Key points are not available for this paper at this time.
Smart grids enhance the efficiency of power systems, especially during the integration of renewable energy (RE) systems. Utilising electricity from RES reduces harmful greenhouse gas emissions, provides diversity in the generation mix, and reduces the overdependence on fossil fuels. Various challenges are encountered during the integration and utilisation of such systems. Recent studies have proposed diverse techniques in addressing these challenges, however, there is a lack of research on the current techniques suitable for integrating the recent developments on REs and smart grids. This paper examines and synthesises the impacts, integration techniques, and scalability considerations associated with RE systems in smart grid applications using mixed-method analysis. In a systematic literature review (SLR), 101 articles were retrieved and analysed. These papers broadly categorised the impacts under grid stability and control, grid infrastructure challenges, energy storage and management, and the integration of intermittent power sources. The study further explores various techniques used to integrate RE into smart grids, including advanced control and protection systems, smart energy storage and management systems, grid infrastructure upgrades, and the development of predictive models. The findings highlight complexities and challenges, such as grid stability issues and the intermittency of renewable power generation. To address these challenges, the research emphasises the importance of developing hybrid optimisation models to enhance load scheduling, peak shaving, and cost reduction. The study also recommends further evaluation and testing of Quantum Deep Reinforcement Learning, neural networks, Autoregressive Integrated Moving Average (ARIMA) models, and adaptive fuzzy inference systems to enhance the reliability, efficiency, and sustainability of renewable energy (RE) integration into smart grids.
Yeboah et al. (Tue,) studied this question.