Review on methods of generation scheduling in electric power systems

Yamin, H.Y.

doi:10.1016/j.epsr.2003.10.002

Cited by 155 publications

(76 citation statements)

References 146 publications

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“…GENCO's objective function is maximal expected profit (37). GENCO can justify optimization of the expected profit by the law of large numbers because it gives an optimal decision on average.…”

Section: Objective Functionmentioning

confidence: 99%

Pricing Energy and Ancillary Services in a Day-Ahead Market for a Price-Taker Hydro Generating Company Using a Risk-Constrained Approach

et al. 2014

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This paper analyzes a price-taker hydro generating company which participates simultaneously in day-ahead energy and ancillary services markets. An approach for deriving marginal cost curves for energy and ancillary services is proposed, taking into consideration price uncertainty and opportunity cost of water, which can later be used to determine hourly bid curves. The proposed approach combines an hourly conditional value-at-risk, probability of occurrence of automatic generation control states and an opportunity cost of water to determine energy and ancillary services marginal cost curves. The proposed approach is in a linear constraint form and is easy to implement in optimization problems. A stochastic model of the hydro-economic river basin is presented, based on the actual Vinodol hydropower system in Croatia, with a complex three-dimensional relationship between the power produced, the discharged water, and the head of associated reservoir.

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Section: Objective Functionmentioning

confidence: 99%

Pricing Energy and Ancillary Services in a Day-Ahead Market for a Price-Taker Hydro Generating Company Using a Risk-Constrained Approach

et al. 2014

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“…Most notably, Dynamic Programming (DP), Lagrangian Relaxation (LR), Linear Programming (LP), Quadratic Programming (QP), Mixed-Integer Programming (MIP) as well as Artificial Intelligence based algorithms like Genetic Algorithm (GA), Artificial Neural Networks (ANN), Tabu Search (TS), Simulated Annealing (SA), Ant Colony Systems (ACS) have been proposed for solving the underlying optimization problem (Padhy, 2004;Yamin, 2004;Sen & Kothari, 1998;Sheble et al, 1994). Most recently, emerging techniques from Swarm Intelligence are being investigated for treating complex optimization problems .…”

Section: Solution Techniquesmentioning

confidence: 99%

Optimization of Spinning Reserve in Stand-alone Wind-Diesel Power Systems

Olsina¹,

Larisson²

2010

Wind Power

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“…The power industry has used optimization techniques for solving the UC problem for many years. Therefore, millions of dollars are being saved every year [1].…”

Section: Introductionmentioning

confidence: 99%