Future energy systems are expected to include distributed energy systems (DES) and microgrids (MG) at the distribution level. These energy efficient environments enable participating consumers to locally generate and ...
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Future energy systems are expected to include distributed energy systems (DES) and microgrids (MG) at the distribution level. These energy efficient environments enable participating consumers to locally generate and share both electrical and thermal energy. Apart from the potential for a more cost-efficient energy system design, improved system availability is also increasingly put forward as a major advantage of MGs. This paper proposes a mixed-integer linear programming (MILP) approach for the design of a neighbourhood-based energy system, considering the trade-off between total annualised cost and electrical system unavailability. System design is optimised to meet the yearly neighbourhood energy demands by selecting technologies and interactions from a pool of dispatchable and renewable polygeneration and storage alternatives. The availability implementation employs a Markov chain approach combined with logic-gate integer programming. The Pareto trade-off sets of on-and off-grid MG modes are obtained using a weighted-sum approach. The developed model is subsequently applied to an Australian case-study. The sought after trade-off "knee" points for each Pareto curve are hereby identified. Additionally, through comparing on-and off-grid design trade-offs, the need for component redundancy for systems with islanding capabilities is analysed. (C) 2017 Elsevier Ltd. All rights reserved.
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