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1st International Conference and Exhibition on Transmission and Distribution in the Asia Pacific Region

作者： Senjyu, T Yamashiro, H Shimabukuro, K Uezato, K Funabashi, T Univ Ryukyus Fac Engn Dept Elect & Elect Engn Okinawa Japan

ISBN: (纸本)0780375254

This paper presents a new approach for large scale unit commitment problem. unit commitment(UC) problem plays major role in power system since the improvement of commitment schedule results in the reduction of operating cost. However, unit commitment problem is one of the most difficult optimization problem in power system, because this problem has many constraints. Moreover search space is vast. To overcome these problems, new genetic operator based on unit characteristic classification and unit integration technique are proposed. The proposed algorithm was tested on a reported UC problem. From simulation results, better solutions are obtained in comparison with previously reported results. Numerical results for system up to 100 units are compared to previously reported results.

关键词： unit commitment problem genetic algorithm characteristic classification of unit

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Optimal Control Formulations for the unit commitment problem 1

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5th International Conference on the Dynamics of Information Systems

作者： Fontes, Dalila B. M. M. Fontes, Fernando A. C. C. Roque, Luis A. C. Univ Porto LIAAD INESC TEC Rua Dr Roberto Frias P-4200464 Oporto Portugal Univ Porto Rua Dr Roberto Frias Inst Sistemas Robot Porto Fac Engn P-4200465 Porto Portugal Inst Super Engenharia Porto Dept Matemat Porto Portugal

ISBN: (数字)9783319100463

ISBN: (纸本)9783319100456

The unit commitment (UC) problem is a well-known combinatorial optimization problem arising in operations planning of power systems. It involves deciding both the scheduling of power units, when each unit should be turned on or off, and the economic dispatch problem, how much power each of the on units should produce, in order to meet power demand at minimum cost while satisfying a set of operational and technological constraints. This problem is typically formulated as nonlinear mixed-integer programming problem and has been solved in the literature by a huge variety of optimization methods, ranging from exact methods (such as dynamic programming and branch-and-bound) to heuristic methods (genetic algorithms, simulated annealing, and particle swarm). Here, we discuss how the UC problem can be formulated with an optimal control model, describe previous discrete-time optimal control models, and propose a continuous-time optimal control model. The continuous-time optimal control formulation proposed has the advantage of involving only real-valued decision variables (controls) and enables extra degrees of freedom as well as more accuracy, since it allows to consider sets of demand data that are not sampled hourly.

关键词： unit commitment problem Power systems planning Nonlinear optimization Mixed-integer programming Optimal control

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Diversity control approach to ant colony optimization for unit commitment problem.

Diversity control approach to ant colony optimization for un...

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IEEE Region 10 Conference on Analog and Digital Techniques in Electrical Engineering

作者： Nualhong, D Chusanapiputt, S Phomvuttisarn, S Saengsuwan, T Jantarang, S Elect Generating Author Thailand Dept Elect Engn Bangkok Thailand

ISBN: (纸本)0780385608

This paper presents a new method to solve the constrained unit commitment problem by applying Ant Colony Optimization (A CO) based on the diversity control approach. The pheromone updating rule is modified to control the diversification by adopting a simple mechanism for random selection in ACO. The proposed method is tested on the 10-unit test system with a scheduling time horizon of 24 hours. The numerical results show an economical saving in the total operating cost when compared to the previous literature results. Moreover, two types of the proposed diversity control technique have the features of easy implementation and a better convergence rate superior to a standard ACO.

