Distributed Coordinative Optimal Scheduling Strategy For Multiple Park Integrated Energy System

The current issues of energy and the environment are receiving increasing attention,and there is a profound transformation underway in the way of energy utilization.The integrated energy system is an effective means to reduce energy carbon and increase energy efficiency by integrating multiple types of energy horizontally and coordinating different application links of energy vertically.Research on this topic is of great significance for building a modern energy system that is clean,low-carbon,safe,and efficient.The multiple park integrated energy system consists of interconnection of several parks,which can further improve energy efficiency,and is an important trend of the future development of the integrated energy system.However,the energy conversion and interaction among different parks in the system are complex,and there are strong autonomous and self-interested demands,making the traditional centralized optimization method inadequate.Moreover,uncertainty exists in renewable energy and various loads,which brings great challenges to the reliable operation of the system.Therefore,this paper takes multiple park integrated energy system as the research object,and carries out research on collaborative optimization scheduling strategy that consider source-load uncertainties in a distributed operating architecture.The main work is as follows:Firstly,the multi-energy interconnection distributed cooperative operation architecture of the multiple park integrated energy system is introduced,and the mathematical model of the key energy equipment inside the park is established.Based on the system architecture,the alternating direction method of multipliers is introduced,and the algorithm is improved by parallelization and adaptive step size to realize the efficient solution of distributed optimization scheduling problem.These works lay a basic model and algorithm foundation for the subsequent research.Secondly,in order to meet the low carbon emission requirements of the system and balance the overall optimal goal and individual benefit goal,the distributed collaborative optimization and scheduling strategy under the deterministic environment is studied.A multi-energy interconnection low-carbon economy dispatching model of the multiple park integrated energy system is established and incorporated into the Nash bargaining model framework.To solve this complex nonlinear problem,it is transformed into an equivalent sub-problem of social cost minimization and emergence benefits allocation.Through the improved alternating direction method of multipliers,the distributed solution of the problem is realized,and the cooperative operation scheduling plan and energy pricing trading strategy of each park are obtained.The case study shows that the scheduling strategy can simultaneously satisfy the rationality of individual parks and the overall system,effectively achieve the system’s goals of carbon reduction and efficiency improvement,and protect the privacy of each park’s information.Finally,this paper delved into robust distributed collaborative optimization and scheduling strategies in the presence of uncertainty in the system’s source and load.Using fuzzy chance constraint theory to construct the uncertainty set for source and load,a two-stage robust optimization and scheduling model for each park was established.The contribution of each park was quantified using the energy interconnection power,and a non-symmetric Nash bargaining model was obtained for the system.An improved alternating direction method of multipliers combined with nested columns and constraint generation algorithm is used to solve the twostage robust optimization problem with two-layer mixed integer programming in the park and the overall distributed optimization problem of the system.The case study shows that the hybrid solution algorithm can effectively solve the robust cooperative bargaining model of multiple park system.The resulting robust scheduling plan can improve the system’s ability to cope with risks and improve the conservatism by adjusting the uncertain set parameters.Each park can allocate cooperative benefits based on their contributions,achieving a system of low-carbon,economical,reliable,and stable operations.