Abstract:Recently, significant development has occurred in the field of microgrid and renewable energy systems (RESs). Integrating microgrids and renewable energy sources facilitates a sustainable energy future. This paper proposes a control algorithm and an optimal energy management system (EMS) for a grid-connected microgrid to minimize its operating cost. The microgrid includes photovoltaic (PV), wind turbine (WT), and energy storage systems (ESS). The interior search algorithm (ISA) optimization technique determines the optimal hour-by-hour scheduling for the microgrid system, while it meets the required load demand based on 24-h ahead forecast data. The control system consists of three stages: EMS, supervisory control and local control. EMS is responsible for providing the control system with the optimum day-ahead scheduling power flow between the microgrid (MG) sources, batteries, loads and the main grid based on an economic analysis. The supervisory control stage is responsible for compensating the mismatch between the scheduled power and the real microgrid power. In addition, this paper presents the local control design to regulate the local power, current and DC voltage of the microgrid. For verification, the proposed model was applied on a real case study in Oshawa (Ontario, Canada) with various load conditions.

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Photovoltaic (PV) power is most commonly used for water pumping applications. The DC output voltage of PV arrays is connected to a DC-DC converter using a maximum power point tracking (MPPT) controller to maximize their produced energy. Then, that converter is linked to a voltage source inverter (VSI) that converts DC power to AC power. Vector control is used to control the VSI fed three phase induction motor driving the water pump. The Affinity laws are used to change the pump characteristics by changing the pump speed, and consequently, the pump flow rate, head, and power will be varied. In this paper, the Affinity laws are adapted to achieve the pump hydraulic requirements while the power delivered to the pump motor remains unchanged by constructing new pump curves. A Matlab/Simulink model of the PV pumping system is observed over a wide range of weather and loading conditions.

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