Energy procurement management for electricity retailer using new hybrid approach based on combined BICA–BPSO

Nojavan, Sayyad; Mehdinejad, Mehdi; Zare, Kazem; Mohammadi‐Ivatloo, Behnam

doi:10.1016/j.ijepes.2015.05.033

Cited by 30 publications

(9 citation statements)

References 13 publications

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“…The common difficulty with solving the problems such as what described in 1, is the uncertainty of input parameters (Ψ). There are some techniques to model these uncertainties such as stochastic programming (SP) [27], fuzzy modeling [28] and robust optimization (RO) [29]. Each technique needs some information about the uncertain parameter.…”

Section: Uncertainty Modeling Via Igdtmentioning

confidence: 99%

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Information gap decision theory approach to deal with wind power uncertainty in unit commitment

Soroudi

Rabiee

Keane

2017

Electric Power Systems Research

116

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The renewable energy sources (RES) integration in the electricity supply utilities can reduce the energy procurement costs as well as the environmental concerns. Wind power is the most popular form of RES which is vastly utilized worldwide. This paper proposes a robust model for unit commitment (UC) problem, minimizing the operating costs considering uncertainty of wind power generation. In order to handle the uncertainties arising from volatile nature of wind power, information gap decision theory (IGDT) is utilized, where risk averse (RA) and opportunity seeker (OS) strategies are developed. RA strategy gives a robust decision making tool for handling the severe uncertainty of wind power, whereas the OS strategy makes benefit of possible uncertainties by adjusting the decision variables in a right way. Besides, the impact of demand flexibility (or demand response) on the operation costs is also investigated. The proposed model is examined on the IEEE 118-bus test system, and its benefits over the existing stochastic programming technique is examined. The obtained results demonstrate the applicability of the proposed method to deal with the UC problem with uncertain wind power generation. It is also observed that demand flexibility has positive impacts in both RA and OS strategies. Index Terms Demand response (DR), information gap decision theory (IGDT), uncertainty, unit commitment (UC), wind power. NOMENCLATURE Indices & Sets g Index for thermal generation units.

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Section: Uncertainty Modeling Via Igdtmentioning

confidence: 99%

“…The relation between the predicted wind power (P W b,t ) and the uncertain wind power (P W b,t ) is described in (27).…”

Section: Uc Problem Formulationmentioning

confidence: 99%

Information gap decision theory approach to deal with wind power uncertainty in unit commitment

Soroudi

Rabiee

Keane

2017

Electric Power Systems Research

116

View full text Add to dashboard Cite

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“…In the second category, due to the non-linear nature of the problem and great technical complexity, the classical optimization approaches are neglected and heuristic search algorithms, e.g. Genetic Algorithm (GA) [21,22], Particle Swarm Optimization technique (PSO) [55] and Imperialist Competitive Algorithm (ICA) [55] are used to solve the problem.…”

Section: Optimization Solutionmentioning

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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“…In long-term scheduling, references [9,10] minimize total cost without pricing, DRP, smart meter technology and maximizing the anticipated benefit considering uncertainty modeling is proposed. Therewith, the review of studies related to medium-term scheduling shows that the objective function is minimizing cost [11,12], maximizing benefit [13][14][15]. Furthermore, the solution technique is based on hybrid heuristic algorithm or GAMS optimization package.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty-based Multi-objective Modeling for Short-term Demand Response Program Scheduling in the Presence of Retail Electricity Providers

Separi

Sheikholeslami

Barforoshi

2020

Journal of Iranian Association of Electrical and Electronics En

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In this paper, the short-term scheduling for demand response program (DRP) with retail electricity providers (REPs) with light physical assets is proposed. The main contribution is to determine an optimal multi-objective model for these REPs to integrate them into design-model of the incentive-based DRP for retail markets, considering load uncertainties on the locational marginal prices (LMP). Fuzzy logic modeling is used for simulating load uncertainty. Non-dominated sorting genetic algorithm (NSGA-II) is used, due to non-linearity and thus the complexity of the proposed model. A non-linear sorting system based on fuzzy logic is also utilized to find the best compromise among the set of solutions generated by the Pareto-front space. IEEE 24 bus reliability test system is utilized to explain the optimal performance of the proposed approach.

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Energy procurement management for electricity retailer using new hybrid approach based on combined BICA–BPSO

Cited by 30 publications

References 13 publications

Information gap decision theory approach to deal with wind power uncertainty in unit commitment

Information gap decision theory approach to deal with wind power uncertainty in unit commitment

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

Uncertainty-based Multi-objective Modeling for Short-term Demand Response Program Scheduling in the Presence of Retail Electricity Providers

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