The potential of residentialdemand response to reduce lossesin an urban low-voltagedistribution grid

Abstract: Demand response (DR) has been widely documented as a potential solution for severalchallenges the electrical power system is facing, such as the integration of intermittentrenewable electricity generation and maintaining system reliability undera rapid, global electrification. While l ots of r esearch has been done i nto differentmarket designs and tariffing methods, less work is available on the implications ofdemand response on power grid operation, especially for the low voltage side. Thepurpose of this thesis is to estimate the impact of a demand response program on thepower losses in the low-voltage distribution network.The thesis will also contributeto the, currently limited, knowledge base on practical implementation of demandresponse by evaluating the outcome of a real-life DR pilot project. This pilot is partof smart cities development project ’Stockholm Royal Seaport’ (SRS) in the east ofStockholm.The study compared the consumption behaviour of around 400 reference consumerswith a group of 154 DR enabled apartments, that are provided with an hourly varyingelectricity tariff. The goal was to evaluate what percentage of daily consumptionis being shifted from peak to off-peak hours by the active consumers in responseto the price signal, using hourly metering data collected between the 1st of Januaryand the 22nd of March 2017. During this period, grid measurements were also collectedfrom the SRS smart grid and used to estimate the technical power losses inthe low-voltage distribution network. By combining the daily load shift of the DRconsumers and the observed daily power loss fraction in the grid, an estimation wasmade of the impact of the demand response on the grid losses. A simulation modelwas also proposed, and used to simulate the effect of load shift on losses in a givengrid situation.It was found that the DR apartments overall exhibit a load shift of 2.8% of dailyelectricity consumption towards peak hours, and have a lower average load factor(0.57 versus 0.62 for the reference group). This could either mean that the pricesignal does not sufficiently manage to change load behaviour, or that the referencegroup was not representative. However, a strong variation in average load shift wasobserved amongst the individual DR apartments, ranging from -16% (shift towardspeak hours) to 7%. Especially the most electricity consuming apartments showedpositive load shifts. No direct influence of the load shift on the level of grid losseswas found. This could be due to a too small amount of DR consumers in the grid orconfounding factors such as variations in power factor and load size. To circumventthis problem, the simulation model was used to calculate loss reductions for severalpossible reference consumer groups and their possible reactions to a price signal. Itwas found that in the SRS project, the potential for loss reductions is limited becausethe reference group are already ’good’ consumers. The maximum loss reductionwould be around 4%. For grids with severe peak consumption however, optimalloss reductions from load shifting up to 25% were found.The key take-away is that, while the technical potential for loss reduction is considerablein grids with strong peak loads, more research is needed to identify incentivesthat effectively manage to make households change their consumption behaviour.More work should also be done to find methods that can correctly evaluate loadshifts.