International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 08 Issue: 05 | May 2021 www.irjet.net p-ISSN: 2395-0072 © 2021, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 3746 DESIGNING OF MODEL PREDICTIVE CONTROL ALGORITHM FOR ACTIVE AND REACTIVE POWER CONTROL OF A MICROGRID Abhimanyu Mandal 1 , Sridhar Burla 2 , Pramod Kumar Baghmar 3 , Ashish Dewangan 4 1 Assistant Professor (EE) , CCET Bhilai , Chhattisgarh , India 2 Assistant Professor (EE) , CCET Bhilai , Chhattisgarh , India 3 Assistant Professor(EE) , CCET Bhilai , Chhattisgarh , India 4 Assistant Professor (EE) , CCET Bhilai , Chhattisgarh , India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract- Microgrid development is a viable solution for integrating rapidly expanding renewable energy sources. However, the stochastic nature of renewable energies and changeable power demand has caused a slew of issues, including unstable voltage/frequency, difficult power management, and grid interaction. Predictive control has recently shown tremendous potential in microgrid applications due to its fast transient response and flexibility to suit various restrictions. This work examines model predictive control (MPC) in individual and interconnected microgrids, including converter- and grid-level control techniques applied to three layers of the hierarchical control architecture. MPC research is just getting started in microgrids, but it's already proving to be a viable alternative to traditional approaches for voltage regulation, frequency control, power flow management, and economic operation optimization. In addition, some of the most significant patterns in MPC development have been identified and addressed as future prospects. Key Words: Grid-Connected PV System, solar panel, inverter, renewable energy, MATLAB/SIMULINK, Model predictive control, microgrid, primary control, secondary control. 1. INTRODUCTION Renewable energy systems (RESs), such as photovoltaic systems (PVs) and wind turbine systems (WTs), have advanced fast in recent decades as a result of ecological, social, economic, and political pressures and interests [1-3]. Microgrids have emerged as a promising way to interconnect RESs, energy storage systems (ESSs), and loads through various power electronics interfaces to better integrate distributed generation (DG) into the utility grid [4-8]. A microgrid can function in grid-tied mode as a controllable single unit, or in islanded mode as a self-sufficient autonomous system, depending on how it interacts with the utility grid. Microgrids are divided into three categories based on the most prevalent buses: dc, ac, and hybrid. The setup of converter-interfaced microgrids with dispersed RESs and ESSs is shown in Figure 1. A microgrid can be connected to other microgrids via various converters, as depicted. It can also be connected to the utility grid via a shared coupling point (PCC). The diagram of interconnected microgrids is shown in Fig. It demonstrates how microgrids can be networked in a radial or mesh architecture, with power flow managed by a distribution network operator (DNO). PV, WT, ESS, electric vehicle (EV), resident, and industrial systems can all be accommodated in each microgrid. Model Predictive Control (MPC) is a control methodology that has been successfully utilised in the industry to address complicated control problems, and it is actively being investigated and embraced in the research community. This study examines the applicability of MPC to microgrids in terms of their primary functions. outlining the design methodology as well as the most recent developments Finally, the problems and future prospects of MPC and its microgrid applications are explained and summarised. The evolution of the smart grid to a more structured system based on microgrids and storage systems that cooperate and self-organize appears to be a key to transforming our existing energy system into a more sustainable one. Through evolving adaptability (ancillary service) markets and novel grid management concepts, a microgrid-based smart grid structure would not only allow greater coordination of emerging distributed components in the wholesale market, and it could also be used as a part of distribution and transmission system management. The ability of microgrids to operate in grid-connected/islanded mode, as well as the mobility given by energy storage systems in microgrids, look to be important solutions to the challenge created by future transmission and distribution networks. In the future power system, microgrids could strengthen dependability, cut emissions, and extend energy sources. They may greatly enhance grid security and stability. Several microgrid facilities can also recover and use heat from their DG systems, a method described as combined heat and electricity generation. Cooling generation can also be used as a power-to-X or flexibility tool. Another level of flexibility is given by directly connecting microgrids into networks of microgrids. Microgrids can also improve the energy system's resilience, security, and knowledge in order to progress toward an energy system that can support a substantial share of variable renewables. Figure depicts the