Based on a previous empirical study of the effect of a residential demand response program in Sala, Sweden, thisproject investigated the economic consequences of consumer behaviour change after a demand-based time ofuse distribution tariff was employed. The economic consequences of consumers were proven to bedisadvantageous in terms of unit electricity price. Consumers could achieve more electricity bill saving throughstabilising their electricity consumption during peak hours, and this way bring least compromising of theircomfort level.In order to estimate the price elasticity of the studies demand response program, a new method of estimationprice elasticity was proposed. With this method, the intensity of demand response of the demand responseprogram was estimated in terms of price elasticity. Regression analysis was also applied to find out the priceincentives of consumer behaviour change. And the results indicated that the rise in electricity supply chargehardly contributes to load reduction, while the demand-based tariff constituted an advantageous solution on loaddemand management. However stronger demand response still

Based on a previous empirical study of the effect of a residential demand response program in Sala, Sweden, this project  investigated the economic consequences of consumer behaviour change after a demand-based time of use distribution tariff was employed. The economic consequences of consumers were proven to be disadvantageous in terms of unit electricity price. Consumers could achieve more electricity bill saving through stabilising their electricity consumption during peak hours, and this way bring least compromising of their comfort level. In order to estimate the price elasticity of the studies demand response program, a new method of estimation price elasticity was proposed. With this method, the intensity of demand response of the demand response program was estimated in terms of price elasticity. Regression analysis was also applied to find out the price incentives of consumer behaviour change. And the results indicated that the rise in electricity supply charge hardly contributes to load reduction, while the demand-based tariff constituted an advantageous solution on load demand management. However stronger demand response still requires better communication with customers and more incentives other than the rise in distribution tariff.

Electrical demand flexibility is a key component to enabling a low cost, low carbon grid. In this study, residential electricity demand and flexibility is explored from the lens of a virtual power plant operator. Individual and aggregate asset consumption is analysed using a pool of >10,000 household assets over 6 years. Key safety, comfort and availability limitations are identified per asset type. Pool flexibility is analysed using a combination of past data and principled calculations, with flexibility quantified for different products and methods of control. A machine learning model is built for a small pool of 200 assets, predicting consumption 24 hours in advance. Calculated flexibility and asset limitations are then used within an optimisation model, leveraging flexibility and combining the value of self consumption and day ahead price optimisation for a residential home. / Flexibilitet i efterfrågan av elektricitet är essentiellt för att möjliggöra ett elnät med låga kostnader och utsläpp. I denna studie undersöks elanvändning av en bostad samt flexibilitet i perspektiv från en virtuell kraftverksoperatör. Individuell och sammanlagd konsumtion analyseras genom tillgång av data från >10 000 bostäder över 6 år. Begränsningar av säkerhet, komfort och tillgänglighet identifieras per tillgångstyp. Sammanlagda flexibiliteten analyseras genom en kombination av tidigare data och principiella beräkningar, med flexibilitet kvantifierad för diverse produkter och kontrollmetoder. En modell för maskininlärning utvecklades för 200 bostäder och förutser konsumtion 24 timmar i förväg. Den beräknade flexibiliteten och tillgångsbegränsningar används sedan i en optimeringsmodell som utnyttjar flexibilitet och kombinerar värdet av självkonsumtion och optimerat pris för nästkommande dag för ett bostadshus.