Application of Advanced Particle Swarm Optimization Techniques to Wind-Thermal Coordination

Singh, Sachin; stergaard, J. Ø; Yadagiri, J.

doi:10.1109/isap.2009.5352912

Cited by 12 publications

(3 citation statements)

References 12 publications

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“…The cost obtained by the proposed IDP algorithm is $78895.55, and it is less than that obtained by the branch and bound algorithm ($78907) [17] and the SA algorithm (average cost $78898.77) [7]. It also shows that the cost of the proposed IDP is very close to that of the PSO algorithm (best cost $78895.5) [25]. The FDP takes more time (26.2 s) to find the optimal schedule which is identical to the results of the proposed algorithm.…”

Section: Numerical Experimentsmentioning

confidence: 94%

Key issues of wind capacity integration in congested areas of the Taiwan power system

Chen

2014

IET Renewable Power Generation

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As wind power penetrations increase in isolated power systems, it is very important to understand how variations in wind plant outputs affect the operation of the multi-area isolated system on a day-today basis and what the associated costs are. Production cost models need to be further advanced to adequately simulate utility operations and unit commitment (UC) of generation in response to higher wind penetrations. In this study, the dynamic programming (DP) algorithm is extended to facilitate economic sharing of generation and reserve across areas and to coordinate wind and thermal generation scheduling in isolated power systems with large integration of wind capacity. Five heuristic strategies are incorporated in the DP algorithm to improve solution quality and performance. Four important issues of wind capacity integration in congested areas of the Taiwan power system are also investigated and discussed by using the developed UC software. Numerical experiments are included to understand wind generator capacity in production cost analysis and to illustrate the effect of transmission capacity limits on wind power penetration level in each area.

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Section: Numerical Experimentsmentioning

confidence: 94%

Key issues of wind capacity integration in congested areas of the Taiwan power system

Chen

2014

IET Renewable Power Generation

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“…The spinning reserve constraint violation, minimum up-down time constraint violation and load demand equality constraint violation are calculated for each chromosome using the Res.PM. If a chromosome violates the load demand equality constraint, than an attempt is made to repair the chromosome modifying a strategy used in [29]. In this strategy the chromosomes are repaired using PL based on either fuel cost coefficients or emission cost coefficients (with equal probability).…”

Section: Constraint Handling and Function Evaluationmentioning

confidence: 99%

Improved multi-objective evolutionary algorithm for day-ahead thermal generation scheduling

Trivedi

Pindoriya

Srinivasan

et al. 2011

2011 IEEE Congress of Evolutionary Computation (CEC)

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This paper presents a multi-objective evolutionary algorithm to solve the day-ahead thermal generation scheduling problem. The objective functions considered to model the scheduling problem are: 1) minimizing the system operation cost and 2) minimizing the emission cost. In the proposed algorithm, the chromosome is formulated as a binary unit commitment matrix (UCM) which stores the generator on/off states and a real power matrix (RPM) which stores the corresponding power dispatch. Problem specific binary genetic operators act on the binary UCM and real genetic operators act on the RPM to effectively explore the large binary and real search spaces separately. Heuristics are used in the initial population by seeding the random population with two Priority list (PL) based solutions for faster convergence. Intelligent repair operator based on PL is designed to repair the solutions for load demand equality constraint violation. The ranking, selection and elitism methods are borrowed from NSGA-II. The proposed algorithm is applied to a large scale 60 generating unit power system and the simulation results are presented and compared with our earlier algorithm [26]. The presented algorithm is found to outperform our earlier algorithm in terms of both convergence and spread in the final Pareto-optimal front.

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“…A day-ahead DED approach for the power system with wind energy generators (WEGs) to optimize cost of generation and reserves of all generating units is presented in Chao et al (2015). Singh et al (2009) proposed 4 versions of particle swarm optimization to solve the scheduling problem of wind-thermal power system. A simulated annealing method combined with an efficient constrained DED approach is presented in Chen (2007) to coordinate thermal and wind generation coordination in a power system with large scale penetration of wind power.…”

Section: Introductionmentioning

confidence: 99%

Optimal Wind-Thermal Coordination Scheduling Considering Reserve Requirement

Jung¹,

Salkuti²

2019

Int J Math, Eng, Manag Sci

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This paper proposes an optimal coordination scheduling methodology for a wind-thermal power system by considering the intermittent behavior of wind power and load demands. The optimum amount of spinning reserves (SRs) needed to handle the uncertain nature of hybrid power system with wind generators is determined by using the probability analysis. The proposed model demonstrates the error in wind power and load forecasts by using the probability distribution functions for over and under estimations of load and wind power. In this work, two objectives, i.e., total operating cost and risk level are considered, which handles both economical and reliability issues, simultaneously. This problem is solved by using the meta-heuristic based Cuckoo search algorithm. The reactive power capability limits of synchronous generators and variable speed doubly fed induction generators are considered in this paper. Simulations have been carried out on IEEE 300 bus system.

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Application of Advanced Particle Swarm Optimization Techniques to Wind-Thermal Coordination

Cited by 12 publications

References 12 publications

Key issues of wind capacity integration in congested areas of the Taiwan power system

Key issues of wind capacity integration in congested areas of the Taiwan power system

Improved multi-objective evolutionary algorithm for day-ahead thermal generation scheduling

Optimal Wind-Thermal Coordination Scheduling Considering Reserve Requirement

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