| 引用本文: | 康守亚,李嘉龙,李燕珊,等.考虑峰谷分时电价策略的源荷协调多目标发电调度模型[J].电力系统保护与控制,2016,44(11):83-89.[点击复制] |
| KANG Shouya,LI Jialong,LI Yanshan,et al.Multi-objective generation scheduling model of source and load considering the strategy of TOU price[J].Power System Protection and Control,2016,44(11):83-89[点击复制] |
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| 摘要: |
| 针对新形势下电力调度的发展需求，提出了一种考虑峰谷分时电价策略的源荷协调多目标发电调度模型。首先，探讨了峰谷分时电价对电源及负荷侧的影响机理，从用户电费支出及用电方式两个角度给出了负荷参与峰谷分时电价的满意度指标。其次，以峰谷分时电价为杠杆，将电源侧的发电成本问题以及负荷侧的用电问题进行有效关联，从源荷两侧建立一个多目标发电调度模型，并进一步给出相应的求解算法。该方法能从电源和负荷两侧最大限度地挖掘发电调度的效益，所得的方案也符合各方的利益需求。最后，通过一个省级电网的算例说明了所提方法的有效性。 |
| 关键词: 需求响应 峰谷分时电价 机组组合 用户满意度 多目标优化 |
| DOI：10.7667/PSPC151256 |
| 投稿时间：2015-07-21修订日期：2015-09-10 |
| 基金项目:国家重点基础研究发展规划项目(973计划) (2013CB228205);中国南方电网有限责任公司科技项目(GDDW202013 0303SC00044) |
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| Multi-objective generation scheduling model of source and load considering the strategy of TOU price |
| KANG Shouya,LI Jialong,LI Yanshan,ZHU Jianquan,LIANG Boye,LIU Mingbo |
(School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
;Guangdong Power Grid Control Center, Guangzhou 510600, China) |
| Abstract: |
| Responding to the speedy development of generation scheduling of modern power grid, a novel multi-objective generation scheduling model of source and load considering the time-of-use price is proposed. First, the effects of time-of-use price to the source and load are analyzed, and the satisfaction indexes of customers are given from the costs and habit of customers. Then a multi-objective generation scheduling model is presented by considering both of the generation cost and the customer satisfaction based on time-of-use price. The solving algorithm is also given. In this way, the benefit of generation scheduling is maximized from both sides of source and load, the interests of source and load are also considered well. Finally, the proposed method is tested in a provincial grid, and the effectiveness is demonstrated fully. This work is supported by the National Basic Research Program of China (973 Program) ( No. 2013CB228205). |
| Key words: demand response time-of-use price unit commitment load satisfaction multi-objective optimization |
