search query: @keyword demand response / total: 19
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Author: | Ali, Mubbashir |
Title: | The role of electric space heating in demand response |
Publication type: | Master's thesis |
Publication year: | 2012 |
Pages: | viii + 65 s. + liitt. 7 Language: eng |
Department/School: | Sähkötekniikan laitos |
Main subject: | Sähköverkot ja suurjännitetekniikka (S-18) |
Supervisor: | Lehtonen, Matti |
Instructor: | |
Electronic version URL: | http://urn.fi/URN:NBN:fi:aalto-201401141130 |
OEVS: | Electronic archive copy is available via Aalto Thesis Database.
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Location: | P1 Ark Aalto 989 | Archive |
Keywords: | demand response electric space heating optimal DR control |
Abstract (eng): | The primary objective of Smart Grid vision is to facilitate the integration of intermittent renewables with a high degree of reliability. Intermittent renewable energy sources (RES) are characterized by their variability and uncertainty which makes their integration in existing power system a very challenging task. The demand response (DR) is playing a crucial role in smart grid research today and there is a strong belief that DR is the only economical and feasible solution for making the RES integration on a large scale. The vital aim of this study was to optimize the DR control of electric space heating with some degree of thermal storage in households under a smart grid scenario. The effect of degree of storage on flexibility of controlling the space heating load is compared by varying the size and initial level of thermal storage. The proposed model can easily integrate to the household level to allow a better exploitation of renewable energy sources and reduction of customer energy bill. The control methodology rests on the simple linear programming algorithm which fulfils certain objective without compromising on quality of service. The objective function was based on the dynamic pricing that follows power exchange prices. However this dynamic tariff can take any trend depending on the priorities (market, reliability) of retailer/aggregator. The study also explored the space heating strategies by performing case studies whose objective was to reduce the peak to average ratio of grid with least loss of user comfort. Thermal model of house was constructed using Simulink to replicate cooling behaviour and thermal inertia of the house. The simulation results quantify the flexibility they offer in terms of load shifting and load reduction during peak period and were assessed by observing the heating type load profile and considering the developed thermal model of house. |
ED: | 2012-12-10 |
INSSI record number: 45703
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