Electricity retail market model with flexible price settings and elastic price-based demand responses by consumers in distribution network

Sekizaki, Shinya; Nishizaki, Ichiro; Hayashida, Tomohiro

doi:10.1016/j.ijepes.2016.02.029

Cited by 66 publications

(58 citation statements)

References 34 publications

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“…One example is the adoption of the automatic production line with radio frequency identification (RFID) technology which improves the stability of the supply level; at the same time, the RFID technology can also reduce the production cost [33]. Meanwhile, retail prices could also affect the market demand [34]. All these questions can be studied in the extension of our model.…”

Section: Discussionmentioning

confidence: 99%

Retailer’s Procurement Strategy under Endogenous Supply Stability

2017

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Abstract:In this paper, a dynamic model is presented to study retailer's procurement strategy when supply stability is endogenously determined. The optimal supply stability as well as the optimal purchasing strategy are characterized with a quadratic cost function. Based on these models, the following findings are brought about. Firstly, when the difficulty level of building supply stability exceeds a certain threshold, it would be more profitable for the retailer to choose a less reliable supplier. Secondly, given that the suppliers can get positive profit, the retailer would choose the one who has the strongest ability to be reliable. Thirdly, the equilibrium supply to the retailer would always meet the demand on the retailing market. Finally, emergency procurement is shown to be an effective way to reduce the risk of supply chain disruptions. To better fit the real situations, an extended model which considers the impact of the stability on costs is further discussed.

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Section: Discussionmentioning

confidence: 99%

Retailer’s Procurement Strategy under Endogenous Supply Stability

2017

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“…The algorithm described below aims to approximate these four solutions to the semivectorial bilevel problem (1) - (14). Scalarizing problems (P1b) and (P2a,b) are employed for this purpose.…”

Section: Semivectorial Bilevel Modelmentioning

confidence: 99%

“…Sekizaki et al [14] presented a bilevel electricity retail market model in which flexible responses of consumers are traded at selling prices offered by a retailer over one day, considering distribution network physical constraints. A genetic algorithm is used to find an approximated solution to the non-convex bilevel model.…”

Section: Introductionmentioning

confidence: 99%

A semivectorial bilevel programming approach to optimize electricity dynamic time-of-use retail pricing

Alves

Antunes

2018

Computers & Operations Research

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Presently, residential electricity consumers are, in general, charged at flat or dual time-of-use tariffs along the day, which are defined by the retailer for long periods (e.g., one year). These pricing schemes do not convey price signals reflecting generation costs and grid conditions. Hence, consumers lack the incentives to engage in different consumption patterns using the flexibility they generally have in the operation of some end-use loads. Dynamic tariffs, i.e. energy prices varying possibly with significant magnitude in short periods of time, are expected to become an applicable pricing scheme in smart grids. In this setting, home energy management systems can play an important role to help end-users optimizing the usage of appliances to minimize energy costs without compromising comfort. This can be advantageous also from the perspective of grid management.A semivectorial bilevel programming approach is developed to model the interaction between electricity retailers and consumers in order to optimize electricity time-of-use retail pricing. The aim is to support the retailer in finding good decisions for the prices. The retailer (upper level decision maker) establishes dynamic time-of-use electricity prices to maximize profits. The consumer (lower level decision maker) responds by selecting, under that price setting, a load scheduling decision leading to a nondominated solution balancing his objectives of minimizing the electricity bill (cost dimension) and minimizing the dissatisfaction in face of his preferences and requirements (comfort dimension).The lower level optimization problem is formulated as a bi-objective mixed-integer linear programming problem. A hybrid approach is proposed, which consists of a genetic algorithm for the upper level problem and an exact solver to solve surrogate scalar problems at the lower level. A case study is presented and discussed.

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“…Paper [85] uses DR programs in the retail side of an energy company to hedge against the uncertainty of wholesale market price. Paper [86] presents a novel retail market model in which elastic demands of consumers can be traded at flexible selling prices offered by a retailer. In this paper, the retailer offers a selling price and the response of elastic consumers toward the prices is investigated by using price-based DR programs In [87] an approach is proposed to determine day-ahead retail electricity price for elastic consumers.…”

Section: Retail Energy Management In Presence Of Newly Emerged Entitiesmentioning

confidence: 99%

Retail Energy Management in Electricity Markets: Structure, Challenges and Economic Aspects- a Review

Golmohamadi

Keypour

2017

Technol Econ Smart Grids Sustain Energy

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In the rapidly growing global energy consumption, electrical energy plays the important role. Environmental concerns about air pollution, fossil fuels depletion and energy crisis have led policy makers of energy systems to increase the portion of electricity in the energy portfolio. On the other hand, economic crises, especially in recent years, have increased the electricity price. With decreased purchasing power, end-use consumers are encouraged to participate in Demand Side Management (DSM) programs, e.g. Demand Response Programs (DRPs), to decrease their electricity bills. In such situation, retail energy management attracts attention in both development and improvement. This paper reviews the concept of retail energy management in modern structure of electricity markets. The objectives of this study are: a) review techno-economic studies in the literature to identify the main structure of retail energy management; b) review the different retail market studies for assessing economic performance; c) present a comprehensive evaluation about the role of DRPs in retail energy management; d) carry out an extensive survey of optimization approaches, mathematical modeling and optimization software about the retail energy management. This paper provides a template for market participants to optimize energy management in the retail side of electricity markets. The proposed structure encourages the efficient development of retail electricity market while eliminating

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Electricity retail market model with flexible price settings and elastic price-based demand responses by consumers in distribution network

Cited by 66 publications

References 34 publications

Retailer’s Procurement Strategy under Endogenous Supply Stability

Retailer’s Procurement Strategy under Endogenous Supply Stability

A semivectorial bilevel programming approach to optimize electricity dynamic time-of-use retail pricing

Retail Energy Management in Electricity Markets: Structure, Challenges and Economic Aspects- a Review

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