An interactive fuzzy satisfying method based on evolutionary programming technique for multiobjective short-term hydrothermal scheduling

Basu, Madhumita

doi:10.1016/j.epsr.2003.10.003

Cited by 212 publications

(125 citation statements)

References 12 publications

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“…If we solve the same problem by the proposed method in this paper, the fuel cost is 40766.83($) and emission value is 18278.76 (lb). It can be seen from results that the proposed method can find better solution for fuel cost and emission in comparison with the results of [45] to [48]. Also, table X shows power generation of each thermal and hydro unit in each hour by solving the problem using the proposed method.…”

Section: Va Comparative Analysismentioning

confidence: 93%

“…All these works have used a heuristic approach to solve the problem. While the frameworks proposed in [45] to [48] are not completely same as the proposed scheme in this paper, i.e. multiobjective hydrothermal self-scheduling problem with objective functions of profit maximization and emission minimization, therefore we compare our proposed method with these references [45] to [48].…”

Section: Va Comparative Analysismentioning

confidence: 99%

“…It should be mentioned that the objective function of works [45] to [48] is the cost function. Also, in these works, emission function has been considered as another objective function of the optimization problem.…”

Section: Va Comparative Analysismentioning

confidence: 99%

“…We have used works [45] to [48] to compare the results of the proposed framework with them. It should be mentioned that the objective function of works [45] to [48] is the cost function.…”

Section: Va Comparative Analysismentioning

confidence: 99%

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Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

Aghaei

Ahmadi

Rabiee

et al. 2015

Applied Soft Computing

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In this paper, a stochastic multiobjective framework is proposed for a day-ahead short-term Hydro Thermal Self-Scheduling (HTSS) problem for joint energy and reserve markets. An efficient linear formulations are introduced in this paper to deal with the nonlinearity of original problem due to the dynamic ramp rate limits, prohibited operating zones, operating services of thermal plants, multi-head power discharge characteristics of hydro generating units and spillage of reservoirs. Besides, system uncertainties including the generating units' contingencies and price uncertainty are explicitly considered in the stochastic market clearing scheme. For the stochastic modeling of probable multiobjective optimization scenarios, a lattice Monte Carlo simulation has been adopted to have a better coverage of the system uncertainty spectrum. Consequently, the resulting multiobjective optimization scenarios should concurrently optimize competing objective functions including GENeration COmpany's (GENCO's) profit maximization and thermal units' emission minimization. Accordingly, the ε-constraint method is used to solve the multiobjective optimization problem and generate the Pareto set. Then, a fuzzy satisfying method is employed to choose the most preferred solution among all Pareto optimal solutions. The performance of the presented method is verified in different case studies. The results obtained from ε-constraint method is compared with those reported by weighted sum method, evolutionary programming-based interactive Fuzzy satisfying method, differential evolution, quantumbehaved particle swarm optimization and hybrid multi-objective cultural algorithm, verifying the superiority of the proposed approach. Abstract-In this paper, a stochastic multiobjective framework is proposed for a day-ahead short-term Hydro Thermal Self-Scheduling (HTSS) problem for joint energy and reserve markets. An efficient linear formulations are introduced in this paper to deal with the nonlinearity of original problem due to the dynamic ramp rate limits, prohibited operating zones, operating services of thermal plants, multi-head power discharge characteristics of hydro generating units and spillage of reservoirs. Besides, system uncertainties including the generating units' contingencies and price uncertainty are explicitly considered in the stochastic market clearing scheme. For the stochastic modeling of probable multiobjective optimization scenarios, a lattice Monte Carlo simulation has been adopted to have a better coverage of the system uncertainty spectrum. Consequently, the resulting multiobjective optimization scenarios should concurrently optimize competing objective functions including GENeration COmpany's (GENCO's) profit maximization and thermal units' emission minimization. Accordingly, the ε-constraint method is used to solve the multiobjective optimization problem and generate the Pareto set. Then, a fuzzy satisfying method is employed to choose the most preferred solution among all Pareto optimal solutions. The perfo...

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Section: Va Comparative Analysismentioning

confidence: 93%

Section: Va Comparative Analysismentioning

confidence: 99%

Section: Va Comparative Analysismentioning

confidence: 99%

“…We have used works [45] to [48] to compare the results of the proposed framework with them. It should be mentioned that the objective function of works [45] to [48] is the cost function.…”

Section: Va Comparative Analysismentioning

confidence: 99%

See 2 more Smart Citations

Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

Aghaei

Ahmadi

Rabiee

et al. 2015

Applied Soft Computing

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“…Recently, aside from the above methods, optimal hydrothermal scheduling problems have been solved by meta-heuristic approaches such as genetic algorithm [4][5][6], cultural algorithm [7] and particle swarm optimization [8] etc. Various heuristic methods such as heuristic search technique [9], fuzzy satisfying evolutionary programming procedures [10] and fuzzy decision-making stochastic technique [11] have been applied to solve multi-objective short-term hydrothermal scheduling problems. Because these meta-heuristic optimization methods are able to provide higher quality solutions, they have received more interest.…”

Section: Introductionmentioning

confidence: 99%

A Novel Solution Based on Differential Evolution for Short-Term Combined Economic Emission Hydrothermal Scheduling

Sun¹,

Lu²

2009

ENG

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This paper presents a novel approach based on differential evolution for short-term combined economic emission hydrothermal scheduling, which is formulated as a bi-objective problem: 1) minimizing fuel cost and 2) minimizing emission cost. A penalty factor approach is employed to convert the bi-objective problem into a single objective one. In the proposed approach, heuristic rules are proposed to handle water dynamic balance constraints and heuristic strategies based on priority list are employed to repair active power balance constraints violations. A feasibility-based selection technique is also devised to handle the reservoir storage volumes constraints. The feasibility and effectiveness of the proposed approach are demonstrated and the test results are compared with those of other methods reported in the literature. Numerical experiments show that the proposed method can obtain better-quality solutions with higher precision than any other optimization methods. Hence, the proposed method can well be extended for solving the large-scale hydrothermal scheduling.

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Power system observability enhancement for parallel restoration of subsystems considering renewable energy resources

Khodabakhshian

Esmaili

Hooshmand

et al. 2019

Int Trans Electr Energ Syst

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Summary The observability of power systems during the parallel restoration of subsystems is one of the most important issues for system operators to accomplish the restoration task as quick as possible. Thus, this article proposes a coordinated optimal plan to solve the observability and sectionalizing problems by determining the locations of phasor measurement units (PMUs) and subsystems. Also, the impact of renewable energy resources on power system sectionalizing and the reliability value of power generation are taken into account in the proposed model. The objective functions that are considered in the optimization problem are the cost of wide‐area measurement system (WAMS), the worst observability index among all subsystems and the lowest value of quality among all subsystems based on the reliability of subsystems. Since there are three contradictory objective functions, a multi‐objective problem (MOP) is proposed as a mixed‐integer nonlinear problem (MINLP). The Pareto curve of the proposed MOP is extracted by using a particle swarm optimization (PSO) algorithm. Two standard power grids are considered to validate the suggested technique. The outcomes of simulations confirm that the observability value of all sections is enhanced during the parallel restoration of the system. Also, the results show that the quality of subsystems in the presence of renewable energy resources is enhanced.

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An interactive fuzzy satisfying method based on evolutionary programming technique for multiobjective short-term hydrothermal scheduling

Cited by 212 publications

References 12 publications

Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

A Novel Solution Based on Differential Evolution for Short-Term Combined Economic Emission Hydrothermal Scheduling

Power system observability enhancement for parallel restoration of subsystems considering renewable energy resources

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