• 제목/요약/키워드: Hydro-thermal scheduling

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확률 타부 탐색법을 이용한 수화력 계통의 경제운용에 관한 연구 (Hydro-Thermal Optimal Scheduling Using Probabilistic Tabu Search)

  • 김형수;문경준;박준호
    • 대한전기학회논문지:전력기술부문A
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    • 제51권3호
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    • pp.153-161
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    • 2002
  • In this paper, we propose a Probabilistic Tabu Search(PTS) method for hydro-thermal scheduling. Hydro scheduling has many constraints and very difficult to solve the optical schedule because it has many local minima. To solve the problem effectively, the proposed method uses two procedures, one is Tabu search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify its search region. To adjust Parameters such as a reducing rate and initial searching region, search strategy is selected according to its probability after restarting procedure. Dynamic decoding method was also used to restrict a search region and to handle water balance constraints. In order to show the usefulness of the proposed method, the PTS is applied on two cases which have independent or dependent hydro plants and compared to those of other method. The simulation results show it is very efficient and useful algorithm to solve the hydro-thermal scheduling problem.

확률 타부 탐색법을 이용한 수화력 계통의 경제운용 (Hydro-Thermal Optimal Scheduling Using Probabilistic Tabu Search)

  • 김형수;박준호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 추계학술대회 논문집 전력기술부문
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    • pp.76-79
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    • 2002
  • In this paper, we propose a Probabilistic Tabu Search(PTS) method for hydro-thermal scheduling. Hydro scheduling has many constraints and very difficult to solve the optimal schedule because it has many local minima. To solve the problem effectively, the proposed method uses two procedures, one is Tabu search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify its search region. To adjust parameters such as a reducing rate and initial searching region, search strategy is selected according to its probability after Restarting procedure. In order to show the usefulness of the proposed method, the PTS is applied on two cases which have dependent hydro plants and compared to those of other method. The simulation results show it is very efficient and useful algorithm to solve the hydro-thermal scheduling problem.

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발전기보수유지계획을 고려한 CO2배출량의 추정 (Assessment of the CO2 Emission Considering the Generator Maintenance Scheduling)

  • 전동훈;박정제;오태곤;조경희;최재석;백웅기
    • 전기학회논문지
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    • 제59권9호
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    • pp.1507-1513
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    • 2010
  • The $CO_2$ emission can be decreased due to freedom of generator maintenance scheduling(GMS). This paper proposes assessment of $CO_2$ emission considering generator maintenance scheduling(GMS) and evaluates effect of the GMS on $CO_2$ emission. And also, this paper assesses the $CO_2$ emission and the probabilistic production cost simulation of nuclear and thermal power generators considering operation of hydro and pumped generator. The minimum reliability criterion level satisfied production cost minimization function model is used in this paper. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system in Korea in 2010.

Tabu 탐색법을 이용한 수화력 계통의 단기 운용 계획 (A Short Term Hydro-Thermal Scheduling using Tabu Search)

  • 김성기;김형수;문경준;황기현;박준호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 A
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    • pp.331-333
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    • 2000
  • This paper propose the method combined Priority and Tabu search (TS) for short term hydro-thermal scheduling. We satisfy various conditions using TS, Restarting method is used as diversification strategy of TS to prevent a local convergence. Also, we use Lagrangian method to solve economic dispatch problems.

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진화 프로그래밍기법을 적용한 단기 수화력 운용 (A Short Term Hydro-Thermal Scheduling using Evolutionary Programming)

  • 김재철;백영식
    • 대한전기학회논문지:전력기술부문A
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    • 제48권8호
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    • pp.917-923
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    • 1999
  • This paper proposes an efficient method of hydro-thermal scheduling in coordination with head variation and hydraulically coupled plants using Evolutionary Programing(EP). Based on the EP technique, the proposed algorithm is capable of determining the global optimal solutions. The constraints such a power balance condition, water available condition and transmission losses are embedded and satisfied throughout the proposed EP approach. The effectiveness of the proposed approach is demonstrated on the test systems and compared to those of other method. The results show that the new approach obtains a more highly optimal solutions than the conventional other methods such as newton-raphson method, Dynamic Programming(DP), LU factorization.

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기동정지계획을 고려한 제수발전소의 주간 운용에 관한 연구 (A Study on the Weekly Operation planning of pumped Hydrostorage plant Considering Unit Commitment)

  • 송길영;홍상은;김영태
    • 대한전기학회논문지
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    • 제36권5호
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    • pp.319-327
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    • 1987
  • This paper presents a dynamic programming sucdessive approximation algorithm for scheduling pumped storage hydro plants and shows how this method can be coordinated with the commitment of the thermal units of the system. The general object of operation of pumped hydrostorage plants is the minimization of the overall production cost and the maximization of generation reserves. The basic procedure used to obtain a combined pumped storage-unit commitment schedule is to execute the pumped storage scheduler and unit commitment scheduler iteratively. A combined DPSA algorithm has been presented to coordinate the scheduling of the pumped storage with the scheduling of the thermal units.

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수력,양수 및 다중모델을 고려한 새로운 확률론적 발전시뮬레이션 (A New Probabilistic Generation Simulation Considering Hydro, Pumped-Storage Plants and Multi-Model)

  • 송길영;최재석
    • 대한전기학회논문지
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    • 제40권6호
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    • pp.551-561
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    • 1991
  • The probabilistic generation simulation plays a key role in power system expansion and operational planning especially for the calculation of expected energy, loss of load probaility and unserved energy expected. However, it is crucial to develop a probabilistic generation simulation algorithm which gives sufficiently precise results within a reasonable computation time. In a previous paper, we have proposed an efficent method using Fast Hartley Transform in convolution process for considering the thermal and nuclear units. In this paper, a method considering the scheduling of pumped-storage plants and hydro plants with energy constraint is proposed. The method also adopts FHT techniques. We improve the model to include multi-state and multi-block generation. The method has been applied for a real size model system.

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고속 Hartley 변환을 이용한 확률론적 발전 시뮬레이션에 관한 연구 -수력 및 양수발전기의 운전을 고려한 경우- (A Study on the Probabilistic Production Costing Simulation using Fast Hartley Transform - with considering Hydro and Pumped-Storage Plants -)

  • 송길영;최재석;김용하
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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    • pp.194-196
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    • 1989
  • The production costing plays a key role in power system expansion and operations planning especially for the calculation of expected energy, loss of load probability and unserved energy. Therefore, it is crucial to develope a probabilistic production costing algorithm which gives sufficiently precise results within a reasonable computational time. In this respect, a number of methods of solving production simulation have been proposed. In previous paper we proposed the method used Fast Hartley Transform in convolution process with considering only the thermal units. In this paper, the method considering the scheduling of pumped-storage plants and hydro plants with energy constraints is proposed.

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Enhanced Particle Swarm Optimization for Short-Term Non-Convex Economic Scheduling of Hydrothermal Energy Systems

  • Jadoun, Vinay Kumar;Gupta, Nikhil;Niazi, K. R.;Swarnkar, Anil
    • Journal of Electrical Engineering and Technology
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    • 제10권5호
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    • pp.1940-1949
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    • 2015
  • This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.