<span lang="EN-US">This paper discusses on the implementation of a grid-connected PV system for university campus in Malaysia. The primary goal of this study is to develop a grid-connected microgrid comprises of Photovoltaic (PV) and a battery storage system to meet the campus load demand and minimize grid dependency. The microgrid modeled and simulated in Hybrid Optimization Model for Electrical Renewable (HOMER) software. Actual load profile and renewable resources were used as an input parameter for the hybrid system. The campus selected is Universiti Kuala Lumpur, British Malaysian Institute as it represents typical load profile for a small campus. Therefore, the results can be used to represent hybrid system development for other small campuses in Malaysia as well. Firstly, optimal sizing of renewable energy (RE) were simulated with respect to total Net Present Cost (NPC) and Cost of Energy (COE). Then, sensitivity analysis conducted to determine the system performance based on changes of load growth, and renewable resources. The results demonstrate optimal HRES combinations for the campus microgrid comprises of 50 kWp of PV generations with 50 kW inverter. However, inclusion of 576 kWh battery storage system will increase the NPC but has higher RE penetration.</span>
<p>There had been increase of the usage of renewable energy sources to supply electricity in remote areas. However, microgrid consists of renewable sources such as solar Photovoltaic (PV) poses challenges for a reliable energy supply due to its intermittent nature. This paper presents a microgrid model with Energy Management System based on Model Predictive Control (MPC). The microgrid comprises of PV, and battery storage system. The goal of the EMS is to deliver a reliable and optimal generation from multiple sources in the microgrid. Moreover, the MPC will also provide controls for the battery charging for a smooth PV output. The model simulated based on actual load profile and renewable resource such as solar radiation. Several disturbances such as variation of load, generation and PV shading has been simulated to measure the performance of the EMS. The results illustrate the system ability to exhibits robust performance in variety of conditions.</p>
Microgrids are new technologies for integrating renewable energies into power systems. Optimal operation of renewable energy sources in standalone micro-grids is an intensive task due to the continuous variation of their output powers and intermittant nature. This work addresses the optimum operation of an independent microgrid considering the demand response program (DRP). An energy management model with two different scenarios has been proposed to minimize the costs of operation and emissions. Interruptible/curtailable loads are considered in DRPs. Besides, due to the growing concern of the developing efficient optimization methods and algorithms in line with the increasing needs of microgrids, the focus of this study is on using the whale meta-heuristic algorithm for operation management of microgrids. The findings indicate that the whale optimization algorithm outperforms the other known algorithms such as imperialist competitive and genetic algorithms, as well as particle swarm optimization. Furthermore, the results show that the use of DRPS has a significant impact on the costs of operation and emissions.
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