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This paper presents a methodology for jointly optimizing the sizing and operation of AC microgrids. The methodology is applied to the CAMPUSGRID microgrid, which is currently being developed at the State University of Campinas (UNICAMP) in Brazil. The distributed energy resources (DERs) considered in the study include a battery energy storage system (BESS), a dispatchable gas generator, and photovoltaic (PV) generation. The proposed energy management system (EMS) minimizes the costs associated with day-ahead operation of the DERs in an unbalanced three-phase AC microgrid. To develop the EMS as a mixed-integer linear programming (MILP) model, the MATLAB Link module of HOMER Pro and the AMPL API are used. Heuristic rules are also developed for contingency and post-contingency operations in case of unintentional disconnection from the main grid. The sizing simulations combine tariff regimes, contingencies, and dispatch strategies. The results demonstrate the influence of the tariff on the net present cost (NPC) and the importance of resilience in sizing DERs. Additionally, the proposed model is capable of assessing the impact of DERs on the electrical grid. Finally, the joint strategy proposed in this paper leads to a reduction in microgrid investment cost, improvement in voltage magnitude profile, and reduction in active power losses when compared to the default dispatch strategies of HOMER Pro. [ABSTRACT FROM AUTHOR]

This paper proposes an Internet-of-Things (IoT) based energy management system (EMS) for the optimal operation of unbalanced three-phase AC microgrids. The system utilizes a software architecture based on microservices, which includes a stochastic economic dispatch optimizer (EDO), a database, a web-based graphical user interface (GUI), and an application programming interface (API). The EDO uses a mixed-integer linear programming (MILP) model to ensure the day-ahead dispatch of the distributed energy resources (DERs) in the microgrid while adhering to grid constraints such as voltage, current, and power limits. Additionally, the optimization module takes into account security constraints for unplanned islanded operation, as well as stochastic scenarios of local demand and renewable generation. To assess the performance of the proposed IoT-based EMS, tests are conducted using a real-time simulator in a software-in-the-loop (SIL) experimental setup. Actual data from a microgrid located at the State University of Campinas (UNICAMP) in Brazil is utilized for the tests. The microgrid consisted of a photovoltaic (PV) system, a battery energy storage system (BESS), a thermal generation unit, and variable demands. Results indicated the effectiveness of the proposed IoT-based EMS in monitoring the operation of the microgrid and defining the optimal day-ahead dispatch of local DERs. • An IoT-based energy management system (EMS) for microgrids is presented. • A database, a web-based GUI, an API, and an optimization module comprise the EMS. • Optimal day-ahead dispatch is defined considering grid and security constraints. • Real-time simulations in a software-in-the-loop environment are implemented. • EMS is efficient in defining the dispatch and monitoring the operation of microgrids. [ABSTRACT FROM AUTHOR]

The modeling of the regulated electricity market is essential since it allows the calculation of optimal rates by the regulatory agency, resulting in maximum socioeconomic welfare. Besides that, it is also possible to predict consumer behavior based on socioeconomic models. Therefore, under rate readjustments, energy shifting can be estimated and encouraged by the regulatory agency. This paper proposes major modifications to the optimized tariff model, originally developed for constant rates and grids without distributed energy resources, to model static time-of-use rates, distributed generation, and energy storage, enabling regulated electricity market optimization. • Development of a regulated socioeconomic model for analyzing TOU rates with DG and ESS. • Development of an optimization technique to obtain maximum socioeconomic welfare. • Energy shifting estimation and promotion based on tariff manipulation. • Analysis of public incentive policies. [ABSTRACT FROM AUTHOR]

• Vector Shift Relay islanding detection capability versus system stability; • The need of Vector Shift Relay standardization for its secure applicability; • A Vector Shift Relay adjustment procedure for grid-tied synchronous generators; • A case study on Brazil's anti-islanding commissioning for distributed generation. The increasing electricity demand has encouraged consumers to invest in distributed energy resources and, among these, synchronous generators fed by biogas. One of the main concerns over this is the possibility of these sources feeding a section of the grid while a loss of mains, known as islanded operation. To prevent it, distributed generators must have protection devices that can identify this loss of connection. Vector Shift Relays are one of the most popular methods for island detection applied to synchronous generators. However, an increasing concern on false tripping of these relays has led the Brazilian electricity regulatory agency to ponder about their removal. In this paper, a detailed analysis of the Vector Shift Relay operation and configuration is done and a new procedure to determine the relay threshold value is proposed, considering different power-load mismatches. It is shown that this protection device is quick to detect islanding when there is a power unbalance greater than 30% but it may risk false tripping if adjusted to a lesser power mismatch. Finally, a discussion is presented to show that there are issues with correctly using this device and still complying with current standards, and further investigations are recommended. [ABSTRACT FROM AUTHOR]