西安交通大学电子与信息工程学院,西安,710049
网络首发:2013-10-10,
纸质出版:2013
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刘连理 1, 李庆 1, 顾运 1, 等. 电力定价策略的多目标优化模型及其应用[J]. 西安交通大学学报, 2013,47(10):115-120.
Multi-Objective Optimization Model with Application to Electricity Pricing[J]. 2013, 47(10): 115-120.
刘连理 1, 李庆 1, 顾运 1, 等. 电力定价策略的多目标优化模型及其应用[J]. 西安交通大学学报, 2013,47(10):115-120. DOI: 10.7652/xjtuxb201310020.
Multi-Objective Optimization Model with Application to Electricity Pricing[J]. 2013, 47(10): 115-120. DOI: 10.7652/xjtuxb201310020.
针对电力定价问题
综合考虑了电力生产过程中的能源利用效率、能源消费等多方面的影响
建立了以最大经济效益和最小环境污染为目标的多目标优化模型。该模型采用用电需求与电价的协整分析表征一定电力定价策略下的消费者行为
采用成本利润模型表征生产者行为
以消费者和生产者行为模型为约束条件。若将环境污染排放量最小的目标转化成约束条件
则多目标问题转化为单目标优化模型求解。在当前电力定价的邻域附近选择一系列定价策略
求解约束条件子模型
得到不同电价模式下经济效益
选择使得经济效益最大的电力定价即为模型最优解。以电力短缺最为严重的2008年以及2009、2010年为例
计算出电价分别为569.72、580.19、598.14元/(MW·h)
均高于实际各年度的平均销售电价
由此可见电力定价应适当上涨。此外
经济社会参数的变化对最优定价策略有明显的影响:排污量限制收紧10%
最优电价将上涨1.09%; GDP增长率升高1个百分点
最优电价将上涨1.08%; 单位生产成本升高1个百分点
最优电价将上涨0.74%。
Considering the effects of energy efficiency and energy consumption on electricity pricing
a multi-objective programming model is constructed and the maximal economic benefit and minimal environmental pollution are taken as the objective functions. Co-integration analysis is performed for modeling the consumer behavior
and cost-profit model is chosen to measure the producer behavior
which serve as the constraint conditions of the multi-objective programming model. The minimal environmental pollutant can be transferred into a constraint condition
the multi-objective programming model thus becomes a single objective one. Various electricity pricing strategies are selected from the neighborhood of current electricity pricing
and economic benefit is calculated by sub-models of constraint conditions. The strategy at the maximal economic benefit is the optimal solution. The optimal electricity prices in 2008
2009 and 2010 get to 569.72
580.19 and 598.14 yuan/(MW·h)
respectively
all higher than the current prices
so electricity price ought to be raised appropriately. It reveals that cutting down the limit of pollutant emission by 10%
the optimal price rises by 1.09%; increasing GDP growth rate by 1%
the optimal price ascends by 1.08%; and raising unit production cost by 1%
the optimal price goes up by 0.74%.
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