No abstract

The rising penetration of renewable energy sources (RESs) has led to increased research interest in the optimal scheduling and management of multi-microgrid (MMG) systems. This is due to the potential economic benefits which can be derived from the sharing of resources between the MGs which constitute the MMG. Advanced optimization procedures such as robust optimization (RO) frameworks have been proposed in the literature to handle any uncertainties caused by the stochastic nature of the RES generation, the load demand, and the electricity prices. However, the existing works in the literature do not consider the nonlinear network constraints of individual MGs which might significantly impact the power balance and the power sharing between MGs in MMG systems. This paper proposes a cooperative trading scheme including a two-stage network-constrained robust energy management system to optimize the resource utilization within each MG and the sharing of resources between the constituent MGs of a MMG system. The results clearly highlight the performance of the proposed approach and the impact of including the AC network constraints on the optimal dispatch of the MMG system under varying uncertainties.

This paper proposes a piecewise-affine decision rule based stochastic optimal power flow approach for reserve dispatch of generators under uncertain demand and renewable energy source generation. The ambiguity set comprises a predefined set of scenarios to capture the plausible uncertain realizations. The objective is to minimize the expected generation cost under those scenarios. A piecewise-affine decision rule is established with auxiliary control parameters to compute the optimal participation of generators depending on the amounts of reserve requirements. Such a reserve dispatch rule would be less conservative compared to the traditional affine decision rule. The results illustrate that the proposed piecewise-affine generation redispatch rule improves the optimality of operation via efficient resource utilization for reserve support.