计及热惯性及光热电站的综合能源系统优化

doi:10.12204/j.issn.1000-7229.2023.01.013

电力建设 ›› 2023, Vol. 44 ›› Issue (1): 109-117.doi: 10.12204/j.issn.1000-7229.2023.01.013

计及热惯性及光热电站的综合能源系统优化

张涛¹(), 刘伉¹(), 陶然²(), 王清川²(), 黄明娟²()

1.三峡大学电气与新能源学院,湖北省宜昌市 443002
2.智慧能源技术湖北省工程研究中心(三峡大学),湖北省宜昌市 443002

收稿日期:2022-05-06 出版日期:2023-01-01 发布日期:2022-12-26
通讯作者: 张涛 E-mail:unifzhang@foxmail.com;1500943318@qq.com;1336818066@qq.com;2781270470@qq.com;1132934946@qq.com
作者简介:刘伉(1998),男,硕士研究生,主要从事综合能源系统及微电网优化调度研究工作,E-mail:1500943318@qq.com。
陶然(1999),男,硕士研究生,主要从事电力系统优化与运行研究工作,E-mail:1336818066@qq.com。
王清川(1998),男,硕士研究生,主要从事电力系统优化与运行研究工作,E-mail:2781270470@qq.com。
黄明娟(1998),女,硕士研究生,主要从事综合能源系统及微电网优化调度研究工作,E-mail:1132934946@qq.com。
基金资助:
国家自然科学基金项目(52007103)

Integrated Energy System Optimization Considering Thermal Inertia and CSP Station

ZHANG Tao¹(), LIU Kang¹(), TAO Ran²(), WANG Qingchuan²(), HUANG Mingjuan²()

1. College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, Hubei Province, China
2. Smart Energy Technology Hubei Engineering Research Center (China Three Gorges University), Yichang 443002, Hubei Province, China

Received:2022-05-06 Online:2023-01-01 Published:2022-12-26
Contact: ZHANG Tao E-mail:unifzhang@foxmail.com;1500943318@qq.com;1336818066@qq.com;2781270470@qq.com;1132934946@qq.com

摘要/Abstract

摘要：

传统热电联供联合调度中,燃气轮机(gas turbine,GT)机组“以热定电”的运行模式极大地限制了系统的调峰能力。提出一种光热电站(concentrating solar power,CSP)参与供热的综合能源系统优化调度方法,并在调度过程中考虑供热网络和供热区域的热惯性。首先,构建光热电站参与电热联合系统调节模型,发挥其供能潜力。其次,构建热网管道和建筑物集群的热惯性模型,挖掘其虚拟储能的特性,在满足各项约束的条件下实现两类热惯性与CSP的协同优化运行。在仿真分析中构建5种对比场景,验证了热网和供热区域的热惯性与CSP储热系统(thermal energy storage,TES)相互协调在提升系统运行经济性、风电上网率和降低系统碳排放方面的有效性。

关键词: 光热发电, 热电联供, 电-热能源系统, 热惯性, 消纳弃风, 低碳效益

Abstract:

The operation mode of gas turbine (GT) in the traditional combined heat and power dispatching greatly limits the peak-shaving capability of the system. A method for optimal dispatch of concentrating solar power (CSP) station participation in heating is proposed. The thermal inertia of the heating network and heating area in the scheduling process is considered. First, a model for the CSP station to participate in the electric heating combined system regulation is built to enhance the peak-regulation capability of the source-side gas turbine unit. Secondly, the thermal inertia model of the heating network and building clusters is constructed, the potential of virtual energy storage is tapped, and the coordinated and optimized operation of the two types of thermal inertia and the CSP station is realized under the conditions of satisfying various constraints. Five comparison scenarios are constructed in the simulation analysis to verify the effectiveness of the coordination between the thermal inertia of the heating network and heating area and the heat storage system of the CSP station in improving the operating economy of the system, improving the efficiency of wind power and reducing the carbon emissions of the system.

This work is supported by National Natural Science Foundation of China (No. 52007103).

Key words: solar thermal power generation, combined heat and power, electric-thermal energy system, thermal inertia, wind absorption and abandonment, low-carbon benefit

中图分类号:

TM732

张涛, 刘伉, 陶然, 王清川, 黄明娟. 计及热惯性及光热电站的综合能源系统优化[J]. 电力建设, 2023, 44(1): 109-117.

ZHANG Tao, LIU Kang, TAO Ran, WANG Qingchuan, HUANG Mingjuan. Integrated Energy System Optimization Considering Thermal Inertia and CSP Station[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(1): 109-117.

图/表 16

图1 光热电站内部简化结构

Fig.1 Simplified internal structure of a CSP station

图2 含光热电站的电-热能源系统框架

Fig.2 Frame of electric-thermal energy system with CSP station

图3 电热负荷与风电功率预测值

Fig.3 Electric heating load and forecast values of wind power

表1 光热电站参数

Table 1 Parameters of the CSP station

表2 火电机组与燃气轮机机组运行参数

Table 2 Operating parameters of thermal power units and gas turbine units

表3 其他模型参数

Table 3 Other model parameters

图4 6节点热力系统结构

Fig.4 6-node thermal system structure

表4 5种典型场景设置

Table 4 Five typical scenarios

表5 各场景下系统运行结果

Table 5 System operation results in various scenarios

图5 各场景下常规机组的供电比例以及CO2排放曲线

Fig.5 Power supply ratio and carbon dioxide emission curve of conventional units in each scenario

表6 5种场景下燃气轮机机组调节能力对比

Table 6 Comparison of adjustment capabilities of gas turbine units in five scenarios

图6 各场景下储热系统最高剩余容量

Fig.6 The maximum remaining capacity of heat storage system in each scenario

图7 场景1与场景2弃风功率对比

Fig.7 Comparison of wind power abandonment in scenario 1 and scenario 2

图8 场景5储热系统各时刻热量变化曲线

Fig.8 The heat change curve of the heat storage system at each time in scenario 5

图9 场景5电-热能源系统电功率优化结果

Fig.9 Electric power optimization results of electric-thermal energy system in scenario 5

图10 场景5电-热能源系统热功率优化结果

Fig.10 Thermal power optimization result of electric-thermal energy system in scenario 5

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计及热惯性及光热电站的综合能源系统优化

Integrated Energy System Optimization Considering Thermal Inertia and CSP Station

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