关键词： power generation dispatch power generation scheduling power generation economics power generation control optimisation unit commitment problem ant colony optimization diversity control approach 10-unit test system total operating cost Power generation dispatch machine unit Ant colony optimization power generation control Power generation economics Manufacturing costs

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VNS based heuristic for solving the unit commitment problem

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Electronic Notes in Discrete Mathematics 2012年 39卷 153-160页

作者： Todosijević, Raca Mladenović, Marko Hanafi, Saïd Crévits, Igor LAMIH Université de Valenciennes et du Hainaut Cambrésis France

unit commitment problem for thermal units consists of finding an optimal electricity production plan in a long time horizon. In this paper, we propose an hybrid approach which combines Variable Neighborhood Search metaheuristic and mathematical programming to solve this NP-Hard problem. For each period, the economic dispatch problem which can be formulated as a convex programming problem is solved by the Lambda iteration method. Extensive computational experiments are performed on well-known test instances from literature. The proposed method successfully solved both small and large scale problems and offers the best results for the problem compared to the well-known metaheuristics used for solving it. © 2012 Elsevier B.V.

关键词： Lambda Iteration method unit commitment problem VNS

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A Binary-Real-Coded Differential Evolution for unit commitment problem: A Preliminary Study

A Binary-Real-Coded Differential Evolution for Unit Commitme...

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5th Multi-Disciplinary International Workshop on Artificial Intelligence, MIWAI-2011

作者： Dutta, Saptarshi Datta, Dilip Royal Grp Inst Royal Sch Engn & Technol Dept Mech Engn Gauhati 781035 India Natl Inst Technol Dept Engn Mech Silchar 788010 India

ISBN: (纸本)9783642257247;9783642257254

Due to its economical importance, the unit commitment problem has become a matter of concern in power systems, and consequently an important area of research. It is a nonlinear mixed-integer optimization problem, in which a given number of power generating units are to be scheduled in such a way that the forecasted demand is met at minimum production cost over a time horizon. In this paper a binary-real-coded differential evolution along with some repairing mechanisms is investigated as the solution technique of the problem. In the computational experiment carried out with a hypothetical 10-unit power system over 24-hour time horizon, available in the literature, the proposed technique is found outperforming all the existing methods.

关键词： unit commitment problem differential evolution repairing mechanisms

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Re-Scheduling the unit commitment problem in Fuzzy Environment

Re-Scheduling the Unit Commitment Problem in Fuzzy Environme...

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IEEE International Conference on Fuzzy Systems (FUZZ 2011)

作者： Wang, Bo Li, You Watada, Junzo Waseda Univ Grad Sch Informat Prod & Syst Kitakyushu Fukuoka 8080135 Japan

ISBN: (纸本)9781424473175

The conventional prediction of future power demands are always made based on the historical data. However, the real power demands are affected by many other factors as weather, temperature and unexpected emergencies. The use of historical information alone cannot well predict real future demands. In this study, the experts' opinions from related fields are taken into consideration. To deal the uncertainty of historical data and imprecise experts' opinions, we employ fuzzy variables to better characterize the forecasted future power loads. The conventional unit commitment problem (UCP) is updated here by considering the spinning reserve costs in a fuzzy environment. As the solution, we proposed a heuristic algorithm called local convergence averse binary particle swarm optimization (LCA-PSO) to solve the UCP. The proposed model and algorithm are used to analyze several test systems. The comparisons between the proposed algorithm and the conventional approaches show that the LCA-PSO performs better in finding the optimal solutions.

关键词： Power supply reliability Fuzzy set theory unit commitment problem Fuzzy Value-at-Risk Local convergence averse binary particle swarm optimization Test systems

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Hybrid Approach For unit commitment problem 6

Hybrid Approach For Unit Commitment Problem

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6th IEEE International Conference on Power Systems (ICPS)

作者： Shukla, Anup Singh, S. N. Indian Inst Technol Kanpur Dept Elect Engn Kanpur India

ISBN: (纸本)9781509001286

In a vertically integrated power system, power utilities extensively performs unit commitment to plan the optimal scheduling of generating units in the system. In this paper hybrid approach utilizing dynamic programming along with particle swarm optimization is proposed to solve unit commitment problem (UCP), under consideration of different constraints related to unit, system and power flow. The proposed approach is divided into outer and inner dependent sub problems, which are discrete and continuous, respectively. The effectiveness of the proposed approach is tested on IEEE 30-bus system. A simulation result demonstrates the potential of proposed approach.

