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1.广东电力交易中心有限责任公司,广东省广州市 510030
2.清华大学电机工程与应用电子技术系,北京市 100084
卢恩(1976—),男,博士,教授级高级工程师,主要研究方向:电力市场、电网运行与调度。E-mail:hbluen@163.com
别佩(1990—),女,博士,主要研究方向:电力市场。E-mail:biepei_gdpec@126.com
王浩浩(1986—),男,硕士,高级工程师,主要研究方向:电力市场、电网运行与调度。E-mail:361641136@qq.com
辜唯朕(1992—),男,通信作者,硕士,主要研究方向:电力市场。E-mail:guwz@tsintergy.com
收稿日期:2019-12-06,
修回日期:2020-05-13,
网络出版日期:2020-07-17,
纸质出版日期:2020-10-10
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卢恩,别佩,王浩浩等.考虑用户自主选择性的零售电价套餐定价策略设计[J].电力系统自动化,2020,44(19):177-184.
LU En,BIE Pei,WANG Haohao,et al.Pricing Strategy Design of Electricity Retail Pricing Package Considering Self-selectivity of Users[J].Automation of Electric Power Systems,2020,44(19):177-184.
卢恩,别佩,王浩浩等.考虑用户自主选择性的零售电价套餐定价策略设计[J].电力系统自动化,2020,44(19):177-184. DOI: 10.7500/AEPS20191206003.
LU En,BIE Pei,WANG Haohao,et al.Pricing Strategy Design of Electricity Retail Pricing Package Considering Self-selectivity of Users[J].Automation of Electric Power Systems,2020,44(19):177-184. DOI: 10.7500/AEPS20191206003.
在零售市场中,零售商制定零售电价套餐时需要尊重用户意愿和选择权,从而保证制定的零售电价方案贴近真实市场结果。为此文中为零售商提出了一种考虑用户自主选择性的零售电价套餐定价策略,该策略考虑了用户的策略行为和选择行为,为同一类型用户(同为工业、商业或居民用户)制定种类数量合理、费率合理的零售套餐,能够满足用户的多样化需求,调动用户资源参与零售市场的潜力。首先,对用户的用电效用、策略行为和选择行为进行了深入分析和建模;其次,构建了零售商在零售市场中的市场份额、购电成本以及运营风险的相关模型;在此基础上,考虑实际问题的限制,建立了零售商以利润最大化为优化目标的套餐定价优化模型;最后使用某地区用户的数据集对套餐定价优化模型进行了验证,说明了模型在考虑用户策略行为和自主选择行为方面可行、有效。
In the retail market
the willingness and the selection rights of power users should be respected when retailers design retail pricing packages
so that it is guaranteed that the designed retail pricing schemes are closed to the outcomes in the real market. Based on this
a pricing strategy for retail pricing packages considering self-selectivity of users is proposed. The users' strategic behaviors and self-selection behaviors are taken into account in the strategy
and the retail packages with reasonable types and rates are formulated for the same users such as industrial
commercial or residential users. This strategy aims to meet the diverse needs of users and mobilize the potential user-side resources to participate in the retail market. Firstly
the utility
strategic behaviors and selection behaviors of users are deeply analyzed and modeled. Secondly
the related models of market share
power purchasing cost and operation risk of retailers in the retail market are constructed. On this basis
considering the limitation of practical situations
the package pricing optimization model with the objective of maximizing the retailer profit is established. Finally
the data set of users in a district is used to verify the package pricing optimization model. The result shows that the model is feasible and effective in considering users' strategic behaviors and self-selection behaviors.
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