search query: @keyword demand response / total: 19
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| Author: | Bashir, Arslan |
| Title: | Demand Response in Electricity Markets: The Effect of Dynamic Cross Price Elasticity in Nord Pool |
| Publication type: | Master's thesis |
| Publication year: | 2015 |
| Pages: | 82 Language: eng |
| Department/School: | Sähkötekniikan korkeakoulu |
| Main subject: | Electrical Systems (S3015) |
| Supervisor: | Lehtonen, Matti |
| Instructor: | Ali, Mubbashir |
| Electronic version URL: | http://urn.fi/URN:NBN:fi:aalto-201603291529 |
| Location: | P1 Ark Aalto 3548 | Archive |
| Keywords: | demand response Nord pool elspot price elasticity |
| Abstract (eng): | In the context of restructured electricity markets, modelling of demand response (DR) is inevitable to evaluate the effects of price responsiveness on system demand and determine new demand supply equilibrium parameters in real time. Due to high volatility of day ahead market prices and long planning horizon, consumers may decide to modify their load profile. This work demonstrates the impact of price based DR on day ahead market equilibrium in Nordic electricity market and one possibility of real time price formation with regard to Elspot curves. Concepts of both self and cross price elasticity are utilized to assess inter-temporal characteristics of demand. For doing so, flexible price elasticity matrices are developed to accurately model customer electricity consumption pattern using historical demand and price data from Nord Pool. The calculated DR is then analyzed in demand supply curves of Elspot to check if it distorts the equilibrium i.e., increase in price is significant with respect to demand. Accordingly, an optimization algorithm is proposed for load aggregator to minimize the overall cost of purchasing electricity from the market without compromising on the comfort level and determine the optimal hourly load and price for given Elspot curves considering flexible DR. The proposed algorithm rests on linear programming approach. Simulation and numerical studies are performed for target day of winter. The obtained results verify the DR optimization algorithm. Based on the optimal prices, the load aggregator can set a flat tariff for its customers. |
| ED: | 2016-04-17 |
INSSI record number: 53341
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