Yang, Jiajia, Zhao, Junhua, Wen, Fushuan, and Dong, Zhao Yang (2018) A Framework of Customizing Electricity Retail Prices. IEEE Transactions on Power Systems, 33 (3). pp. 2415-2428.

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Abstract

The problem of designing customized pricing strategies for different residential users is investigated based on the identification results of residential electric appliances and classifications of end-users according to their consumption behaviors. This study is based on the following assumptions: 1) Each retailer purchases electricity from the forward contract market, day-ahead spot market, and real-time market; 2) the competition among retailers is modeled by a market share function; 3) each retailer adopts fixed time-of-use prices for end-users; 4) the price fluctuations in day-ahead and real-time spot markets as well as uncertainty of electricity consumption behaviors are considered as main sources of risk. Under these assumptions, a pricing framework for retailers is established based on the bilevel programming framework and the optimal clustering in a time sequence. Meanwhile, profit risk is considered by taking conditional value at risk as the risk measure. The proposed bilevel optimization model is finally reformulated into a mixed-integer nonlinear programming problem by solving Karush-Kuhn-Tucker conditions. The online optimization solvers provided by the network-enabled optimization system server and the commercial solver AMPL/GUROBI are used to solve the developed models, respectively. Finally, a case study is employed to demonstrate the feasibility and efficiency of the developed models and algorithms.

Item ID:	77977
Item Type:	Article (Research - C1)
ISSN:	1558-0679
Copyright Information:	© 2017 IEEE.
Date Deposited:	28 Mar 2023 02:13
FoR Codes:	40 ENGINEERING > 4008 Electrical engineering > 400803 Electrical energy generation (incl. renewables, excl. photovoltaics) @ 100%
SEO Codes:	17 ENERGY > 1708 Renewable energy > 170899 Renewable energy not elsewhere classified @ 100%
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