关键词： unit commitment problem dynamic programming particle swarm optimization power flow

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An intelligent computing technique based on a dynamic-size subpopulations for unit commitment problem

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OPSEARCH 2019年第3期56卷 911-944页

作者： El-Shorbagy, M. A. Mousa, A. A. Farag, M. A. Prince Sattam bin Abdulaziz Univ Coll Sci & Humanities Al Kharj Dept Math Al Kharj 11942 Saudi Arabia Menoufia Univ Fac Engn Dept Basic Engn Sci Shibin Al Kawm Egypt Taif Univ Fac Sci Dept Math & Stat At Taif Saudi Arabia

A new intelligent computing based approach for solving multi-objective unit commitment problem (MOUCP) and its fuzzy model is presented in this paper. The proposed intelligent approach combines binary-real-coded genetic algorithm (BRCGA) and K-means clustering technique to find the optimal schedule of the generation units in MOUCP. BRCGA is used in order to tackle both the unit scheduling and load dispatch problems. While, K-means clustering technique is used to divide the population into a specific number of subpopulation with-dynamic-sizes. In this way, different genetic algorithm (GA) operators can apply to each sub-population, instead of using the same GA operators for all population. The proposed intelligent algorithm has been tested on standard systems of MOUCPs. The results showed the efficiency of the proposed approach to solve (MOUCP) and its fuzzy model.

关键词： unit commitment problem Intelligent computing Genetic algorithm Dynamic subpopulation structure

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A unit commitment problem by using genetic algorithm based on unit characteristic classification

A unit commitment problem by using genetic algorithm based o...

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Winter Meeting of the IEEE-Power-Engineering-Society

作者： Senjyu, T Yamashiro, H Uezato, K Funabashi, T Univ Ryukyus Dept Elect & Elect Engn Fac Engn Okinawa Japan

ISBN: (纸本)0780373227

This paper presents new approach for thermal unit commitment problem. unit commitment(UC) problem plays major role in power system since the improvement of commitment schedule results in the reduction of operating cost. However, unit commitment problem is one of the most difficult optimization problem in power system, because this problem has many constraints. Further, these constraints varies with each unit. To handle these constraints, some cording methods has been proposed. However, these methods require computation time. To overcome these problems, new genetic operator based on unit characteristic classification and intelligent technique generating initial populations are introduced. The proposed algorithm was tested on a reported UC problem. From simulation results, satisfactory solutions are obtained in comparison with previously reported results. Numerical results for system of up to 100 units are compared to previously reported results.

关键词： unit commitment problem Genetic algorithm Characteristic classification of unit.

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Optimization of unit commitment problem with ramp-rate constraint and wrap-around scheduling

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ELECTRIC POWER SYSTEMS RESEARCH 2019年 177卷 105948-000页

作者： Deka, Dimbalita Datta, Dilip Tezpur Univ Sch Engn Dept Mech Engn Tezpur 784028 Assam India

The unit commitment problem (UCP) is one of the most studied problems in power systems. The scheduling of the units to meet the forecasted power demand at each time instant at the minimum production cost, subject to a set of system constraints, makes it a complex nonlinear mixed-integer optimization problem. The complexity of the UCP increases further if the dynamic power limit based ramp-rate constraint is also taken into account. In the present work, the problem is made even more complicated by implementing the concept of wrap-around in scheduling, which allows to handle another practical scenario that a planning horizon is the repetition of a production cycle, e.g., a week in the UCP can be handled as the repetition of days, or a month as the repetition of weeks or days. Owing the inadequacy of deterministic methods to tackle this complicated model of the UCP, real-binary variants of three evolutionary algorithms are investigated and their comparative performances on some benchmark instances are analyzed.

关键词： unit commitment problem Scheduling Optimization Evolutionary algorithms

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