• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1485-1495
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• 2009

This paper presents a novel approach to economic dispatch (ED) with nonconvex fuel cost function as combinatorial optimization problems (COP) while most of the conventional researches have been developed as function optimization problems (FOP). One nonconvex fuel cost function can be divided into several convex fuel cost functions, and each convex function can be regarded as a generation type (G-type). In that case, ED with nonconvex fuel cost function can be considered as COP finding the best case among all feasible combinations of G-types. In this paper, a genetic algorithm is applied to solve the COP, and the ${\lambda}-P$ function method is used to calculate ED for the fitness function of GA. The ${\lambda}-P$ function method is reviewed briefly and the GA procedure for COP is explained in detail. This paper deals with two kinds of ED problems, namely ED with multiple fuel units (EDMF) and ED with prohibited operating zones (EDPOZ). The proposed method is tested for all the ED problems, and the test results show an improvement in solution cost compared to the results obtained from conventional algorithms.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.10
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• pp.480-488
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• 2001

This paper presents a technique that can obtain an optimal solution for the Security-Constrained Economic Dispatch (SCED) problems using the Interior Point Method (IPM) while taking into account of the power flow constraints. The SCED equations are formulated by using only the real power flow equations from the optimal power flow. Then an algorithm is presented that can linearize the SCED equations based on the relationships among generation real power outputs, loads, and transmission losses to obtain the optimal solutions by applying the linear programming (LP) technique. The objective function of the proposed linearization algorithm are formulated based on the fuel cost functions of the power plants. The power balance equations utilize the Incremental Transmission Loss Factor (ITLF) corresponding to the incremental generation outputs and the line constraints equations are linearized based on the Generalized Generation Distribution Factor (GGDF). Finally, the application of the Primal Interior Point Method (PIPM) for solving the optimization problem based on the proposed linearized objective function is presented. The results are compared with the Simplex Method and the promising results ard obtained.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.80-89
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• 2013

This paper presents an efficient approach for solving economic dispatch (ED) problems with nonconvex cost functions using a 'Mean-Variance Optimization (MVO)' algorithm with Kuhn-Tucker condition and swap process. The aim of the ED problem, one of the most important activities in power system operation and planning, is to determine the optimal combination of power outputs of all generating units so as to meet the required load demand at minimum operating cost while satisfying system equality and inequality constraints. This paper applies Kuhn-Tucker condition and swap process to a MVO algorithm to improve a global minimum searching capability. The proposed MVO is applied to three different nonconvex ED problems with valve-point effects, prohibited operating zones, transmission network losses, and multi-fuels with valve-point effects. Additionally, it is applied to the large-scale power system of Korea. The results are compared with those of the state-of-the-art methods as well.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.468-476
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• 2008

This paper presents a novel approach to economic dispatch (ED) with nonconvex fuel cost function as combinatorial optimization problems (COP) while most of the conventional researches have been developed as function optimization problems (FOP). One nonconvex fuel cost function can be divided into several convex fuel cost functions, and each convex function can be regarded as a generation type (G-type). In that case, ED with nonconvex fuel cost function can be considered as COP finding the best case among all feasible combinations of G-types. In this paper, a genetic algorithm is applied to solve the COP, and the $\lambda$-P table method is used to calculate ED for the fitness function of GA. The $\lambda$-P table method is reviewed briefly and the GA procedure for COP is explained in detail. This paper deals with three kinds of ED problems, namely ED considering valve-point effects (EDVP), ED with multiple fuel units (EDMF), and ED with prohibited operating zones (EDPOZ). The proposed method is tested for all three ED problems, and the test results show an improvement in solution cost compared to the results obtained from conventional algorithms.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.926-928
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• 1998

A fast optimization algorithm has been evolved from a simple two stage optimal power flow(OPF) algorithm for constrained power economic dispatch. In the proposed algorithm, we consider various constraints such as power balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the coupled LP based OPF method to an average gain of 53.13 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1658-1666
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• 2009

This paper proposes an approach of Mult_HPSO based on the PC cluster system to reduce or remove the stagnation on an early convergence effect of PSO, reduce an execution time and improve a search ability on an optimal solution. Hybrid PSO(HPSO) is combines the PSO(Particle Swarm Optimization) with the mutation of conventional GA(Genetic Algorithm). The conventional PSO has operated a search process in a single swarm. However, Multi_PSO operates a search process through multiple swarms, which increments diversity of expected solutions and reduces the execution time. Multiple Swarms are composed of unsynchronized PC clusters. We apply to SCED(security constrained economic dispatch) problem, a nonlinear optimization problem, which considers line flow constraints and N-1 line contingency constraints. To consider N-1 line contingency in power system, we have chosen critical line contingency through a process of Screening and Selection based on PI(performace Index). We have applied to IEEE 118 bus system for verifying a usefulness of the proposed approaches.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.734-736
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• 1999

The electricity demand has been in the trend of increase for the past 30 years except last year due to economic crisis. The central electrical power dispatch center anticipates each and every hour's electricity demand and dispatch every power plant's output(MW) taking into account of the costs, frequency regulation abilities, locations, reliabilities and so on. to meet the demand as quickly as possible. The large portion of the power plants' output is contolled automatically by the AGC(Automatic Generation Control) function which is a part of the EMS(Energy Manage System) computer in the dispatch center. To receive the electrical power dispatch signal from the EMS, a power plant should have a remote MW control feature in the turbine control system or unit master control system. We investigated the AGC function and a power plant's remote MW control configuration.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.199-206
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• 2008

The introduction of competition in electricity markets emphasizes the importance of sufficient transmission capacities to guarantee effective power transactions. Therefore, for the economic and stable electric power system operation, transmission security constrains should be incorporated into the dispatch scheduling problem. With the intent to solve this problem, we decompose a dispatch scheduling problem into a master problem(MP) and several subproblems(SPs) using Benders decomposition. The MP solves a general optimal power flow(OPF) problem while the SPs inspect the feasibility of OPF solution under respective transmission line contingencies. If a dispatch scheduling solution given by the MP violates transmission security constraints, then additional constraints corresponding to the violations are imposed to the MP. Through this iterative process between the MP and SPs, we derive an optimal dispatch schedule incorporating the post-contingency corrective rescheduling. In addition, we consider interruptible loads as active control variables since the interruptible loads can participate as generators in competitive electricity markets. Numerical examples demonstrate the efficiency of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.636-639
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• 1987

• Journal of Energy Engineering
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• v.16 no.1 s.49
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• pp.40-45
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• 2007

Many countries have been preparing the exercise of UNFCCC (United Nations Framework Convention on Climate Change). If UNFCCC is enforced, considerable changes in generation sector are expected due to the imposed greenhouse gas emission. This paper proposes dispatch scheduling algorithms which incorporate the emission constraints and emission trading. Numerical examples are provided to demonstrate the availability these algorithms.