• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.3
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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.

• Proceedings of the KIEE Conference
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• 2002.11b
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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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.

• Proceedings of the KIEE Conference
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• 2000.07a
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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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.5
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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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.6
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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.

• Proceedings of the KIEE Conference
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• 1989.11a
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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.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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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.