Decentralized Autonomous Optimal Operation of Multi-Energy System with Multiple Community Integrated Energy Stations

With large scale renewable generation integrated, future power system is confronted with huge pressure of renewable consumption. To solve the wind power curtailment problem brought by central district heating in north China, this paper proposed a novel architecture and decentralized dispatching framework for multi-energy system with multiple community integrated energy systems (CIES) connected via power distribution and existing heating networks. As load clusters and local operators, CIESs are modeled based on conventional heat exchange stations and distribution substations for adaption to existing central heating system. Besides, extra peak shaving equipment such as electric boilers and energy storage is applied to CIESs. A decentralized algorithm based on Analytic Target Cascading (ATC) is presented to solve the optimal dispatching problem by dividing the problem into subproblems of upper-level system and lower-level CIESs. They are optimized locally with exchange power coordination to obtain a final converged optimal operation plan for the whole system. Case study shows effectiveness of the proposed system architecture and dispatching framework on renewable energy consumption and system economic operation.