Title: Modeling of residential demand response of smart electricity grids to day ahead markets
Abstract: Developments in the electricity system need to accommodate the pressure of steadily rising demand, advanced technology integration in addition to increasing penetration levels of renewable energy sources (RES) and distributed generation (DG). As such, European energy policy for 2020 is aimed at reducing greenhouses gases by 20%, increasing RES by 20% and curbing energy consumption by 20%. Renewable generation in the Netherlands accounts for 4% of the national energy use with an expected 14% increase by 2020. Traditionally, power system control has adapted the supply side to meet fluctuations in consumption, with little attention paid to demand side modifications and thus accounting for the resultant system and grid inefficiencies. As the Dutch veer away from flexible fossil-?based electricity supply and towards greener stochastic generation the system will have to consider all available resources for balancing, including the demand side. The implementation of Demand Side Response (DSR) has the potential to provide added flexibility to dynamic system conditions solely based on reshaping the demand for electrical energy. DSR mechanisms entail incentivizing load flexibility in response to an economic stimulus reflective of generation or transport constraint in the power system. Given today's grid capabilities and owing to the intermittency of the power production by Renewable Energy Sources (RES), there is little scope of integration of renewables and other decentralized power generating units. The consumers would thus be prosumers in the future, wherein their domestic power production through PV and wind would be integrated within the framework of the conventional electricity grid. This would not be possible without insights into their production characteristics and consumption behavior. However, the precise impact of the DSM policies on the consumer behavior in the Netherlands is not yet known. Agent-?based simulation is used to model the consumer behavior with respect to Demand Side Response in the liberalized Dutch electricity market. The model inputs include electricity consumption by household type, APX power NL Day-?Ahead auction results and selected price-?based DSR mechanisms. In order to assess the potential of residential DSR, a bottom-?up construction methodology is used to simulate the average domestic electricity consumption for every household type. Household profiles are generated on the basis of current data from domestic electricity consumption of appliances in Dutch households, whereby accurately representing the electricity consumption and flexibility feasibility on a 24 hour basis. Consumer response to implemented mechanisms is modeled based on the potential drivers for Dutch power consumption behavior: convenience, cost, conscious and climate. Furthermore, price results from the Day-?Ahead auction are used and DSR mechanisms (TOU, CPP and RTP) are constructed from the resulting hourly prices. The emergent behavior from the hourly interaction between consumer response and mechanism serves as an illustration of the tangible value of aggregated demand-?side flexibility. Decentralized power production from renewable energy sources like PV and wind are modeled as components of the prosumers. The effect of renewables integration and distributed generation in the form of rooftop PV's and the effect of electric vehicle charging based on the current ownership rate are integral to the model. The ultimate objective of the model is to provide insight into the effectiveness and feasibility of residential Demand Side Response to price fluctuations in the day-?ahead market, serving as a decision support tool for effective policymaking from simulation of various scenarios (penetration rate of appliances and levels of renewable energy share to the prosumer generation mix) based on the pricing mechanisms set by regulators. It would also inform the policymakers of the policies that could augment the overall system efficiency and thus engage the gear towards sustainable development. Furthermore, it is expected to facilitate them to formulate effective policies that would maximize the net social welfare of the economy and incentivize the adoption of smart metering technologies by consumers. Results of the research show that Critical Peak Pricing (CPP) price mechanisms have the highest saving potential for the consumers and resulted in the maximum reduction in the system peak demand for the residential electricity system. As a consequence, it was estimated that the investment on smart meters in the households would pay its upfront investment back in roughly 6 months from the date of use. From the analysis of model results, it was found that the mere virtue of design of the policies, the system could be influence to great extents as a result. It was also found that the design of policies is key to expediting the diffusion of a particular technology (EV and PV) and promoting social welfare in the electricity system. Additionally, CPP policies were found to be the best to incur the least cost for consumers at higher penetration levels of these green technologies, which incentivizes an increase in the share of decentralized residential power production by PV for self-?consumption. From extensive analysis and upon reflection, it is concluded that the newly proposed CPP-?7PM policies fare better than the other alternatives and therefore are recommended for adoption in the Dutch electricity system. As an extension of the conclusions from the model, additional measures including awareness creation programs about the benefits of energy saving measures and participating in load shifting for the consumers are to be introduced in order to be able to fully maximize the potential of Demand Response as a flexibility resource in the electricity market.
Publication Year: 2013
Publication Date: 2013-01-01
Language: en
Type: article
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Cited By Count: 3
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