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以节能调度为导向的发电侧与售电侧峰谷分时电价联合优化模型
引用本文:谭忠富陈广娟赵建保侯建朝姜海洋. 以节能调度为导向的发电侧与售电侧峰谷分时电价联合优化模型[J]. 中国电机工程学报, 2009, 29(1): 55-62
作者姓名:谭忠富陈广娟赵建保侯建朝姜海洋
作者单位:华北电力大学电力经济研究所华北电力大学电力经济研究所河南洛阳供电公司华北电力大学电力经济研究所华北电力大学电力经济研究所
摘    要:针对中国现阶段还未全面执行电力竞价上网的实际情况,以节能调度为导向,基于需求侧响应,考虑发电机组的上网电量及其在峰、平、谷时段的电量分配问题,在保证发、供、用三方均能从峰谷分时电价中受益的前提下,以实施峰谷分时电价后平均发电能耗成本最低为目标函数,建立发电侧与售电侧峰谷分时电价联合设计的优化模型。在建模过程中,根据各类机组在发电过程中所排放污染物带来的经济损失,为发电机组设置环境价值参数,并给出环境价值参数的确定方法。最后,应用遗传算法给出该优化模型的求解步骤。算例结果表明该优化模型的可行性和有效性。

关 键 词:峰谷分时电价  节能调度  需求弹性  环境价值  遗传算法
收稿时间:2007-09-11

Optimization Model for Designing Peak-valley Time-of-use Power Price of Generation Side and Sale Side at the Direction of Energy Conservation Dispatch
TAN Zhong-fuCHEN Guang-juanZHAO Jian-baoHOU Jian-chaoJIANG Hai-yang. Optimization Model for Designing Peak-valley Time-of-use Power Price of Generation Side and Sale Side at the Direction of Energy Conservation Dispatch[J]. Proceedings of the CSEE, 2009, 29(1): 55-62
Authors:TAN Zhong-fuCHEN Guang-juanZHAO Jian-baoHOU Jian-chaoJIANG Hai-yang
Abstract:At present, electricity bidding isn't enforced completely in China's electricity market. At the direction of energy conservation dispatch, considering the demand response and the problem of units' electricity distribution for different periods an optimization model for designing peak-valley time-of-use power price of generation side and sale side is presented on the condition that units, distribution companies and users can all benefit from peak-valley time-of-use power price. The model's objective is to minimize the average cost of consumed energy. According to economic loss made by contamination of generator emission environment value parameters are given to units with the optimization model being set up. And the expressions of these parameters are settled. At last, the process of solving this optimization model is given applying genetic algorithm (GA). Case results show that the proposed model is efficient.
Keywords:peak-valley time-of-use power price  energy conservation dispatch  demand elasticity  environment value  genetic algorithm
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