Security and Economic Integration Scheduling of Electricity-Heat Integrated Energy System

Abstract

This paper proposes a security and economic integration scheduling of electricity-heat integrated energy systems (IES) in order to address the uncertainty from the renewable energy source (RES) and load demand and ensure voltage safety. Firstly, we develop mathematical models for the electricity-heat IES using mathematical techniques. Additionally, we predict the power output of the RES and load demand using back propagation (BP) neural networks with genetic optimization. Secondly, we establish an objective function that includes voltage safety and total operating cost. This objective function takes into account the constraints of the electric and heat networks, as well as individual devices. We solve this problem using simulated annealing particle swarms optimization (SA-PSO), which shows superior performance in comparison to other methods. Finally, we carry out comparative simulation schemes to validate the proposed security and economic integration scheduling, which improves the overall operational efficiency and ensures system voltage safety at the same time.

Keywords

• Electricity-heat integrated energy system
• voltage safety
• operating economy
• source load fore-cast
• SA-PSO