A Master of Science thesis in Electrical Engineering by Asmaa Ibrahim Abdelfattah entitled, “Optimal Management of Seasonal Pumped Hydro Storage in UAE”, submitted in November 2022. Thesis advisor is Dr. Ahmed Osman and thesis co-advisor is Dr. Mostafa Shaaban. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
Abstract
Power demand varies with the time of day and with seasons. Responding to changing demand over time, especially during peak times, is challenging for Energy suppliers. UAE annual demand curve is characterized to be high in seasonal variation. This causes peak power plants to operate more in the highest demand seasons, usually summer, increasing the cost of electricity and the operation of expensive power plants. Peak load shaving is making the load curve flatten by reducing the peak load and shifting it to times of lower demand and hence reduce the operation of expensive power plants. Possible solutions for demand curve flattening are switching off equipment or load-shifting techniques through demand side management (DSM), also through electrical vehicles (EV) integration, and Energy Storage Systems (ESS). However, DSM and EV integration are not applicable solutions for seasonal variation as the peak is mainly driven by the Air conditioning loads. Hence, there is a need for large-scale and long-term ESS to store energy in the time of low-demand seasons for future utilization in the highest-demand ones. This research aims to develop an Energy Management System (EMS) that optimally manages a grid-connected pumped hydro storage (PHS) unit to achieve the purpose of peak shaving. The proposed framework analyses the seasonal performance of PHS in supporting the grid in the UAE and reflects the possible economic benefits considering transmission constraints, optimal power flow, hydraulic model, and losses over a study period of one year. The proposed model incorporates dynamic economic dispatch (DED) over a relatively long period; hence DC power flow analysis is considered to ensure fast load flow estimation. This analysis is essential to motivate the construction of new seasonal PHS plants due to the high construction cost they are identified with, especially in geographical areas where this technology is not yet considered and is hard to construct.