Advanced Optimization and Control Methods for Adaptive Microgrids

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"This is a research project in electrical/electronic engineering. This project will explore the issue of enabling resilient energy communities or local microgrids, which increasingly rely on local renewable generation, with reduced dependency of a centralised (national or regional) power grid. Such settings are very frequent in ODA nations, such as India and Bhutan, but DNOs in developing countries (such as the UK) are increasingly interested in increasing local energy resiliency, especially given widespread embedded renewables, storage and new loads, such as EV charging.This requires new control techniques, which enable assuring a stable power supply in decentralised grids with significant embedded generation, modeling user incentives and demand, as well as new platforms that enable peer-peer electricity exchanges. Relevant modeling techniques for this problem include multi-agent systems, distributed AI and machine learning, as well as technologies that empower users to take control of their own energy demand (such as blockchains). The pinch point analysis proposed by the candidate in a previous Elsevier "Energy" paper is also a good example of such a method. The PhD student will be based within the Smart Systems Group (https://smartsystems.hw.ac.uk/). Work in this PhD project will benefit and complement research in two large EPSRC research projects the group runs: CESI (the UK National Centre for Energy Systems Integration) [EP/P001173/1], CEDRI (Community Energy Demand Reduction in India) [EP/R008655/1] and SCORRES (Smart Control of Rural Renewable Energy & Storage in India) [EP/P031145/1]. The experience of the candidate in the challenges of the power grid in Bhutan and India will bring considerable additional value to these research projects."