Research On The Coordinated Optimal Operation Of Multi Energy Hubs In The Market Environment

A safe,efficient,low-carbon and clean integrated energy system,supplemented by a market-oriented operation mechanism,is the current mainstream development direction of the global energy system.To facilitate the analysis and management of comprehensive energy systems under market mechanisms,the concept of energy hub was proposed by the Swiss Federal Institute of Technology Zurich.It is defined as an input-output port model that describes the power exchange and coupling relationships between energy,load,and network in multi-energy systems.As one of the core elements in a comprehensive energy system,the development of operating strategies for energy hubs has a significant impact on the operation of the entire system.In the face of numerous and diverse energy hubs with multiple energy sources and numerous internal devices,determining the optimal strategy for each energy hub that considers the individual benefits of different energy hubs and the overall operational efficiency of the comprehensive energy system is a highly challenging task.In this dissertation,we conduct research on the coordinated optimization operation of multiple energy hubs in market environments.The market environments studied include two types,energy sharing markets and wholesale energy markets.When the energy hub is in the early stage of development and the number is small,we use game theory to study the operation strategy of multiple energy hubs when it participates in the energy sharing market and considers the influence of uncertain factors.When the energy hub develops to a large scale,the calculation cost of the model based on game theory is too high,so the auction theory is used to study the operation strategy of many energy hubs participating in the energy sharing market.In addition,due to the differences in the strategies of energy hubs in different market environments,the research on the operation strategies of multiple energy hubs when they participate in the energy wholesale market is also carried out.The details are as follows:1)The coordinated operation model of multiple energy hubs based on bargaining game is proposed for the coordinated operation of multiple energy hubs in the energy sharing market environment.To balance the energy utilization efficiency and economic efficiency,and to consider the individual demands of different energy hubs,the objective function contains two parts,namely,the exergy loss and the operating cost.We simplify the non-convex thermal network model into a linear model using linear fitting,reducing computational costs.We use Nash negotiation game theory to determine the energy,heat value,and cost interactions among multiple EHs.By considering time delays in the thermal network,we improve the accuracy of the network model.The case study shows that the proposed method can balance energy utilization efficiency,economic benefits,and game relationships among EHs well.In addition,due to the slow speed of heat transfer in the thermal network,the time delay effect needs to be considered.As a result of the time delay effect,the thermal network has certain energy storage capabilities and can achieve the transfer of thermal power over time.2)Further consideration of the impact of uncertainties for the coordinated operation of multiple energy hubs,we developed a multiple energy hubs coordinated operation model based on cooperative game theory to address the coordinated operation problem of EHs with different risk preferences.Firstly,a bi-objective optimization model for EHs with different risk preferences was established.Then,a multi-EHs coordinated operation model was built based on cooperative game theory.Finally,a dual-objective allocation method based on Shapley value was proposed to achieve independent allocation of expected cost and CVaR.The case study shows that after the collaboration of multiple energy hubs,the expected cost and conditional value-at-risk are significantly reduced due to the sharing of surplus photovoltaic power and the efficient coordinated operation of multiple devices.The costs of each energy hub are probabilistically independent,and multiple energy hubs collaboration can hedge the risk of costs and further reduce the conditional value-at-risk.Compared with independent operation of energy hubs,the proposed fixed proportion coefficient cost allocation method ensures that the expected cost and conditional value-at-risk of each energy hub are superior.3)When the number of energy hubs is large,the computational cost of the model based on game theory is too high.Therefore,for the problem of coordinated operation of many energy hubs,a multiple energy hubs energy sharing method based on call auction mechanism is proposed.Firstly,we establish an energy sharing market framework based on a set-bidding auction,where each microgrid submits its own bid strategy for purchasing and selling electricity to the energy sharing service provider in both roles.The energy sharing service provider considers the impact of distribution network usage fees during the clearing process.We propose a microgrid purchase and sale bid strategy based on marginal utility to reduce computational costs.The marginal utility is calculated using sensitivity analysis and sliding average filtering methods.The case study shows that energy sharing among microgrids can improve their net utility.When there are enough microgrids and marginal bidding strategies are used,the proposed method can ensure both individual and collective optimality.Moreover,the method can prioritize power exchange between microgrids located at the same node with lower network usage fees,reducing network usage costs.Finally,energy sharing can reduce microgrid electricity prices,increase their load size,and increase the on-site consumption rate of photovoltaic energy.4)The optimal decision model of multiple energy hubs based on the coalition game is proposed for the coordinated operation of multiple energy hubs in the wholesale energy market environment.Firstly,we establish an optimization model for a single energy hub participating in both electricity and natural gas markets.Secondly,we build an electricity and natural gas market model based on the double auction mechanism to describe the competitive relationship among energy hub coalitions.Thirdly,considering the scenario where multiple energy hubs cooperate to form coalitions and there is competition between coalitions,we provide a coalition value representation method based on the minimax theory.On this basis,we propose an optimal coalition structure model for energy hubs considering coalition costs and scale limitations.Finally,we use a hybrid algorithm consisting of diagonalization algorithm and dynamic programming algorithm to solve the optimal cooperation structure and operation strategy of energy hubs.The case study shows that most energy hubs prefer to obtain higher profits through coalitions.After forming coalitions,their market power is strengthened,which increases their own profits but also squeezes the profit space of other small energy hubs,resulting in a decrease in their profits.Due to the existence of coalition costs and scale limitations,which suppresses oligopolistic tendencies,the optimal coalition structure changes from a single grand coalition to multiple coexisting coalitions.