• 제목/요약/키워드: operational constraints

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최적화 기법에 의한 발전시뮬레이션 방법론의 개발 및 전원확충계획 문제에의 적용 (The Development of Production Simulation Methodology by Optimization Technique and It's Application to Utility Expansion Planning)

  • 송길영;오광해;김용하;차준민
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.793-796
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    • 1996
  • This study proposes a new algorithm which performs a production simulation under various constraints and maintains computational efficiency. In order to consider the environmental and operational constraints, the proposed algorithm is based on optimization techniques formulated in LP form In the algorithm, "system characteristic constraints" reflect the system characteristics such as LDC shape, unit loading order and forced outage rate. By using the concept of Energy Invariance Property and two operational rules i.e. Compliance Rule for Emission Constraint, Compliance Rule for Limited Energy of Individual Unit, the number of system characteristic constraints is appreciably reduced. As a solution method of the optimization problem, the author uses Karmarkar's method which performs effectively in solving large scale LP problem. The efficiency of production simulation is meaningful when it is effectively used in power system planning. With the proposed production simulation algorithm, an optimal expansion planning model which can cope with operational constraints, environmental restriction, and various uncertainties is developed. This expansion planning model is applied to the long range planning schemes by WASP, and determines an optimal expansion scheme which considers the effect of supply interruption, load forecasting errors, multistates of unit operation, plural limited energy plants etc.

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다단계 공급체인에서의 장비운용가용도 시뮬레이션 분석 (An Operational Availability Analysis in Supply Chain Using Simulation)

  • 박세훈;문성암
    • 한국시스템다이내믹스연구
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    • 제12권1호
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    • pp.115-130
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    • 2011
  • This study shows the operational availability(Ao) analysis of the supply chain with maintenance functions using the system dynamics simulation. The simulation uses 60 equipments which are serial systems composed by 4 major components. And every entities are connected each other by causal loops. So whole simulation executed like one organic system. Specially we consider 2 constraints, one is the number of spare parts and the other is maintenance capacity level. 2 constraints have 11 levels each so the simulation has 121(11*11) scenarios which scenario has 30 different random number seed. The simulation executed total 3,630(11*11*30) times. We analysis average Ao of total equipments by 121 scenarios and additionally the regression of the average Ao and 2 constraints. As the result, we can get the more accurate values by the system dynamics simulation than the regression to analysis complex system like the supply chain with maintenance functions.

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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.

Analytical design of constraint handling optimal two parameter internal model control for dead-time processes

  • Tchamna, Rodrigue;Qyyum, Muhammad Abdul;Zahoor, Muhammad;Kamga, Camille;Kwok, Ezra;Lee, Moonyong
    • Korean Journal of Chemical Engineering
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    • 제36권3호
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    • pp.356-367
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    • 2019
  • This work presents an advanced and systematic approach to analytically design the optimal parameters of a two parameter second-order internal model control (IMC) filter that satisfies operational constraints on the output process, the manipulated variable as well as rate of change of the manipulated variable, for a first-order plus dead time (FOPDT) process. The IMC parameters are designed to minimize a control objective function composed of the weighted sum of the error between the process variable and the set point, and the rate of change of the manipulated variable, and to satisfy the desired constraints. The feasible region of the constrained IMC control parameters was graphically analyzed, as the process parameters and the constraints varied. The resulting constrained IMC control parameters were also used to find the corresponding industrial proportional-integral controller parameters of a Smith predictor structure.

Opposition Based Differential Evolution Algorithm for Dynamic Economic Emission Load Dispatch (EELD) with Emission Constraints and Valve Point Effects

  • Thenmalar, K.;Ramesh, S.;Thiruvenkadam, S.
    • Journal of Electrical Engineering and Technology
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    • 제10권4호
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    • pp.1508-1517
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    • 2015
  • Optimal Power dispatch is the short-term decision of the optimal output of a number of power generation facilities, to meet the system demand, with the objective of Power dispatching at the lowest possible cost, subject to transmission lines power loss and operational constraints. The operational constraint includes power balance constraint, generator limit constraint, and emission dispatch constraint and valve point effects. In this paper, Opposition based Differential Evolution Algorithm (ODEA) has been proposed to handle the objective function and the operational constraints simultaneously. Furthermore, the valve point loading effects and transmission lines power loss are also considered for the efficient and effective Power dispatch. The ODEA has unique features such as self tuning of its control parameters, self acceleration and migration for searching. As a result, it requires very minimum executions compared with other searching strategies. The effectiveness of the algorithm has been validated through four standard test cases and compared with previous studies. The proposed method out performs the previous methods.

