• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.6
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• pp.331-338
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• 1988

A simple algorithm is presented for solving the thermal unit commitment problem which is one of very important areas in economic operation of power systems. This algorithm is based on simple priority ordering by the unit operation cost and it is shown that the operation cost of chosen sets of generators is the minimum. The proposed method differs from the conventional priority-based formulations in that the unit operation are calculated in every load level. Further the poerating reserve requiements are satisfied by the newly derived analytical security function or the expectation of reserve. The proposed method is proven to be very simple, accurate and efficient in a sample system.

• Journal of Power Electronics
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• v.13 no.3
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• pp.437-446
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• 2013

This paper proposes a design scheme for an LCL-filter used for the three-parallel operation of the power converters in high-capacity wind turbines. The designs of the power devices and grid connected filter are difficult due to the high level voltages and currents in huge-capacity wind turbines. To solve these problem, this paper presents three-parallel operation and LCL-filter design techniques optimized by parallel operation. Furthermore, the design of an inverter side inductance of the LCL-filter is discussed in detail considering the switching modulation method. Simulation and experimental results demonstrate the validity of the designed filter and wind turbines.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1999-2004
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• 2004

Collision avoidance for the aircraft can be stated as a problem of maintaining a safe distance between aircrafts in conflict. Optimal collision avoidance problem seeks to minimize the given cost function while simultaneously satisfying the constraints. The cost function can be a function of time or input. This paper addresses the trajectory time-optimization problem for collision avoidance of the unmanned aerial vehicles. The problem is difficult to handle, because it is a two points boundary value problem with dynamic environment. Some simplifying algorithms are used for application in on-line operation. Although there are more complicated problems, by prediction of conflict time and some assumptions, we changed a dynamic environment problem into a static one.

• Korean Management Science Review
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• v.25 no.1
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1721-1730
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• 2007

SThis paper proposes a new dispatch scheduling algorithm in interconnected regional system operations. The dispatch scheduling formulated as mixed integer non-linear programming (MINLP) problem can efficiently be computed by generalized Benders decomposition (GBD) algorithm. GBD guarantees adequate computation speed and solution convergency since it decomposes a primal problem into a master problem and subproblems for simplicity. In addition, the inter-temporal optimal power flow (OPF) subproblem of the dispatch scheduling problem is comprised of various variables and constraints considering time-continuity and it makes the inter-temporal OPF complex due to increased dimensions of the optimization problem. In this paper, regional decomposition technique based on auxiliary problem principle (APP) algorithm is introduced to obtain efficient inter-temporal OPF solution through the parallel implementation. In addition, it can find the most economic dispatch schedule incorporating power transaction without private information open. Therefore, it can be expanded as an efficient dispatch scheduling model for interconnected system operation.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.222-224
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• 2006

This paper addresses a particle swarm optimization-based approach for solving a generating unit maintenance scheduling problem(GMS) with some constraints. We focus on the power system reliability such as reserve ratio better than cost function as the objective function of GMS problem. It is shown that particle swarm optimization-based method is effective in obtaining feasible schedules such as GMS problem related to power system planning and operation. In this paper, we find the optimal solution of the GMS problem within a specific time horizon using particle swarm optimization algorithm. Simple case study with 16-generators system is applicable to the GMS problem. From the result, we can conclude that PSO is enough to look for the optimal solution properly in the generating unit maintenance scheduling problem.

• Journal of the Korean Society for Railway
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• v.9 no.2 s.33
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• pp.206-211
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• 2006

This thesis presents railroad crew restoring problem, which is to determine the railroad plan allocation. This problem is constructed that determine the sequence of duties that railroad crews have to perform. We analyze characteristic of this problem and railroad industry. It's hard to consider many constraint conditions. We propose Integer Programming model and easy methodology to be considered all given operation rules. This problem is known to be NP-hard. We develop a genetic algorithm, which is proved to be powerful in solving optimization problems. We proposed the effective mathematical model and algorithm about making crew restoring in real industry.

• IE interfaces
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• v.12 no.1
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• pp.94-101
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• 1999

The set covering(SC) problem is the problem of covering all the rows of an $m{\times}n$ matrix of ones and zeros by a subset of columns with a minimal cost. It has many practical applications of modeling of real world problems. The SC problem has been proven to be NP-complete and many algorithms have been presented to solve the SC problem. In this paper we present hybrid simulated annealing(HSA) algorithm based on the Simulated Annealing(SA) for the SC problem. The HSA is an algorithm which combines SA with a crossover operation in a genetic algorithm and a local search method. Our experimental results show that the HSA obtains better results than SA does.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.3_4
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• pp.117-129
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• 2003

In this paper, we propose advanced parallel join algorithm to efficiently process join operation on hypercube systems. This algorithm uses a broadcasting method in processing relation R which is compatible with hypercube structure. Hence, we can present optimized parallel join algorithm for that hypercube structure. The proposed algorithm has a complete solution of two essential problems - load balancing problem and data skew problem - in parallelization of join operation. In order to solve these problems, we made good use of the characteristics of clustering effect in the algorithm. As a result of this, performance is improved on the whole system than existing algorithms. Moreover. new algorithm has an advantage that can implement non-equijoin operation easily which is difficult to be implemented in hash based algorithm. Finally, according to the cost model analysis. this algorithm showed better performance than existing parallel join algorithms.

• IE interfaces
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• v.24 no.3
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• pp.220-230
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• 2011

The multi-reservoir operation problem for efficient utilization of water resources involves conflicting objectives, and the problem can be solved by varying weight coefficient on objective functions. Accordingly, decision makers need to choose appropriate weight coefficients balancing the trade-offs among multiple objectives. Although the appropriateness of the weight coefficients may depend on the total amount of water inflow, reservoir operating policy may not be changed to a certain degree for different hydrological conditions on inflow. Therefore, we propose to use fuzzy Data Envelopment Analysis (DEA) to rank the weight coefficients in consideration of the inflow variation. In this approach, we generate a set of Paretooptimal solutions by applying different weight coefficients on Coordinated Multi-reservoir Operating Model. Then, we rank the Pareto-optimal solutions or the corresponding weight coefficients by using Fuzzy DEA model. With the proposed approach, we can suggest the best weight coefficients that can produce the appropriate Pareto-optimal solution considering the uncertainty of inflow, whereas the general DEA model cannot pinpoint the best weight coefficients.