Day-ahead scheduling strategy optimization of electric-thermal integrated energy system for improvement of new energy consumption

WANG Sen; ZHANG Zhaoyan; YUAN Yubao; ZHANG Dongyue; CHENG Xiaonan; SHI Songkai

doi:10.19666/j.rlfd.202203020

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Day-ahead scheduling strategy optimization of electric-thermal integrated energy system for improvement of new energy consumption

Thermal Power Generation Vol. 51, Issue 7, Pages: 36-45(2022)

更新时间：2025-09-28

- Day-ahead scheduling strategy optimization of electric-thermal integrated energy system for improvement of new energy consumption
- 作者机构：
  
  1. 河北大学电子信息工程学院
  2. 河北省智能电网配用电技术创新中心(石家庄科林电气股份有限公司)
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202203020
  CLC： TM73;TK018
- Published：2022
- 稿件说明：
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WANG Sen, ZHANG Zhaoyan, YUAN Yubao, et al. Day-ahead scheduling strategy optimization of electric-thermal integrated energy system for improvement of new energy consumption[J]. Thermal Power Generation, 2022, 51(7): 36-45.
DOI：

WANG Sen, ZHANG Zhaoyan, YUAN Yubao, et al. Day-ahead scheduling strategy optimization of electric-thermal integrated energy system for improvement of new energy consumption[J]. Thermal Power Generation, 2022, 51(7): 36-45. DOI： 10.19666/j.rlfd.202203020.

摘要

电、热综合能源系统的协调优化可以有效提升我国北方地区冬季取暖期间的用能结构，改善环境污染问题。为此，提出了一种将太阳能集热系统与风电机组、固体蓄热锅炉、生物质锅炉、地源热泵和蓄电池相耦合的电-热综合能源系统经济调度模型，以及综合考虑新能源不确定性、需求侧响应和储能的日前优化调度策略。建立了以整个系统的运行成本为目标的日前区间优化调度模型，采用Pyomo-GLPK软件进行建模并对其进行优化求解；通过算例，分析了模型在不同场景下的运行情况，比较太阳能集热系统与其他设备相耦合对系统的影响以及GLPK和CPLEX的求解结果。仿真结果表明，所提调度方法可有效降低整个系统的运行成本，并提高系统的灵活性和新能源的消纳能力。

Abstract

The coordinated optimization of the comprehensive energy system of electricity and heat can effectively improve the energy structure during winter heating period in northern China and improve the environmental pollution. This paper presents an economic dispatch model for an electric-thermal integrated energy system which couples the solar collector system with wind turbines

solid-state heat storage boilers

biomass boilers

groundsource heat pumps and accumulators

and presents a day-ahead optimal dispatch strategy which takes into account the uncertainty of new energy

demand-side response and storage. A pre-day interval optimal dispatch model is established

which takes the operating cost of the whole system as the target. Pyomo-GLPK software is used to model and solve the problem. Through an example

the operation of the model in different scenarios is analyzed

the influence of the solar collector system coupled with other devices on the system is compared

and the solution results of GLPK and CPLEX are compared. The simulation results show that

the scheduling method proposed in this paper can effectively reduce the operating cost of the whole system and improve the flexibility of the system and the ability to consume new energy.

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