A three-stage strategy for optimal price offering by a retailer based on clustering techniques

Mahmoudi-Kohan, N.; Moghaddam, Mohsen Parsa; Sheikh‐El‐Eslami, Mohammad Kazem; Shayesteh, Ebrahim

doi:10.1016/j.ijepes.2010.06.011

Cited by 61 publications

(38 citation statements)

References 30 publications

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“…The retailers can procure electrical energy in the wholesale electricity market through two different resources: (1) wholesale markets and (2) wholesale contracts. Considering the wholesale market, Day-ahead Market (DAM) [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28], Real Time Market (RTM) [17][18][19][20][21][22][23][24][25][26][27][28][29], Reserve Market (RM) [15,21,22] and Intraday Market (IDM) [20] are the most common markets used by retailers to purchase their obligated energy. Moreover, regarding the wholesale contracts, future contracts [17,26,29], forward contracts [16,18,23,30], call option [23,30] and swing contracts [25,28] are typically used in different studies of retail market.…”

Section: Energy Management In Retail Electricity Marketmentioning

confidence: 99%

“…In the literature about the energy management in retail electricity markets, there are many different research studies which consider the retailers as a price-taker agent [21][22][23][24][25][26][27][28][29]. Price-taker retailers (PTR) and price-maker retailers (PMR) are exposed to different sources of uncertainty.…”

Section: Price-maker and Price-taker Retailersmentioning

confidence: 99%

“…The most common way to model the problem with uncertain variables is the stochastic programming. Regarding the retail problem, many research studies use stochastic programming approach to model the problem mathematically [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. Instead of the stochastic programming, some papers, especially in recent years, have concentrated on Information Gap Decision Theory (IGDT) [16] and robust optimization approach [31] to model the retail problem.…”

Section: Mathematical Modelingmentioning

confidence: 99%

See 2 more Smart Citations

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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Section: Energy Management In Retail Electricity Marketmentioning

confidence: 99%

Section: Price-maker and Price-taker Retailersmentioning

confidence: 99%

Section: Mathematical Modelingmentioning

confidence: 99%

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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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“…Dynamic pricing is considered in [19,23,41] focusing on the tariffs. Apart from the costs that are related with the procurement mechanism, a crucial parameter is the DR of the consumers.…”

mentioning

confidence: 99%

“…RTP is considered in [19], where different price/demand functions are examined in order to evaluate the influence of the type of the aforementioned function in the profits. In [23], the test set includes 300 consumers connected in the 20 kV distribution network in Iran. The consumers are clustered into four clusters and for each cluster a different RTP profile is applied.…”

mentioning

confidence: 99%

An Improved Fuzzy C-Means Algorithm for the Implementation of Demand Side Management Measures

et al. 2017

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Abstract:Load profiling refers to a procedure that leads to the formulation of daily load curves and consumer classes regarding the similarity of the curve shapes. This procedure incorporates a set of unsupervised machine learning algorithms. While many crisp clustering algorithms have been proposed for grouping load curves into clusters, only one soft clustering algorithm is utilized for the aforementioned purpose, namely the Fuzzy C-Means (FCM) algorithm. Since the benefits of soft clustering are demonstrated in a variety of applications, the potential of introducing a novel modification of the FCM in the electricity consumer clustering process is examined. Additionally, this paper proposes a novel Demand Side Management (DSM) strategy for load management of consumers that are eligible for the implementation of Real-Time Pricing (RTP) schemes. The DSM strategy is formulated as a constrained optimization problem that can be easily solved and therefore, making it a useful tool for retailers' decision-making framework in competitive electricity markets.

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Risk‐based retailer profit maximization: Time of Use price setting for elastic demand

Chawda

Mathuria

Bhakar

2019

Int Trans Electr Energ Syst

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Summary Retailers in electricity markets face challenges of hourly varying energy prices and consumers' elastic demand. Besides these challenges, utilization of high renewable energy (RE) self‐generation such as solar energy could significantly affect energy procurement and sale prices decisions of a retailer. A retailer with RE self‐generation makes decisions targeting best utilization of RE availability, to maximize its profit. However, a retailer without RE makes decisions considering energy prices and elastic demand. In this perspective, this paper determines optimal Time of Use (ToU) sale prices to be offered and optimal energy procurement portfolio, for a retailer with and without RE, considering elastic demand and wholesale market price uncertainty, aiming to maximize retailer's profit. Case study considers three consumer classes to examine risk neutral and risk averse behavior of a retailer. Results illustrate impact of multiple consumer class behavior on ToU price, procurement strategy, and risk preferences of a retailer.

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A three-stage strategy for optimal price offering by a retailer based on clustering techniques

Cited by 61 publications

References 30 publications

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

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

An Improved Fuzzy C-Means Algorithm for the Implementation of Demand Side Management Measures

Risk‐based retailer profit maximization: Time of Use price setting for elastic demand

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