计及需求响应不确定性的园区综合能源系统日前经济优化调度

doi:10.12204/j.issn.1000-7229.2021.12.002

电力建设 ›› 2021, Vol. 42 ›› Issue (12): 9-20.doi: 10.12204/j.issn.1000-7229.2021.12.002

• 综合多元能源及信息技术的能源互联网规划与运行·栏目主持刘洋副教授、韩富佳博士· • 上一篇下一篇

计及需求响应不确定性的园区综合能源系统日前经济优化调度

林文智¹(), 杨苹¹^,²(), 陈芯羽¹(), 左冠林¹()

1.华南理工大学电力学院,广州市 510640
2.广东省绿色能源技术重点实验室(华南理工大学),广州市 510630

收稿日期:2021-06-01 出版日期:2021-12-01 发布日期:2021-11-26
通讯作者: 林文智 E-mail:931490882@qq.com;eppyang@scut.edu.cn;645822589@qq.com;473952955@qq.com
作者简介:杨苹(1967),女,博士,教授,博士生导师,主要研究方向为可再生能源并网和微电网技术,E-mail: eppyang@scut.edu.cn;
陈芯羽(1997),女,硕士研究生,主要研究方向为综合能源系统经济优化调度,E-mail: 645822589@qq.com;
左冠林(1997),男,硕士研究生,主要研究方向为新能源并网发电与微网技术、综合能源系统,E-mail: 473952955@qq.com。
基金资助:
南方电网数字电网研究院有限公司科技项目(YTYZW20010)

Day-ahead Optimal Economic Dispatch of Park Integrated Energy System Considering Uncertainty of Demand Response

LIN Wenzhi¹(), YANG Ping¹^,²(), CHEN Xinyu¹(), ZUO Guanlin¹()

1. School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
2. Guangdong Key Laboratory of Clean Energy Technology (South China University of Technology), Guangzhou 510630, China

Received:2021-06-01 Online:2021-12-01 Published:2021-11-26
Contact: LIN Wenzhi E-mail:931490882@qq.com;eppyang@scut.edu.cn;645822589@qq.com;473952955@qq.com
Supported by:
Research Project of Digital Grid Research Institute,China Southern Power Grid(YTYZW20010)

摘要/Abstract

摘要：

园区综合能源系统(park integrated energy system,PIES)通过多能互补可显著提升其运行经济性,然而园区可控资源响应的不确定性会给日前调度策略的制定带来挑战,为此提出了一种考虑综合需求响应及其不确定性的园区综合能源系统日前经济优化调度策略。文章首先运用三角模糊数描述光伏、负荷预测功率以及柔性负荷响应量的不确定性,建立计及不确定性的日前调度模型;然后以系统总运行成本最小为目标,对系统供需两侧可控资源进行协同优化,并根据模糊规划理论,将模糊期望约束和模糊机会约束等效转换为确定性约束形式便于求解;最后通过算例验证了所提策略通过综合需求响应可有效降低系统运行成本,并分析了模糊机会约束置信水平对系统运行成本的影响。

关键词: 园区综合能源系统(PIES), 日前优化调度, 综合需求响应, 不确定性, 模糊规划理论

Abstract:

The park integrated energy system can significantly improve its operation economy through multi-energy complementary. However, the uncertainty of the controllable resource response will bring challenges to the formulation of the day-ahead dispatching strategy. Thus, a day-ahead optimal economic dispatching strategy considering the integrated demand response and its uncertainty is proposed for the park integrated energy system. Firstly, the uncertainty of photovoltaic and load forecast power and the uncertainty of flexible load response are described by triangular fuzzy number, and a day-ahead dispatching model considering uncertainty is established. Then, in order to minimize the total operation cost of the system, the controllable resources of the supply and demand sides of the system are optimized. According to the fuzzy scheduling theory, fuzzy expectation constraints and fuzzy chance constraints are equivalently converted into their certainty forms for easy solution. Finally, the case analysis shows that the proposed strategy can further reduce the operating cost through integrated demand response; and the impact of fuzzy chance constraint confidence level on the system operating cost is analyzed.

Key words: park integrated energy system (PIES), day-ahead optimal dispatch, integrated demand response, uncertainty, fuzzy scheduling theory

中图分类号:

TM73

林文智, 杨苹, 陈芯羽, 左冠林. 计及需求响应不确定性的园区综合能源系统日前经济优化调度[J]. 电力建设, 2021, 42(12): 9-20.

LIN Wenzhi, YANG Ping, CHEN Xinyu, ZUO Guanlin. Day-ahead Optimal Economic Dispatch of Park Integrated Energy System Considering Uncertainty of Demand Response[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(12): 9-20.

图/表 20

图1 典型园区综合能源系统结构

Fig.1 Structure of typical PIES

图2 园区综合能源系统日前调度架构

Fig.2 Day-ahead scheduling structure of PIES

表1 Comparison of optimal scheduling results in different scenarios 元

Table 1

表2 Comparison of optimal scheduling results under different confidence levels 元

Table 2

图3 不同置信水平下的CCHP机组发电功率

Fig.3 Generating power of CCHP units under different confidence levels

表3 用户用能满意度表

Table 3 Energy-consumption satisfaction

图4 参与IDR前后电能负荷功率曲线对比

Fig.4 Comparison of power load curve before and after IDR

图A1 园区用户A各类能源负荷日前预测曲线

Fig. A1 Day ahead load forecasting of User A

图A2 园区用户B各类能源负荷日前预测曲线

Fig. A2 Day ahead load forecasting of User B

图A3 园区用户C各类能源负荷日前预测曲线

Fig. A3 Day ahead load forecasting of User C

图A4 各用户热水需求量和夏季典型日室外温度曲线

Fig. A4 Hot water demand and outdoor temperature curve

表A1 园区能量转换单元运行参数

Table A1 Operating parameters of energy conversion units

表A2 园区能量存储单元运行参数

Table A2 Operating parameters of energy storage units

表A3 模糊变量的三角隶属度参数

Table A3 Parameters of triangular membership degree of fuzzy variables

表A4 园区综合能源系统购售能价格

Table A4 Purchase and sale price for PIES

表A5 需求响应交易出清及补偿价格

Table A5 Clearing and compensation price of DR transaction

图B1 不同场景下PIES冷能负荷优化平衡曲线对比

Fig.B1 Comparison of optimal balance of PIES cooling load under different cases

图B2 不同场景下PIES热能负荷优化平衡曲线对比

Fig.B2 Comparison of optimal balance of PIES thermal load under different cases

图B3 不同场景下PIES电能负荷优化平衡曲线对比

Fig.B3 Comparison of optimal balance of PIES electrical load under different cases

图B4 不同场景下PIES气能负荷优化平衡曲线对比

Fig.B4 Comparison of optimal balance of PIES gas load under different cases

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计及需求响应不确定性的园区综合能源系统日前经济优化调度

Day-ahead Optimal Economic Dispatch of Park Integrated Energy System Considering Uncertainty of Demand Response

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