We present a rolling decision-making process for electrical power systems, in which unit commitment, dispatch and reserve policies are co-optimized in order to minimize expected short-run operating costs in the presence of uncertainty arising from demand and renewable infeeds. The uncertainty is assumed to be bounded, with estimated first and second moment statistics available. The rolling “look-ahead” process employs a planning horizon of several hours, with re-optimization taking place each time the first step has been implemented. We present an expected-cost formulation incorporating multi-stage recourse on continuous decision variables—plans for adjusting the dispatch in the light of future information to be discovered at each stage of the optimization horizon. The generic formulation allows the flexibility of devices such as energy storage units to be exploited in the reserve mechanism. We demonstrate using closed-loop numerical tests that significant reductions in the cost of accommodating uncertainty are attainable relative to a time-decoupled reserve mechanism. In contrast to previous results, we show that a time-coupled cost function is not required for this benefit to be observed. In addition, we show that relaxing binary unit commitment decisions after the first step of the horizon brings significant computational speed-ups, and in some cases also reduce closed-loop system operation costs.
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