoting the establishment of a trustworthy trading market.For solving the problem of multi-energy real-time trading,this paper focuses on describing trading speculative behaviors while considering the coupling relationship of multiple energy.With such a consideration,a dynamic non-cooperative game model considering market speculation is established,where each speculator will select a preferred trading role and obtain its preferred degree through a multi-classification algorithm based on the current and historical trading information,so as to achieve the optimal trading strategy.Based on the proposed optimal response algorithm,the optimal equilibrium point is obtained iteratively.Numerical simulations are provided to verify the convergence and effectiveness of the proposed dynamic game model,and it is found that speculators play a peak-load shifting role in the multi-energy market.