Multi-Level Distributed Demand Response Study For Multi-Park Integrated Energy System

The traditional power system is gradually being replaced by a new,smarter,cleaner and more efficient power system that is more flexible and reliable,enabling efficient integration of distributed power sources and various power assets,and capable of handling the growing demand for electricity.China’s power industry,which is in the midst of an accelerated transition period for the construction of new power systems,is in urgent need of a comprehensive transformation across the entire spectrum of power generation,transmission and consumption.To ensure a stable supply of electricity,the power system must be able to respond quickly to changes in power supply and demand.This will require close collaboration between all parts of the power system.from energy suppliers to energy consumers,to optimise resource allocation and improve energy efficiency,and to jointly drive the upgrade and development of the power system to meet the challenges of the future.At the same time,grid operators will need to continue to innovate and introduce more advanced technological tools and management mechanisms to meet the development needs of the new power system.Demand response is an effective means of integrating the potential for user-side grid response.Grid operators can guide customers to adjust their electricity consumption patterns by changing electricity prices or other market signals to reduce peak-to-valley differences.By authorizing customers to take responsibility for their own electricity consumption behavior,the power system can achieve a more decentralized and efficient mode,which can improve energy utilization efficiency at the macro level and optimize users’ economic benefits at the micro level,benefiting all stakeholders.Based on the above background,this paper proposes a multi-level distributed demand response model for a comprehensive energy system in multiple industrial parks,considering the dynamic interaction characteristics among different stakeholders in multiple industrial park clusters,and designing reasonable benefit allocation mechanisms under different scenarios,balancing the coordination and complementarity of multiple industrial parks with the autonomy of each zone,so that each participant has individual initiative and decision-making ability,and maximizes benefits through the optimal allocation of resources between parks.The main research work of this paper is as follows:(1)A low-carbon economic operation optimization model for comprehensive energy systems has been established.The framework structure and equipment composition of the comprehensive energy system were studied,and the energy flows of electricity,gas,heat,and cold in the system were analyzed from the perspective of energy cascade utilization.Carbon trading costs were introduced into the optimization objectives to establish a low-carbon economic optimization operation strategy for the comprehensive energy system.By formulating effective energy use plans and adjusting equipment output,the optimal total cost can be achieved.(2)An integrated demand response market for the park has been established based on the master-slave game.The stakeholders in the park were analyzed,and market clearing optimization models for the park energy management system and user IDR response strategy optimization models were established respectively.The energy management system is the leader in the masterslave game and is responsible for market clearing.As followers,the lower-level users have a noncooperative game relationship with each other due to conflicting interests.By solving a onemaster-multiple-slaves bi-level game model through distributed iteration,demand response can be achieved with less information,and the optimal clearing strategy for the park’s IDR market,as well as self-optimized operating plans for all users under the strategy,can be obtained to protect user privacy and improve user control autonomy.(3)A multi-level distributed demand response optimization model for multiple park comprehensive energy systems has been established.Multiple parks form an alliance through load aggregation merchants,based on cooperative game theory to optimize peak-shaving demand allocation strategies and establish a reasonable benefit distribution mechanism.By optimizing the demand response capability of the system at three levels:multi-park alliance,park as a whole,and individual users,the interests of all stakeholders are fully coupled to achieve the optimal economic benefits for the entire alliance while being profitable for all individuals.