An MILP model for cost-optimal planning of an on-grid hybrid power system for an eco-industrial park

The application of on-grid hybrid power system (HPS) has been effective for harnessing renewable energy resources and ensuring environmental sustainability. A number of algebraic and mathematical modeling approaches have been introduced for the optimisation of on-grid HPS. While algebraic power pinc...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Theo, W.L., Lim, J.S., Wan Alwi, S.R., Mohammad Rozali, N.E., Ho, W.S., Abdul-Manan, Z.
التنسيق: مقال
منشور في: Elsevier Ltd 2016
الوصول للمادة أونلاين:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984839037&doi=10.1016%2fj.energy.2016.05.043&partnerID=40&md5=1ac1ef6e24c844f03b7c1bf103044dcc
http://eprints.utp.edu.my/25748/
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الوصف
الملخص:The application of on-grid hybrid power system (HPS) has been effective for harnessing renewable energy resources and ensuring environmental sustainability. A number of algebraic and mathematical modeling approaches have been introduced for the optimisation of on-grid HPS. While algebraic power pinch analysis (PoPA) tools have been developed to enable the selection of cost-effective energy storage technology, the available mathematical modeling approaches have yet to consider the economics and storage system selection in the design of an optimal on-grid HPS. This work presents a mixed-integer linear programming (MILP) for the optimal design of an on-grid HPS with the minimum net present value (NPV) of the overall electricity production cost and the selection of the optimum energy storage technology. Two case studies are presented in this work. In the former, the differences between the developed MILP model and previous methods are highlighted, with sensitivity analysis to investigate the impact of electricity tariff on the on-grid HPS. In the second case study, the developed MILP model was applied to an Eco-Industrial Park (EIP) case study with energy storage technology selection. Lead-acid battery system was found to be the optimal choice due to its low investment requirement. © 2016 Elsevier Ltd