An Evolutionary Programming Based Tabu Search Method for Unit Commitment Problem with Cooling-Banking Constraints

Christober, C.; Rajan, Asir

doi:10.2478/v10187-011-0002-6

Cited by 3 publications

(4 citation statements)

References 32 publications

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“…While in reality these costs typically depend exponentially on the number of hours since the last shutdown, Christober (2011), in this paper a single start-up cost is assumed…”

Section: Constraintsmentioning

confidence: 99%

A Model of German Spot Power Market

Šumbera¹,

Dlouhý²

2015

Prague Economic Papers

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Abstract:This paper aims to model the day-ahead prices on the German EPEX SPOT exchange during the year 2011 using a fundamental mixed-integer programming model with focus on the changes in the volatility of prices. A model of the German market is built from publicly available data. Various constraints on the supply side such as operational characteristics of power plants are described, characterized and ultimately formulated as constraints of a cost-minimization problem. Unknown power plant characteristics are estimated by expert opinions or are inferred indirectly from other data. Several scenarios testing the impact of constraints and modelling approaches are analysed. In addition, a future scenario simulating the year 2016 is used to forecast price developments under the ongoing massive renewable energy growth. Finally, results are discussed with respect to price forecasting accuracy with a focus on the changes in the volatility of prices.

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“…While in reality these costs typically depend exponentially on the number of hours since the last shutdown, Christober (2011), in this paper a single start-up cost is assumed…”

Section: Constraintsmentioning

confidence: 99%

A Model of German Spot Power Market

Šumbera¹,

Dlouhý²

2015

Prague Economic Papers

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“…Numerous researchers have examined an assortment of evolutionary optimization techniques, related to UC problem, in diverse dimensions. This paper proposes to present a complete review of the UC problem, integrated with numerous types of evolutionary optimization techniques like UC problem incorporated with GA [133]- [159], UC problem incorporated with PSO [160]- [170], UC problem incorporated with EA [171]- [177], UC problem incorporated with EP [178]- [183], UC problem incorporated with DE [184]- [190], UC problem incorporated with SFLA [191]- [193], UC problem incorporated with FA [194]- [199], UC problem incorporated with other evolutionary optimization techniques like BFA [200], FSA [201], [202] and CSA [203], UC problem incorporated with Hybrid evolutionary optimization techniques [204]- [244], in the subsequent sections. Distinctive features of the references, connected to evolutionary optimization techniques, are captured and showed in Table 4, including the year of the publication.…”

Section: Review Of Uc Problem Dealt With By Evolutionary Optimization...mentioning

confidence: 99%

“…In this approach, the optimal point is found by EP technique and SA is assisted by EP to make quick best point convergence. The same author also presented an EP-TS approach, with cooling and banking constraints, to solve UC problem solution [183].…”

Section: Uc Problem Incorporated With Epmentioning

confidence: 99%

A Comprehensive Review on Evolutionary Optimization Techniques Applied for Unit Commitment Problem

Muralikrishnan¹,

Jebaraj²,

Rajan

2020

IEEE Access

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Unit Commitment (UC) is a key task in electric power system operation, aiming at minimizing the total cost of power generation. It is essential to monitor wide range of activities and practices of UC necessary to determine the operating plan of generating units. The UC problem is particularly crucial, when the behavior of loads at every hour interval, is oscillatory and with different operational constraints and environments. Many works have been proposed, with different optimization methods to solve the UC problem. This paper gives a detailed review of the evolutionary optimization techniques, employed for solving UC problem, by collecting them from lots of peer reviewed published papers. This review was carried out under many sections, based on various evolutionary optimization techniques, to help new researchers, dealing with modern UC problem solutions, under different situations of power system.

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“…This algorithm gave a faster and cheaper result compared to tabu search, dynamic programming, Artificial neural networks, Lagrange programming, LR-GA, TS-GA and EP-TS methods. In addition, C. Asir [26] has developed another strategy which consists in integrating the tabu search with the genetic algorithm. The purpose of this technique is to find the planning of the production.…”

Section: Introductionmentioning

confidence: 99%

Theoretical Investigation of Combined Use of PSO, Tabu Search and Lagrangian Relaxation methods to solve the Unit Commitment Problem

Marrouchi¹,

Amor²,

Hessine³

et al. 2018

Adv. sci. technol. eng. syst. j.

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Solving the Unit Commitment problem (UCP) optimizes the combination of production units operations and determines the appropriate operational scheduling of each production units to satisfy the expected consumption which varies from one day to one month. Besides, each production unit is conducted to constraints that render this problem complex, combinatorial and nonlinear. In this paper, we proposed a new strategy based on the combination three optimization methods: Tabu search, Particle swarm optimization and Lagrangian relaxation methods in order to develop a proper unit commitment scheduling of the production units while reducing the production cost during a definite period. The proposed strategy has been implemented on a the IEEE 9 bus test system containing 3 production unit and the results were promising compared to strategies based on metaheuristic and deterministic methods.

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An Evolutionary Programming Based Tabu Search Method for Unit Commitment Problem with Cooling-Banking Constraints

Cited by 3 publications

References 32 publications

A Model of German Spot Power Market

A Model of German Spot Power Market

A Comprehensive Review on Evolutionary Optimization Techniques Applied for Unit Commitment Problem

Theoretical Investigation of Combined Use of PSO, Tabu Search and Lagrangian Relaxation methods to solve the Unit Commitment Problem

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