• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.415-422
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• 2014

This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.203-205
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• 1999

The unit commitment is an important problem of production scheduling which determines the generating unit to in service(on/off) during scheduling period, to meet system demand and reserve requirement at minimum cost. This paper presents an box type crossover to improve searching ability of GA, to solve unit commitment problem. Satisfactory results are obtained by GA with the proposed crossover operator.

• 산업공학
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• 제20권2호
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• pp.186-194
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• 2007

Recent deregulation of Korean electricity industry has made each power generation company pay more attention to maximizing its own profit instead of minimizing the overall system operation cost while guaranteeing system security. Electricity power generation problem is typically defined as the problem of determining both the on and off status and the power generation level of each generator under the given fuel constraints, which has been known as Profit-Based Unit Commitment (PBUC) problem. To solve the PBUC problem, the previous research mostly focused on devising Lagrangian Relaxation (LR) based heuristic algorithms due to the complexity of the problem and the nonlinearity of constraints and objectives. However, these heuristic approaches have been reported as less practical in real world applications since the computational run time is usually quite high and it may take a while to implement the devised heuristic algorithms as software applications. Especially when considering long-term planning problem which spans at least one year, the complexity becomes higher. Therefore, this paper proposes an explicit column generation algorithm using power generation patterns and the proposed algorithm is successfully applied to a Korean power generation company. The proposed scheme has a robust structure so that it is expected to extend general PBUC problems.

• Journal of Electrical Engineering and Technology
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• 제4권2호
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• pp.159-167
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• 2009

This paper presents the Improved Pre-prepared Power Demand (IPPD) table and Muller's method as a means of solving the Profit Based Unit Commitment (PBUC) problem. In a deregulated environment, generation companies (GENCOs) schedule their generators to maximize profits rather than to satisfy power demand. The PBUC problem is solved by the proposed approach in two stages. Initially, information concerning committed units is obtained by the IPPD table and then the subprob-lem of Economic Dispatch (ED) is solved using Muller's method. The proposed approach has been tested on a power system with 3 and 10 generating units. Simulation results of the proposed approach have been compared with existing methods and also with traditional unit commitment. It is observed from the simulation results that the proposed algorithm provides maximum profit with less computational time compared to existing methods.

• 대한전기학회논문지
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• 제43권3호
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• pp.351-362
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• 1994

This paper presents a new method for solving a long term unit commitment problem including hydro and pumped storage hydro units in a large scale power system. The proposed method makes it possible to get variable power of hydro and pumpde storage hydro units and results in the better unit commitment with good convergency. Moreover this paper proposes an unit commitment algorithm to consider variable power of these units effectively by Lagrangian Relaxation method. By applying the proposed method to the test system and the real system, it is verified the usefulness of this method.

• 경영과학
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• 제25권1호
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• pp.43-53
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• 2008

This paper considers a profit-based unit commitment problem with fuel consumption constraint and maintenance cost, which is one of the key decision problems in electricity industry. The nature of non-linearity inherent in the constraints and objective functions makes the problem intractable which have led many researches to focus on Lagrangian based heuristics. To solve the problem more effectively, we propose mixed integer programming based solution algorithm linearizing the complex non-linear constraints and objectives functions. The computational experiments using the real-world operation data taken from a domestic electricity power generator show that the proposed algorithm solves the given problem effectively.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.359-360
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• 2006

This paper introduces a variable of methodology and models of solving Security-Constrained Price-Based Unit Commitment(SPUC) Problems in the Deregulated Power Market. The objective of SPUC is coordination between GENCOs and the ISO. GENCOs apply Price-Based Unit Commitment(PBUC) without security constraints and submit capacity bids to the ISO for maximizing their revenues. Using generation data and transmission data obtained from TRANSCOs, the ISO applies Security-Constrained Unit Commitment(SCUC), executes congestion management and contingency analysis for minimizing line flow violations and the risk supplying loads. Considering analysis data, the ISO should adjust GENCOS' bid. In this paper, we presents the result of survey and analyze on the approach of the SPUC problem.

• Journal of Electrical Engineering and Technology
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• 제3권4호
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• pp.514-519
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• 2008

The non-separable quadratic penalty terms create an inherent difficulty when applying the standard augmented Lagrangian relaxation(ALR) method for decomposing the unit commitment problem into independent subproblems. This paper presents a separable augmented Lagrangian relaxation method for solving the unit commitment problem. The proposed method is designed to have a separable structure by introducing the quadratic terms with additional auxiliary terms in the augmented Lagrangian function. Numerical results are presented to validate the effectiveness of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1506-1509
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• 1999

This paper presents a new economic dispatch algorithm to improve the unit commitment solution while guaranteeing the near optimal solution without reducing calculation speed. The conventional economic dispatch algorithms have the problem that it is not applicable to the unit commitment formulation due to the frequent on/off state changes of units during the unit commitment calculation. Therefore, piecewise linear iterative method have generally been used for economic dispatch algorithm for unit commitment. In that method, the approximation of the generator cost function makes it hard to obtain the optimal economic dispatch solution. In this case, the solution can be improved by introducing a inverse of the incremental cost function. The proposed method is tested with sample system. The results are compared with the conventional piecewise linear iterative method. It is shown that the proposed algorithm yields more accurate and economical solution without calculation speed reduction.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.711-713
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• 1996

This paper proposes a unit commitment scheduling method based on Genetic Algorithm(GA). Due to a variety of constraints to be satisfied, the search space of the UC problem is highly nonconvex, so the UC problem cannot be solved efficiently only using the standard GA To efficiently deal with the constraints of the problem and greatly reduce the search space of the GA, the minimum up and down time constraints are embedded in the binary strings that are coded to represent the on-off states of the generating units. The violations of other constraints arc handled by integrating penalty factors. To show the effectiveness of the GA based unit commitment scheduling, test results for system of 5 units are compared with results obtained using Lagrangian Relaxation and Dynamic Programming.