This paper proposes a computational technique for the classification of electricity consumption profiles. The methodology is comprised of two steps. In the first one, a C-means-based fuzzy clustering is performed in order to find consumers with similar consumption profiles. Afterwards, a fuzzy classification is performed using a fuzzy membership matrix and the Euclidean distance to the cluster centers. Then, the distance measures are normalized and ordered, yielding a unitary index score, where the potential fraudsters or users with irregular patterns of consumption have the highest scores. The approach was tested and validated on a real database, showing good performance in tasks of fraud and measurement defect detection.

A simple and efficient algorithm based on evolutionary strategies is proposed for the solution of the economic dispatch (ED) problem with noncontinuous and nonsmooth/nonconvex cost functions and with generator constraints being considered. The proposed method solves both, the ED problem with nonconvex/nonsmooth cost functions due to valve-point loading and the ED problem that takes into account nonlinear generator characteristics such as ramp-rate limits and prohibited operating zones in the power system operation. The effectiveness of the algorithm is demonstrated using six different test systems and the performance is compared with other relevant methods reported in the literature. In all cases, the proposed algorithm either matches or outperforms the behaviour reported for the existing algorithms. This level of performance is obtained despite the simplicity of the approach.

In isolated microgrids, storage systems play a crucial role in maintaining the instantaneous power balance between generation and consumption. Lead-acid batteries are now widely used as storage elements in such systems, and their useful life depends heavily on the operation strategy. This is a serious problem that up to now has limited the sustainability of this type of systems. This article proposes a new philosophy of battery storage energy management for isolated systems based on photovoltaic energy. A dual battery bank is proposed: the first one is responsible for storing energy when renewable sources are available to meet the load demand. The second bank has smaller size and is calculated to meet the needs of daily snapshot balancing and network voltage regulation. The proposed configuration significantly increases the life of the largest bank, reducing the operating and maintenance costs of isolated systems by more than 19 %. Results are reported using data from an isolated microgrid based on photovoltaic solar energy located in Humberto de Campos, Maranhao, Brazil.

This paper presents a new method to allocate active and reactive losses simultaneously to generators and loads. The allocation is calculated for each transmission branch, identifying and quantifying the buses' responsibilities in losses. This is a two-step process. In the first step, generators are modeled as current injections and loads as constant admittances in order to determine generator participations in losses. In the second step, loads are modeled as current sources and generators as constant admittances in order to determine load participations in losses. The Aumann-Shapley and circuit theories are used to calculate the participation of each real and imaginary current component, considering them as independent players in the “complex losses allocation” game. The properties of the Aumann-Shapley method ensure equitable allocation and recovery of the total active and reactive losses. Counter-flow, cross-subsidy, and negative allocation issues are discussed. Numerical results are presented and discussed to demonstrate the applicability of the proposed method.