Long term flexibility forecasting for grid planning

Examensarbete för masterexamen
Master's Thesis
Electric power engineering (MPEPO), MSc
Kenaan, Hadi
Passachin, Adam
Abstract With the expected electrification in Gothenburg, distribution system operators (DSOs) must cope with the increasing peak demand. Traditionally, it is done with grid reinforcements but in recent years, other strategies have emerged. One strategy is demand-side flexibility (DSF), which refers to the change in consumption that consumers may provide to support the grid. For a DSO to plan ahead, long-term forecasts of the available DSF are required in order to assess how its application can be incorporated into the network expansion plans and support the increasing capacity demand. In this study, a long-term forecast of the available DSF was conducted for the customer base of Göteborg Energi in order to investigate the availability and impact of DSF, both today and for the years 2030 and 2035. A customer segmentation and weighting of the total customer base, showcased the residential segment as most suitable for flexibility applications. The load shifting capability of heat pumps (HPs) and electric vehicles (EVs), as well as peak shaving effect from photovoltaic (PV) solar panels proved to be the most fitting demand side resources (DSRs) to investigate. The results indicated that on the coldest day of the year, the theoret ical maximum DSF in 2035 from HPs, PV solar panels and EVs would reach 145 MW during the expected morning peak load hours at 8 a.m. to 11 a.m. and 100 MW during the evening peak load hours at 4 p.m. to 7 p.m. Due to higher HP consumption and solar production during the early hours of the day, more DSF was consequently available in the morning, although there was no contribution from smart home charging of EVs at that time. With an expected 68% increase in power demand from today to 2035, the application of DSF from the residential customer base, could provide a 10% reduction of the expected power demand in Gothenburg during the morning peak load hours and 7% during the evening peak load hours.
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