Wind Power and Electricity Prices at the PJM Market

Gil, H.A.; Lin, Jeremy

doi:10.1109/tpwrs.2013.2260773

Cited by 74 publications

(38 citation statements)

References 6 publications

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“…conventional (thermal) generation units [11], renewable resources [12], aggregated DGs and storage devices [13]. The retailers can procure electrical energy in the wholesale electricity market through two different resources: (1) wholesale markets and (2) wholesale contracts.…”

Section: Energy Management In Retail Electricity Marketmentioning

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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Section: Energy Management In Retail Electricity Marketmentioning

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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“…(5) The best previous personal position Pbest i and the best personal fitness value fPbest i of particle i are obtained, and the global best position Gbest and the global best fitness value fGbest are obtained. (4). (11) The global best position Gbest and the global best fitness value fGbest are obtained.…”

Section: Programming Of Iqpsomentioning

confidence: 99%

“…A number of studies have investigated the impacts of large-scale wind power integration on the day-ahead market [3][4][5][6]. In [3], a two-stage stochastic programming model is used to clear the day-ahead market, instead of deterministic models, for handling uncertainties better.…”

Section: Introductionmentioning

confidence: 99%

“…In [3], a two-stage stochastic programming model is used to clear the day-ahead market, instead of deterministic models, for handling uncertainties better. The impact of wind power on the day-ahead market prices in the PJM electricity market is examined by using robust economic models and statistical inference [4]. Furthermore, the impacts of demand response and wind power on the day-ahead market prices are described in [5,6].…”

Section: Introductionmentioning

confidence: 99%

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A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

2017

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Abstract:In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO) is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle swarm algorithm (QPSO). Finally, the impacts of associated parameters on the separate trading and unified trading model are analyzed to verify the superiority of the proposed model and algorithm.

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“…Part II [10] of the survey examines the recent trend towards stochastic, or non-deterministic, search techniques and hybrid methods for OPF. The effect of wind power generation on the day-ahead (DA) market prices in the PJM (Pennsylvania New Jersey Maryland) electricity market using robust econometric models and statistical inference is examined in [11]. A new approach for energy and reserve scheduling in electricity markets subject to transmission flow limits, and security is imposed by guaranteeing power balance under each contingency state including both generation and transmission assets is presented in [12].…”

Section: Introductionmentioning

confidence: 99%

Optimum day-ahead clearing of energy and reserve markets with wind power generation using anticipated real-time adjustment costs

Reddy

Bijwe

Abhyankar

2015

International Journal of Electrical Power & Energy Systems

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Wind Power and Electricity Prices at the PJM Market

Cited by 74 publications

References 6 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

A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

Optimum day-ahead clearing of energy and reserve markets with wind power generation using anticipated real-time adjustment costs

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