A comprehensive review on day‐ahead electricity market and important features of world's major electric power exchanges

Shah, Devnath; Chatterjee, Saibal

doi:10.1002/2050-7038.12360

Cited by 38 publications

(12 citation statements)

References 46 publications

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“…(2) The voltage angle at each voltage-controlled (PV) bus is constant. (3) The voltage amplitude at each PV bus is fixed. (4) The load current to total load current ratio remains constant.…”

Section: Equality Constraintsmentioning

confidence: 99%

“…3 h 1 W P = .AD.a.e.W s 2 (12) where, AD is the density of air in kg/m 3 (1.225); a is the wind generator swept area in m 2 ; e is the efficiency constant of the wind generator (0.49); Wsh 3 is the wind speeds in m/s. Wind speed is a value that is variable in this equation by ignoring minor non-linearities.…”

Section: Ws H Wsmentioning

confidence: 99%

“…Wind energy will cause additional uncertainties in the transaction due to the variability in wind speeds affecting the power system operation. To ensure robust wind energy trading in the electricity market, forecasted wind speeds, load forecasting, and power generation models to optimize market strategies and identify uncertainties are essential to ensure system reliability and economic benefits for GENCOs and customers [3,4]. Dynamic economic dispatch (DED) is a significant optimization problem that studies the impact of wind energy integration.…”

Section: Introductionmentioning

confidence: 99%

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Simulated Annealing Algorithm for Dynamic Economic Dispatch Problem in the Electricity Market Incorporating Wind Energy

Bouddou¹,

Benhamida²,

Haba³

et al. 2020

ISI

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In this paper, a bid-based dynamic economic dispatch (BBDED) problem is solved in the electricity market system under bidding strategies, including wind energy penetration using simulated annealing (SA) algorithm. The multi-objective dispatch model allows generating companies (GENCOs) and their customers to submit supply and demand bids to a market controller known as the independent system operator (ISO) and follow a bidding strategy. ISO is responsible for the market clearing and settlement to maximize the social profit and benefit for GENCOs and customers during trading periods. To study the effect and advantages of wind energy integration in the BBDED problem, the wind energy generation is computed using the forecasted wind speeds and included in the dispatch model. In this regard, the ISO's dispatch model is formulated as a bilevel nonlinear optimization problem. The higher-level is solving the market-clearing with and without wind energy, and the lower level is maximizing GENCO's social profit. The proposed SA algorithm is evaluated for optimality, convergence, robustness, and computational efficiency tested on an IEEE 30-bus test system. The simulation results are compared with those found using different algorithm-based approaches, considering various constraints like power balancing, generator limits, ramp rate limits, and transmission losses.

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Section: Equality Constraintsmentioning

confidence: 99%

Section: Ws H Wsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simulated Annealing Algorithm for Dynamic Economic Dispatch Problem in the Electricity Market Incorporating Wind Energy

Bouddou¹,

Benhamida²,

Haba³

et al. 2020

ISI

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“…3 In a uniform price day-ahead market (DAM), EPX clears the market based on supply-demand equilibrium and determines a common price called market-clearing price (MCP). 4 All offers/bids were cleared at this MCP. Sell offers with offer price less than or equal to MCP only get cleared, whereas rest of the offers were rejected.…”

Section: Introductionmentioning

confidence: 99%

Optimal GENCO's bidding strategy in a power exchange facilitating combined power and emission trading using Intelligent Programmed Genetic Algorithm

Shah

Chatterjee²

2020

Int Trans Electr Energ Syst

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“…In References 27,28, the authors propose power electricity market for efficient energy management and reliability improvement of networked MMGs systems. MG's economic dispatch has been an attractive topic for many studies due to the impact on the electricity market and power consumption 29 . The main advantages of the mentioned approaches include the optimality of the solutions with low computational burden, the plug‐and‐play control ability, and the improvement of smart grid cybersecurity 30 …”

Section: Introductionmentioning

confidence: 99%

Hierarchical smart energy management strategy based on cooperative distributed economic model predictive control for multi‐microgrids systems

Brahmia

Wang

Oliveira

et al. 2020

Int Trans Electr Energ Syst

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Summary With the new edge of smart grids technology, the concept of efficient energy management among cooperative microgrids (MGs) distribution networks for the next generation of energy trading applications has become more and more challenging. This article presents smart energy dispatch for multi‐MGs (MMGs) systems based on the cooperative distributed economic model predictive control (DEMPC) within a hierarchical structure. The optimization framework consists of two levels. First, a DEMPC coordinator computes the optimal energy dispatch solution, taking into account the energy surplus with a power‐sharing policy, the retail electricity price based on the time of use (TOU), and the distributed generators units. For the second level, each local controller executes the energy scheduling reference from the first level. Thus, the MMGs system achieves a global supply‐demand balance. Moreover, the proposed approach improves the utilization of renewable power and demonstrates optimal energy dispatch while reducing operating costs. Finally, to validate the efficiency and resiliency of our proposed approach, two cases of study are presented based on three interconnected MGs system under a cooperative and non‐cooperative optimization. Simulation results show the advantage of the cooperative strategy with 28% for MG 1, and 20% for MG 2 in terms of daily operating costs savings.

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A comprehensive review on day‐ahead electricity market and important features of world's major electric power exchanges

Cited by 38 publications

References 46 publications

Simulated Annealing Algorithm for Dynamic Economic Dispatch Problem in the Electricity Market Incorporating Wind Energy

Simulated Annealing Algorithm for Dynamic Economic Dispatch Problem in the Electricity Market Incorporating Wind Energy

Optimal GENCO's bidding strategy in a power exchange facilitating combined power and emission trading using Intelligent Programmed Genetic Algorithm

Hierarchical smart energy management strategy based on cooperative distributed economic model predictive control for multi‐microgrids systems

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