Predictive management of cogeneration-based energy supply networks using two-stage multi-objective optimization

Tetsuya Wakui, Kento Sawada, Ryohei Yokoyama and Hirohisa Aki

Energy, 2018, vol. 162, issue C, 1269-1286

Abstract: A predictive management system for cogeneration unit-based energy supply networks using two-stage multi-objective optimization was developed to tackle a trade-off between energy savings and operating cost reduction. The developed system integrated support vector regression-based energy demand prediction, MILP (mixed-integer linear programming)-based schedule planning, and rule-based operation control. The contribution is to develop two-stage MILP-based multi-objective schedule planning, which is extension of an ε-constraint method, and operation control rule of multiple cogeneration units. In the first-stage schedule planning, primary energy consumption in the prediction horizon is minimized, and a reduction rate of primary energy consumption is calculated. In the second-stage schedule planning, an operating cost is minimized additionally subject to satisfaction of partial achievement of the reduction rate of primary energy consumption calculated in the first stage. An energy-saving achievement rate is regarded as a decision-making parameter to control a trade-off between energy savings and cost reduction, of which definition is quantitatively apprehensible for decision makers. Annual operating simulation of an energy supply network using four fuel-cell-based cogeneration units revealed that the developed predictive management system has high controllability to the trade-off between the energy-saving rates (18.9%–21.6%) and the operating cost reduction rate (19.0%–15.6%), caused by a time-of-use power tariff structure.

Keywords: Energy management; Multi-objective optimization; Microgrid; Cogeneration; Model predictive control; Mixed-integer linear programming (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:162:y:2018:i:c:p:1269-1286

DOI: 10.1016/j.energy.2018.08.072

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