Mixed-Integer Dynamic Scheduling Optimization For Demand Side Management
30TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PTS A-C(2020)
摘要
With fluctuating electricity prices, demand side management (DSM) promises to reduce energy costs. DSM of processes and energy supply systems requires scheduling optimization to consider transient behavior and binary on/off-decisions resulting in challenging mixed-integer dynamic programs. In this work, we present an efficient scheduling optimization approach that captures scheduling-relevant dynamics in a linear scale-bridging model and relies on collocation for time discretization. The resulting mixed-integer linear program (MILP) can be solved with state-of-the-art solvers. We apply the approach to a case study on building DSM. A detailed simulation model represents an office building, which allows load shifting through dynamic concrete core activation and is heated by a heat pump with minimum part-load. The DSM scheduling optimization approach reduces energy cost significantly compared to a rule-based scheduler without DSM if electricity price volatility is high. At the same time, the optimization is sufficiently fast to perform online scheduling.
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关键词
Mixed-Integer Dynamic Optimization, Demand Side Management, Mixed-Integer Linear Programming
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