Geographical distribution of agricultural residues and optimum sites of biomass based power plant in Bathinda, Punjab

Singh, Jagtar; Panesar, B.S.; Sharma, Sapna

doi:10.1016/j.biombioe.2011.09.004

Cited by 25 publications

(9 citation statements)

References 9 publications

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“…[3,[17][18][19][20]), representing around 6% of all bioenergy MCDM studies [21]. In general, such proposals make use of GIS and consider location-allocation analysis where road network data is taken into account (avoiding over simplified Euclidean distances between points).…”

Section: Introductionmentioning

confidence: 99%

A fuzzy approach to a multiple criteria and Geographical Information System for decision support on suitable locations for biogas plants

et al. 2015

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h i g h l i g h t sWe propose the GAF decision support methodology for optimal site selection. The GAF methodology builds decision support from multi-dimensional imprecise data. We present a real-case application for biogas facilities at Ringkøbing-Skjern, Denmark. a b s t r a c tThe purpose of this paper is to model the multi-criteria decision problem of identifying the most suitable facility locations for biogas plants under an integrated decision support methodology. Here the Geographical Information System (GIS) is used for measuring the attributes of the alternatives according to a given set of criteria. Measurements are taken in interval form, expressing the natural imprecision of common data, and the Fuzzy Weighted Overlap Dominance (FWOD) procedure is applied for aggregating and exploiting this kind of data, obtaining suitability degrees for every alternative. The estimation of criteria weights, which is necessary for applying the FWOD procedure, is done by means of the Analytical Hierarchy Process (AHP), used jointly with the LLSM-AHP for the estimation of upper and lower bounds for the weights. Then, a combined AHP-FWOD methodology allows identifying the more suitable sites for building biogas plants. We show that the FWOD relevance-ranking procedure can also be successfully applied over the outcomes of different decision makers, in case a unique social solution is required to exist.The proposed methodology can be used under an integrated decision support frame for identifying the most suitable locations for biogas facilities, taking into account the most relevant criteria for the social, economic and political dimensions.

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Section: Introductionmentioning

confidence: 99%

A fuzzy approach to a multiple criteria and Geographical Information System for decision support on suitable locations for biogas plants

et al. 2015

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“…The NLP is solved by an exact reformulation to a MILP. AlsoSingh et al (2011) apply NLP modelling to obtain the optimum location of biomass based power plants and their collection centres by minimising the collection cost in the field, transportation cost, conversion cost and collection centre radius. The NLP is solved following the Nelder Mead method[81].Čuček et al (2012) combine a NLP model and Pareto optimisation to simultaneously maximise the economic performance and minimise environmental and social footprints.…”

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confidence: 99%

Methods to optimise the design and management of biomass-for-bioenergy supply chains: A review

Meyer

Cattrysse

Rasinmäki³

et al. 2014

Renewable and Sustainable Energy Reviews

271

150

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Biomass supply chain optimisation is essential to overcome barriers and uncertainties that may inhibit the development of a sustainable and competitive bioenergy market. The number of research papers presenting optimisation models in the field of bioenergy systems rises exponentially. This paper gives an overview of the optimisation methods and models focussing on decisions regarding the design and management of the upstream segment of the biomass-for-bioenergy supply chain. After a general description of the supply chain and the decisions coming along with the design and management, all selected publications are classified and discussed according to (1) the mathematical optimisation methodology used, (2) the decision level and decision variables addressed and (3) the objective to be optimised. This classification allows users to identify existing optimisation methods or models that satisfy specific requirements. Moreover, the factual description of the presented optimisation methods and models points to opportunities for development of an integrated, holistic approach to optimise decisions in the field of biomass supply chain design and management. Such approach must be based on the consideration of the interrelationships and interdependence between all operations in the entire biomass-for-bioenergy supply chain.

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“…In the first stage of the methodology, GIS is used to identify the candidate sites for the facilities, and mathematical modeling is utilized in the second stage to select the optimal location based on a total transportation cost model. Singh et al (2011) presented a GIS and NLP based methodology to evaluate the feasibility of constructing biomass based power plants and optimize their location. GIS is used to assess the geographical distribution of crop residue and non-linear optimization techniques are employed to locate appropriate sites and sizes of plants.…”

Section: Non Linear Programming Approachmentioning

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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Geographical distribution of agricultural residues and optimum sites of biomass based power plant in Bathinda, Punjab

Cited by 25 publications

References 9 publications

A fuzzy approach to a multiple criteria and Geographical Information System for decision support on suitable locations for biogas plants

A fuzzy approach to a multiple criteria and Geographical Information System for decision support on suitable locations for biogas plants

Methods to optimise the design and management of biomass-for-bioenergy supply chains: A review

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

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