Study on operation strategy and load forecasting for distributed energy system based on Chinese supply-side power grid reform

Abstract

This study focuses on the development and analysis of a real-time updated operations strategy of a distributed energy system (DES). Owing to the relevant Chinese policy of electrical transmission and distribution, combined cooling, heating, and power system (CCHP) and photovoltaic (PV) systems are not currently allowed. However, with the Chinese supply-side power grid reform, the permissions for connections between DESs and utilities are gradually evolving. By performing building simulation and using mixed integer linear programming (MILP), a real-time updated operation strategy of a DES is established. Then, considering the DES from Tianjin Eco-city as a case study, a comparative analysis between this updated strategy and the current operation strategy is performed by evaluating three factors: economic efficiency, energy consumption, and CO2 emission. The results show that the updated strategy can reduce 29.12% of electricity time-of-use cost, 10.11% of total fuel consumption, and 18.40% of CO2 emission during the cooling season. Besides, a method of “rolling load forecasting” for DES by using Support vector regression machine (SVR) is proposed and discussed. The testing shows that the Mean Absolute Percentage Error (MAPE) is below 7.5%. And when the training sample is large, the particle swarm optimization algorithm can be used to shorten the modeling time of the air conditioning load forecasting model.

Keywords

• Distributed Energy System (DES)
• Mixed integer linear programming
• Energy efficiency, Operation strategy establishment