Multi-objective mutation-enabled adaptive local attractor quantum behaved particle swarm optimisation based optimal sizing of hybrid renewable energy system for smart cities in India

可再生能源 粒子群优化 光伏系统 风力发电 按来源划分的电力成本 汽车工程 环境科学 发电 计算机科学 工程类 可靠性工程 电气工程 功率(物理) 量子力学 机器学习 物理
作者
Ramakrishna S S Nuvvula,D. Elangovan,Rajvikram Madurai Elavarasan,Seyed Iman Taheri,Muhammad Irfan,Teegala Srinivasa Kishore
出处
期刊:Sustainable Energy Technologies and Assessments [Elsevier]
卷期号:49: 101689-101689 被引量:30
标识
DOI:10.1016/j.seta.2021.101689
摘要

Favourable renewable energy policies led to a higher proportion of renewable energy in the country’s entire energy generation. However, these regulatory affairs caused the lower capacity utilisation factor of thermal power stations. It is not prudent to burden the thermal stations by enforcing ramp rates during peak hours as this would cause serious operational issues. Hence, further renewable additions must be supported by battery-energy storage systems (BESS) to meet the grid ramping requirements. BESS being quite expensive and require heavy maintenance, municipal solid waste-based waste-to-energy (WtE) plants play a crucial role in enhancing grid reliability under a high renewable energy (RE) environment. In this paper, the potential of four renewable energy technologies, such as floating solar, bifacial rooftop, wind energy conversion system, and WtE plant, are evaluated for a smart city, Visakhapatnam, India. This paper identifies a total of 439 MW of RE potential in the selected location. Mutation-enabled adaptive local attractor-based quantum behaved particle swarm optimisation (ALA-QPSO), supported by the combination of BESS and WtE plant, and is applied to obtain the optimal configuration of photovoltaic (PV) and wind energy conversion system (WECS) by minimising the techno-economic objectives of a municipal body. The results are compared with four variants of differential evolution. The results show that for an optimal set of BESS and hybrid renewable energy sources (HRES), the grid can offer better reliability with the presence of the WtE plant. The obtained optimal configuration results in a levelized cost of US $ 0.0539, high reliability with a loss of power supply probability of 0.049%, and reduced battery degradation with minimal life cycle loss of 0.048. The municipality requires a total investment of US $ 40.5 M, a significant part of which can be met by acting as a renewable energy service company between the rooftop owners and the distribution companies.
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