The current chapter presents a novel modified complex coefficient filter-based phase-locked loop (MCCF-PLL) control technique for managing a single-phase grid-linked photovoltaic (PV) system integrated with an electric vehicle (EV) charging station. Designed for residential applications, this system enables efficient bi-directional power transfer, supports grid stability, and increases renewable energy usage. A bidirectional inverter serves as both an EV charger and a grid-interfacing converter, operating in multiple modes such as charging the EV battery, supplying stored energy back to the grid, and storing excess grid energy during low demand. The MCCF-PLL-based control system coordinates power flow among EV batteries, household loads, and the grid. MATLAB simulations validate the system's performance, showing enhanced power quality, grid stabilization during peak loads, and reliable backup power during blackouts. The system also meets IEEE-519 standards by keeping total harmonic distortion (THD) at 5%.

Automation has transformed fields, increased productivity and efficiency, and lessened the need for human labor. However, fast-growing e-commerce development has prompted concerns about environmental sustainability, such as increased energy consumption, resource waste, and electronic waste. This chapter addresses the overlap between automation and sustainability and the changes that it brings about in terms of sustainable practices in automation systems. Additionally, the chapter covers regulations and policy initiatives that shape sustainable automation adoption, as well as the financial impact on businesses. Results highlight the important role of collaboration between multiple stakeholders, strong policy incentives, and workforce adaptation in achieving automation systems that enable operational excellence and also strongly contribute to global sustainability. This chapter, in turn, helps to move the debate over industrial sustainability forward by arguing for a more balanced account in which automation is seen as enabling efficiency gains and environmental concern.

The Government of Uttarakhand has undertaken significant initiatives to promote renewable energy development to meet growing demand while safeguarding the

India has grown increasingly dependent on imported foreign fossil fuels to fuel an expanding population and economy, thereby placing considerable strain on the economy, society, and environment. Transitioning from fossil fuels to renewable sources of energy is necessary for India to continue developing and prospering as a nation in the future. One approach to realize energy goals (SDG-7) for India and assist it in transitioning to renewable energy is using photovoltaic (PV) technology. Despite having gained significant traction in India, many barrierss still exist beyond improving effectiveness. A systematic approach will be presented in this paper to overcome these barriers using the spherical fuzzy (SF) technique for decision-making. The SF decision-making technique is designed to help reduce uncertainty when making decisions and to minimize bias when evaluating procedures and regulations related to solar energy. To support the SF framework proposed, three different methodologies will be utilized: SF-SWARA for determining subjective criterion weights; SF-CRITIC for finding objective weights; and SF-CODAS for ranking strategic alternatives. Based on a literature review and recommendations from the authors, twelve main barriers will be identified and ranked according to their relative importance in achieving success with PV technology in India. Furthermore, it is suggested that funding be allocated for additional research and development to boost domestic production of PV equipment. An evaluation of the proposed methodology confirms its reliability, particularly through comprehensive sensitivity analysis. The authors provide thorough evidence to support the recommendation of using this methodology to evaluate the expected economic and environmental impacts of PV technology in India.