Optimization of green energy portfolio in retail market using stochastic programming

Golmohamadi, Hessam; Keypour, Reza; Hassanpour, Atefeh; Davoudi, Masoud

doi:10.1109/naps.2015.7335233

Cited by 12 publications

(9 citation statements)

References 17 publications

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“…Equation 27shows the cost function of the boiler as a function of heat generation. The heat generation of the boiler is bounded to lower and upper thresholds by inequality (28). Note that α Bo , β Bo, and γ Bo are coefficients of the cost function.…”

Section: Industrial Boilermentioning

confidence: 99%

“…The second term shows the cost function of the CHP unit which was modeled in (21)- (26). The third term states the cost function of the industrial boiler which was formulized in (27) and (28). Equation (30) explains the procurement cost from the power grid.…”

Section: Energy Cost Optimizationmentioning

confidence: 99%

“…As illustrated in the previous sections, the main aim of this study is to use the flexibility potentials of the ORI to overcome the external grid's limitation. Therefore, the operation of refinery processes is optimized to provide electricity regulation to the power network when a serious electricity shortage occurs or the grid reliability is jeopardized [28]. This issue is a major problem for Iran Energy Market.…”

Section: Integration Of Flexibility To External Networkmentioning

confidence: 99%

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Integration of Joint Power-Heat Flexibility of Oil Refinery Industries to Uncertain Energy Markets

Golmohamadi

Asadi

2020

Energies

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This paper proposes a novel approach to optimize the main energy consumptions of heavy oil refining industries (ORI) in response to electricity price uncertainties. The whole industrial sub-processes of the ORI are modeled mathematically to investigate the joint power-heat flexibility potentials of the industry. To model the refinery processes, an input/output flow-based model is proposed for five main refining units. Moreover, the role of storage tanks capacity in the power system flexibility is investigated. To hedge against the electricity price uncertainty, an uncertain bound for the wholesale electricity price is addressed. To optimize the industrial processes, a dual robust mixed-integer quadratic program (R-MIQP) is adopted; therefore, the ORI’s operational strategies are determined under the worst-case realization of the electricity price uncertainty. Finally, the suggested approach is implemented in the south-west sector of the Iran Energy Market that suffers from a lack of electricity in hot days of summer. The simulation results confirm that the proposed framework ensures industrial demand flexibility to the external grids when a power shortage occurs. The approach not only provides demand flexibility to the power system, but also minimizes the operation cost of the industries.

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Section: Industrial Boilermentioning

confidence: 99%

Section: Energy Cost Optimizationmentioning

confidence: 99%

Section: Integration Of Flexibility To External Networkmentioning

confidence: 99%

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Integration of Joint Power-Heat Flexibility of Oil Refinery Industries to Uncertain Energy Markets

Golmohamadi

Asadi

2020

Energies

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“…For this reason, many studies consider electricity price and load level as the main uncertain variables in their scheduling [3][4][5][6][7][8][9][10][11][12]. In general terms, as more uncertain variables are considered, the optimization problem becomes more complex, which usually increases the time required to solve the problem.…”

Section: Introductionmentioning

confidence: 99%

Stochastic optimization for retailers with distributed wind generation considering demand response

Golmohamadi

Keypour

2018

J. Mod. Power Syst. Clean Energy

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In this paper, a multi-stage stochastic model is presented for a renewable distributed generation (RDG)-owning retailer to determine the trading strategies existing in a competitive electricity market. Uncertainties associated with wholesale electricity market price, clients' consumption and power output of wind resources are considered through auto regressive integrated moving average (ARIMA) approach. In the proposed method, three trading floors are addressed for the retailer to hedge against the uncertainties. In the first stage, the retailer participates in day-ahead market to supply the clients and in the second stage, intraday market is addressed to allow the retailer to modify the schedule of its clients' consumption/RDG production. Due to unfavorable uncertainties, especially in renewable power production, real-time market is considered in the third stage to diminish the uncertainty at power delivery time. Cost function of wind resources considering capital, operation and maintenance (O&M) cost is incorporated in the objective function to increase the applicability of the mechanism. The proposed approach is formulated for risk-averse and risk-taker retailer through conditional value at risk (CVaR) approach. In order to study the impact of retail strategies on consumption pattern and consumers' electricity bills, time-of-use (TOU) demand response programs are discussed in this paper. Formulating the problem, the mixed integer non-linear programming (MILNP) problem is transformed into mixed integer linear programming (MILP) by jointly using decomposition and disjunctive constraints. Finally, a case study containing wind power resources, energy storage system and retailer is considered to analyze the proficiency of the proposed approach.

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“…In the literature, several studies have proposed new methods to integrate DERs in the wholesale market [16][17][18][19][20][21] and in the retail market [22][23][24][25][26][27]. Reference [28] provided a comprehensive bibliographical survey of recent works related to the next-generation U.S. retail electricity market with consumers and prosumers, which are end users with the ability to produce and consume electricity.…”

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confidence: 99%

The Next-Generation Retail Electricity Market in the Context of Distributed Energy Resources: Vision and Integrating Framework

Prado

Wang

et al. 2019

Energies

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The increasing adoption of distributed energy resources (DERs) and smart grid technologies (SGTs) by end-user retail customers is changing significantly both technical and economic operations in the distribution grid. The next-generation retail electricity market will promote decentralization, efficiency, and competitiveness by accommodating existing and new agents through new business models and transactive approaches in an advanced metering infrastructure (AMI). However, these changes will bring several technical challenges to be addressed in transmission and distribution systems. Considerable activities have been carried out worldwide to study the impacts of integrating DERs into the grid and in the wholesale electricity market. However, the big vision and framework of the next-generation retail market in the context of DERs is still unclear. This paper aims to present a brief review of the present retail electricity market, some recent developments, and a comprehensive vision of the next-generation retail electricity market by describing its expected characteristics, challenges, needs, and future research topics to be addressed. A framework of integrating retail and wholesale electricity markets is also presented and discussed. The proposed vision and framework particularly highlight the necessity of new business models and regulatory initiatives to establish decentralized markets for DERs at the retail level as well as advances in technology and infrastructure necessary to allow the widespread use of DERs in active and effective ways.

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Optimization of green energy portfolio in retail market using stochastic programming

Cited by 12 publications

References 17 publications

Integration of Joint Power-Heat Flexibility of Oil Refinery Industries to Uncertain Energy Markets

Integration of Joint Power-Heat Flexibility of Oil Refinery Industries to Uncertain Energy Markets

Stochastic optimization for retailers with distributed wind generation considering demand response

The Next-Generation Retail Electricity Market in the Context of Distributed Energy Resources: Vision and Integrating Framework

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