Comparison of metaheuristic techniques to determine optimal placement of biomass power plants

López, P. Reche; Ruiz-Reyes, N.; García-Galán, S.

doi:10.1016/j.enconman.2009.04.008

Cited by 41 publications

(11 citation statements)

References 17 publications

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“…Whereas the ''running model'' is a MILP model, they proposed two ''planning models'', both of which are MINLP problems. Reche-López et al (2009) applied and compared several metaheuristic techniques to optimize the location and biomass supply area of biomass based power plants. For this purpose two trajectory (Simulated Annealing and Tabu Search) and two population-based (GA and PSO) methods are applied.…”

Section: Studies With Single Objectivementioning

confidence: 99%

Biomass to Energy Supply Chain Network Design: An Overview of Models, Solution Approaches and Applications

Balaman

Selim

2015

Handbook of Bioenergy

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Energy production from biomass is an alternative and additive way to fossil fuel based energy production to reduce the dependency on limited fossil fuel sources and mitigate the harmful environmental impacts of these systems. One of the major challenges in establishing efficient renewable energy systems is the complex supply chain structure in an uncertain decision environment, various decisions to be made and different conflicting criteria/objectives. This study describes the key issues in decision making for biomass to energy supply chains such as decision levels, uncertainty and sustainability concepts. It also provides a comprehensive review and systematic classification of the current literature on decision making approaches for design, management and operation of biomass to energy supply chains. This study allows readers to identify the decision making methods that satisfy the problem specific requirements and offer a clear vision of the advances in the field.

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Section: Studies With Single Objectivementioning

confidence: 99%

Biomass to Energy Supply Chain Network Design: An Overview of Models, Solution Approaches and Applications

Balaman

Selim

2015

Handbook of Bioenergy

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“…Their model specifies the most economic size of the plant. Reche- López et al (2009) presented a paper to optimize the location and area of the supply chain using four meta-heuristic methods. Accordingly they proposed two Simulated Annealing and Tabu Search (trajectory) and two GA and PSO (population-based) methods.…”

Section: Other Methodsmentioning

confidence: 99%

Optimization methods applied to renewable and sustainable energy: A review

Asadi¹,

Sadjadi²

2017

10.5267/j.uscm

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“…In order to minimize the power losses and maximizing the profitability, in [11] a new method was proposed which investigated the optimal size and location of biomass fuelled gas turbines in distribution systems. Application and comparison of several metaheuristic techniques for optimizing the placement and supplying the area of biomass-fueled power plants was presented in [12]. In all the above papers, the placement of CHPH FCPPs has not been investigated.…”

Section: Literature Reviewmentioning

confidence: 99%

Placement of Combined Heat, Power and Hydrogen Production Fuel Cell Power Plants in a Distribution Network

Farjah¹,

Bornapour

Niknam

2012

Energies

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This paper presents a new Fuzzy Adaptive Modified Particle Swarm Optimization algorithm (FAMPSO) for the placement of Fuel Cell Power Plants (FCPPs) in distribution systems. FCPPs, as Distributed Generation (DG) units, can be considered as Combined sources of Heat, Power, and Hydrogen (CHPH). CHPH operation of FCPPs can improve overall system efficiency, as well as produce hydrogen which can be stored for the future use of FCPPs or can be sold for profit. The objective functions investigated are minimizing the operating costs of electrical energy generation of distribution substations and FCPPs, minimizing the voltage deviation and minimizing the total emission. In this regard, this paper just considers the placement of CHPH FCPPs while investment cost of devices is not considered. Considering the fact that the objectives are different, non-commensurable and nonlinear, it is difficult to solve the problem using conventional approaches that may optimize a single objective. Moreover, the placement of FCPPs in distribution systems is a mixed integer problem. Therefore, this paper uses the FAMPSO algorithm to overcome these problems. For solving the proposed multi-objective problem, this paper utilizes the Pareto Optimality idea to obtain a set of solution in the multi-objective problem instead of only one. Also, a fuzzy system is used to tune parameters of FAMPSO algorithm such as inertia weight. The efficacy of the proposed approach is validated on a 69-bus distribution system. OPEN ACCESS

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Comparison of metaheuristic techniques to determine optimal placement of biomass power plants

Cited by 41 publications

References 17 publications

Biomass to Energy Supply Chain Network Design: An Overview of Models, Solution Approaches and Applications

Biomass to Energy Supply Chain Network Design: An Overview of Models, Solution Approaches and Applications

Optimization methods applied to renewable and sustainable energy: A review

Placement of Combined Heat, Power and Hydrogen Production Fuel Cell Power Plants in a Distribution Network

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