Abstract
The increase in the demand for a reliable electricity supply by the utilities and consumers has necessitated the evaluation of the reliability of power systems. A reliable electricity supply is characterized by no or minimal duration and frequency of supply outages. This has triggered the necessity of using renewable energy sources (RESs) with optimization methods for reliability improvement of electricity systems and reduction of greenhouse gas (GHG) emissions. The main objective of this study is to optimize micro-grid systems operations, improve reliability, reduce emissions and balance the demand and supply of energy through RESs and battery energy storage system (BESS). The adaptive model predictive control (AMPC) method is used to address the issues of micro-grid operation. The AMPC algorithm solves the optimization problem of disturbance prediction in a micro-grid with different types of RESs and BESS integration. This optimization problem considers different constraints for minimum operating costs in different case scenarios. The financial viability of the proposed method is investigated. Solar photovoltaic (Solar PV), wind plant (WP) and BESSs are used with the AMPC method to investigate the impacts of annual real interest rates on cost and emission parameters, quantification of the emission oxides from different case scenarios, reduction of the cost of electricity (Ccoe), and power system reliability improvement. A modified Roy Billinton Test System (RBTS) is used to confirm the reliability enhancement and financial feasibility of the system. Case studies are used to confirm the proposed methods using climatic data for the city of Pietermaritzburg (29.37°S and 30.23°E), South Africa. The results obtained establish that the incorporation of RESs and BESSs using the AMPC method gives satisfactory outcomes.
Highlights
T HE ever-increasing demand for electricity due to world population growth and economic expansion has placed a massive demand on a reliable power supply
STUDY In this study, the economic, environmental, and reliability impacts of fossil fuel generators, Solar PV, wind plants (WP), and battery energy storage system (BESS) in a micro-grid power system are investigated using the meteorological data of Pietermaritzburg, KZN, South Africa
EEN S and expected interruption cost (ECOST) are the reliability indices used for the evaluation of the network
Summary
T HE ever-increasing demand for electricity due to world population growth and economic expansion has placed a massive demand on a reliable power supply. This study has the goal of exploring the stochastic features of vital components of the micro-grid system to evaluate the reliability of the power system with respect to cost analysis considering Cacs, Cnpc and Ccoe. To the best of the authors’ knowledge, the reliability problems in micro-grid systems with integrated RESs, and the investigation of the impacts of ARIR on the cost and emission parameters, have not been previously addressed using an AMPC optimization algorithm. This work proves, through its results, that the reliability of a power system can be improved by the incorporation of RESs using the proposed method, and Cacs and Ccoe can simultaneously be reduced This outcome can serve as a measure for making investment decisions by utilities and the governments with respect to renewable energy policies
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