Derivation of a new dose constraint applicable to radioactive discharges from Korean nuclear power plants through retrospective dose assessment

  • Kim, Soyun;Cheong, Jae Hak
    • Nuclear Engineering and Technology
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    • 제54권10호
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    • pp.3660-3671
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    • 2022
  • A new methodology to derive a dose constraint for radioactive effluent from a unit of nuclear power plant (NPP) through retrospective assessment was developed to reflect operational flexibility in line with international standards. The new dose constraint can retain the safety margin between the offsite dose and the past dose constraints. As case studies, the new approach was applied to 24 Korean NPPs to address the limitations of the existing seven dose constraints that do not fully comply with current international radiation protection standards. Therefore, an effective dose constraint for Korean NPPs was proposed as no less than 0.15 mSv/y, which is comparable to the international practices and previous studies (0.05-0.3 mSv/y). Although the lower bound of the equivalent dose constraint was calculated as 0.17 mSv/y, it is not proposed in this study since the compliance with the derived effective dose constraint can prevent accompanied equivalent doses to any organs from exceeding equivalent dose limits. The new framework and the case studies are expected to contribute toward and support the revision of existing dose constraints for radioactive effluent from NPPs, ensuring better compliance with the current international safety standards as well as reflect the operational flexibility in practice.

Karmarkar 알고리듬을 이용한 최적 발전시뮬레이션 (Optimal Production Cost Evaluation Using Karmarkar Algorithm)

  • 송길영;김용하;오광해
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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    • pp.113-116
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    • 1995
  • In this study, we formulate production costing problem with environmental and operational constraints into an optimization problem of LP form. In the process of formulation, auxiliary constraints on which reflect unit loading order are constructed to reduce the size of optimization problem by economic operation rules. As a solution of the optimization problem in LP form, we use Karmarkar's method which performs much faster than simplex method in solving large scale LP problem. The proposed production costing algorithm is applied to IEEE Reliability Test System, and performs production simulation under environmental and operational constraints. Test and computer results are given to show the accuracy and usefulness of the proposed algorithm in the field of power system planning.

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A Case Study of Human Resource Allocation for Effective Hotel Management

  • Murakami, Kayoko;Tasan, Seren Ozmehmet;Gen, Mitsuo;Oyabu, Takashi
    • Industrial Engineering and Management Systems
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    • 제10권1호
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    • pp.54-64
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    • 2011
  • The purpose of this study is to optimally allocate the human resources to tasks while minimizing the total daily human resource costs and smoothing the human resource usage. The human resource allocation problem (hRAP) under consideration contains two kinds of special constraints, i.e. operational precedence and skill constraints in addition to the ordinary constraints. To deal with the multiple objectives and the special constraints, first we designed this hRAP as a network problem and then proposed a Pareto multistage decisionbased genetic algorithm (P-mdGA). During the evolutionary process of P-mdGA, a Pareto evaluation procedure called generalized Pareto-based scale-independent fitness function approach is used to evaluate the solutions. Additionally, in order to improve the performance of P-mdGA, we use fuzzy logic controller for fine-tuning of genetic parameters. Finally, in order to demonstrate the applicability and to evaluate the performance of the proposed approach, P-mdGA is applied to solve a case study in a hotel, where the managers usually need helpful automatic support for effectively allocating hotel staff to hotel tasks.

로보트 운용조건을 포함한 가변구조 제어방식에 관한 연구 (A study on the variable structure control method including robot operational condition)

  • 이홍규;이범희;최계근
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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    • pp.72-75
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    • 1988
  • Due to the fact that the set point regulation scheme by the variable structure control method concerns only the initial and final locations of a manipulator, many constraints may exist in the application of path tracking with obstracle avoidance. The variable structure parameter should be selected in the trajectory planning step by satisfying the constraints of the travel time and the path deviations This paper presents the selection algorithm of the variable structure parameters with the constraints of the system dynamics and the travel time and the path deviation. This study makes unify the trajectory planning and tracking control using the variable structure control method.

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예산제약하에서 수리부속 최적조달요구량 산정 연구 (A Study of the Optimal Procurement to Determine the Quantities of Spare Parts Under the Budget Constraint)

  • 이상진;김승철;황지현
    • 경영과학
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    • 제27권2호
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    • pp.31-44
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    • 2010
  • It is very important to forecast demand and determine the optimal procurement quantities of spare parts. The Army has been forecasting demand not with actual usage of spare parts but with request quantities. However, the Army could not purchase all of forecasted demand quantities due to budget limit. Thus, the procurement quantities depend on the item managers' intuition and their meetings. The system currently used contains many problems. This study suggests a new determination procedure; 1) forecasting demand method based on actual usage, 2) determining procurement method through LP model with budge and other constraints. The newly determined quantities of spare parts is verified in the simulation model, that represents the real operational and maintenance situation to measure the operational availability. The result shows that the new forecasting method with actual usage improves the operational availability. Also, the procurement determination with LP improves the operational availability as well.