Affiliation:
1. School of Electrical and Automation Engineering Nanjing Normal University Nanjing China
2. Jiangsu Province Integrated Energy Equipment and Integration International Joint Laboratory Nanjing China
3. State Grid Nantong Electric Power Supply Company Nantong China
Abstract
AbstractTo address the issues of node interaction power overrun and high carbon emissions that may arise during distributed optimization in multi‐energy parks (MEPs), this paper proposes a distributed low‐carbon and economic operation method for multi‐energy parks based on a cloud platform that considers network transmission capacity.The proposed method achieves maximun profit by designing a two layer collaborative architecture for distributed optimization operations. At the top level, cloud platform services are utilized to build a model for checking network transport capacity and carbon emission quotas, optimizing network node over‐limit inspection . The bottom layer constructs a distributed optimization model for multi‐energy complementation in each park, taking into account the information privacy and individual interests of each multi‐energy park. An improved alternating direction multiplier method (ADMM) is proposed to effectively solve the two‐layer framework. The case studies show that the distributed optimization method under cloud platform services proposed in this paper can achieve maximum revenue for integrated energy service provider while ensuring the safe operation of multi‐energy parks, and reasonably allocate the benefits of collaborative operation among various parks while promoting carbon emission reduction.
Publisher
Institution of Engineering and Technology (IET)
Subject
Renewable Energy, Sustainability and the Environment