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The optimal sitting and operation of Battery Energy Storage Systems (BESS) plays a key role in energy transition and sustainability. This paper presents an optimization framework based on a Multi-period Optimal Power Flow (MOPF) for the optimal sitting and operation of BESS alongside PV in active distribution grids. The model was implemented in AMPL (A Mathematical Programming Language) and solved using the Knitro solver to minimize power losses over one week, divided into hourly intervals. To demonstrate the applicability of the proposed model, various analyses were conducted on a benchmark 33-bus distribution network considering 1, 2 and 3 BESS. Along with the reduction in power losses of up to 17.95%, 26% and 29%, respectively. In all cases, there was an improvement in the voltage profile and a more uniform generation curve at the substation. An additional study showed that operating over a one-week horizon results in an energy gain of 1.08 MWh per day compared to single daily operations. The findings suggest that the proposed model for optimal sitting and operation of BESS in the presence of Renewable Energy Sources (RES) applies to real-world scenarios. [ABSTRACT FROM AUTHOR]

The data presented in this paper are related to the paper entitled "Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection", available in the Energies journal. Here, data are included to show the results of an Under-Frequency Load Shedding (UFLS) scheme that considers the injection of virtual inertia by a VSC-HVDC link. The data obtained in six cases which were considered and analyzed are shown. In this paper, each case represents a different frequency response configuration in the event of generation loss, taking into account the presence or absence of a VSC-HVDC link, traditional and optimized UFLS schemes, as well as the injection of virtual inertia by the VSC-HVDC link. Data for each example contain the state of the relay, threshold, position in every delay, load shed, and relay configuration parameters. Data were obtained through Digsilent Power Factory and Python simulations. The purpose of this dataset is so that other researchers can reproduce the results reported in our paper. Dataset: 10.5281/zenodo.11371324 Dataset License: Creative Commons Attribution 4.0 International (CC BY 4.0) [ABSTRACT FROM AUTHOR]

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This paper addresses the protection coordination problem of microgrids combining unsupervised learning techniques, metaheuristic optimization and non-standard characteristics of directional over-current relays (DOCRs). Microgrids may operate under different topologies or operative scenarios. In this case, clustering techniques such as K-means, balanced iterative reducing and clustering using hierarchies (BIRCH), Gaussian mixture, and hierarchical clustering were implemented to classify the operational scenarios of the microgrid. Such scenarios were previously defined according to the type of generation in operation and the topology of the network. Then, four metaheuristic techniques, namely, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Invasive Weed Optimization (IWO), and Artificial Bee Colony (ABC) were used to solve the coordination problem of every cluster of operative scenarios. Furthermore, non-standard characteristics of DOCRs were also used. The number of clusters was limited to the maximum number of setting setting groups within commercial DOCRs. In the optimization model, each relay is evaluated based on three optimization variables, namely: time multiplier setting (TMS), the upper limit of the plug setting multiplier (PSM), and the standard characteristic curve (SCC). The effectiveness of the proposed approach is demonstrated through various tests conducted on a benchmark test microgrid. [ABSTRACT FROM AUTHOR]

This paper proposes a comprehensive 26-bus microgrid (MG) test system designed to validate or propose new protection coordination schemes. The proposed MG test system comprises various components facilitating the simulation of diverse configurations and operating modes. It also presents a predefined overcurrent protection scheme which is validated with and without Distributed Generation (DG), offering detailed specifications and settings for the test network. The MG test system outlined in this paper incorporates multiple DG sources in different buses, multiple voltage levels, and two operating modes (with and without DG). Additionally, the overcurrent protection scheme considers multiple functions and devices simultaneously. The detailed features of the proposed protection coordination scheme enable the simulation of various fault types and contingencies. The paper also presents specific details of the MG test system under different single-phase and three-phase faults, reporting bus voltages in nodes, transformer and line loadability, short-circuit currents, and operating times. The MG test system is meant to serve as a valuable tool for researchers to conduct comparative studies and develop new strategies regarding the operation and planning of MGs. [ABSTRACT FROM AUTHOR]

Distribution system reconfiguration (DSR) is an essential activity in the operation of distribution utilities, usually carried out to lower active power losses and improve reliability metrics. The insertion of distributed generation (DG) units in electric power distribution systems (EPDS) causes the rearrangement of power flows through the conductors and changes the real power losses and voltage profile; therefore, up to a certain point, the insertion of certain quantities of DG may potentially delay or change the reconfiguration strategy of EPDS. This article presents an analysis of the impact of DG, for different locations of the units and different levels of active power supplied by them, on real power losses and on the effectiveness of DSR. The article presents tests with different distribution systems with varying sizes and topologies, showing that the allocation of DG units in buses far from the substation provided the best cost–benefit results. The DSR impact changes depending on the installment location and the generation level of the DG units, corroborating that DSR must be considered and performed using certain criteria, to maximize its efficiency. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have gained considerable attention in the last decade due to a paradigm shift in the transport sector driven by a higher awareness of environmental issues. While the importance of EVs cannot be overstated in the context of the global climate crisis, it does raise the question of whether certain countries or states are ready for their implementation. It is, therefore, necessary to analyze the impact of EVs in the power grids of these countries and states, considering factors such as line congestion and the eventual degradation of voltage profiles, to determine their hosting capacity and assess eventual expansion options. This paper proposes a representative prototype of Curaçao's electrical system, which is used for assessing the impacts of EVs, allowing us to determine its hosting capacity. Curaçao is an island in the southern Caribbean Sea that uses fuel generators, wind energy, and solar energy to generate electricity. The idea behind this paper is to analyze the effects caused by an increase in EVs on Curaçao's power grid and propose preventive measures to deal with such problems. Eight EV charging stations were considered, one DC super fast-charging station, three normal DC fast-charging stations, and four AC fast-charging stations. In 2022, there were an estimated 82,360 vehicles on the island. Using this information, this paper analyzes how many vehicles can be simultaneously connected to the grid before it no longer operates under acceptable values. The results showed that 3.5% of the total vehicles can be hosted by the grid. Nonetheless, this can be increased up to 4.5% with the reinforcement of a transmission line. [ABSTRACT FROM AUTHOR]