To meet the electricity demand in rural, urban, and remote places like islands and hill-tracks, it is difficult to rely on one source, and therefore the hybrid renewable energy system (HRES) has become an inseparable part of the power system. HRES generally composed of two or more energy harvesting options based on renewable or non-renewable sources along with storage devices and consuming units. Due to the multiple sources and consuming units, its structure and operations are sophisticated and therefore need detailed knowledge about its operation and optimization. Regarding optimization, artificial intelligence (AI) based optimization plays a crucial role in parallel with classical optimization. Besides, to foresee the performance of either classical or AI-based HRESs, several simulation software is available to predict their behavior before implementation. Hence, this chapter is designed to provide the ins and outs of HRESs, like, the configuration architecture, stability issues, maintenance, available optimization techniques, and performance predicting simulation software for HRESs. Fourteen recent popular simulation software is described and compared to help the researcher to pick the apposite software for the specified HRESs. Finally, the challenges of HRESs and the future scope of it are also described in this chapter to show the limitations and opportunities of using HRESs.
Link: https://www.routledge.com/Introduction-to-AI-Techniques-for-Renewable-Energy-System/Tripathi-Dubey-Rishiwal-Padmanaban/p/book/9780367610920
KHULNA UNIVERSITY OF ENGINEERING & TECHNOLOGY
