Minimax Model Predictive Operation Control of Microgrids

Abstract

Due to the steady growth of decentralised distributed generation, the operational management of small, local electricity networks (microgrids) is becoming an increasing challenge to meet: How to provide an operational control for microgrids with a high share of renewable energy sources (RES) that is robust to perturbations? In this paper we address an optimal control problem (OCP) that maintains all of the stated properties in the presence of an uncertain load and RES infeed in islanded operation. Assuming that the uncertainty is within a bounded region along a given load and RES trajectory prediction, the problem is posed as a worst-case hybrid OCP, where the RES output can be curtailed. We propose a minimax (MM) model predictive control (MPC) scheme that adjusts according to the present uncertainty and can be formulated as a mixed-integer linear program (MILP) and solved numerically online.

Scenario-based model predictive operation control of islanded microgrids

“…A scenario-based approach for grid-connected MGs can be found in [8]. For islanded MGs, in [9] a scheme that uses a robust forecast interval for load, and RES and allows limiting RES infeed was proposed. To decrease conservativeness, [10] extended the approach by considering the dependence of the controls on the predicted states.…”

“…Further, they do not allow to capture the fact that RES could be limited. In contrast, [9], [10] propose schemes for islanded MGs that use the forecast intervals of load and RES and allow a limitation of RES infeed. Even though in [10] the run time costs could be decreased, the approach still leads to conservative results as the forecast probability distribution is not considered.…”

“…Combining ideas from time-series based forecasting [11], scenario reduction [12], stochastic optimization [13], and the MG model from [9], our contribution is a scenariobased stochastic MPC for islanded MGs. Taking into account the stochasticity of RES and load forecasts, we provide a solution that reduces the conservativeness of [10].…”

Min-max control of fuel-cell-car-based smart energy systems

“…In order to deal with the uncertainty in the energy management systems, robust control techniques are used in [9] and [10]. The authors in [9] use stochastic optimization in the energy management system, while in [10] a minimax formulation is used.…”

“…The authors in [9] use stochastic optimization in the energy management system, while in [10] a minimax formulation is used. In [11], a method is developed in order to model the uncertainty in power systems as a polytope, while the appropriate control strategy in order to deal with the modeled uncertainty is not discussed.…”