Residential Demand Response model and impact on voltage profile and losses of an electric distribution network

Venkatesan, Naveen; Solanki, Jignesh; Solanki, Sarika Khushalani

doi:10.1016/j.apenergy.2011.12.076

Cited by 154 publications

(61 citation statements)

References 9 publications

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“…As the likelihood of switching on a device of discrete time duration, D, is represented by a single switch-on probability, P, consumers would react to the prices over that discrete duration in determining how to react to variable prices. So the change in probability of any single instant, i, is a function of the price differentials experienced over the entire window of operation (12).…”

Section: B Effect Of Discrete Duration Appliancesmentioning

confidence: 99%

“…Other research into developing residential demand response models uses timevarying values for self and cross elasticity of demand to determine the potential distribution network impacts at an hourly resolution and assuming continuous demand [12]. In [13] a bottom-up simulation of household electricity demand is presented under variable pricing, without simulating elastic consumer response, but automating the operation of appliances that require minimum or no consumer interaction such as wet and cold appliances.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Discrete elastic residential load response under variable pricing schemes

McKenna

Keane

2014

IEEE PES Innovative Smart Grid Technologies, Europe

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Section: B Effect Of Discrete Duration Appliancesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Discrete elastic residential load response under variable pricing schemes

McKenna

Keane

2014

IEEE PES Innovative Smart Grid Technologies, Europe

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“…DR is one of smart grid tools that empowers customers and offers them with opportunity to interact with utilities. It has the potential to reduce overall plant and capital cost investments and postpone the need for network upgrades [4] (Venkatesan, Solanki et al 2012). Real time pricing (RTP), one of the DR tools used in this paper is more flexible because its price varies on hourly basis [5] (Chen and.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder

Petinrin¹,

Sanusi²,

Tijani³

et al. 2017

IJMEA

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Abstract:Increasing demand on electrical energy coupled with lack of new distribution facilities create a potential threat that can eventually sprawl to jeopardize the distribution system reliability. The variability characteristics of wind energy sources present a fundamental problem to its smooth integration in the distribution feeders, in a large proportion. Energy storage (ES) systems and demand response (DR) technique have the potential to improve the flexibility of distribution network, by allowing two ways of freedom for the distribution network operator (DNO), to support mitigation of demand-supply balance issues, and thereby the share of renewable energy sources (RESs) or improve penetration levels of renewables. By shifting electricity supply and customer demand patterns, this paper applies real time pricing and energy storage not only to significantly increase the penetration of wind energy, but also to offer other important value to shifts demand to times of relatively high renewable energy resources and low load; and by storing energy during off-peak, with less line losses, and redispatching this energy when needed. The results show that real time pricing and energy storage can effectively provide demand-supply benefits to the distribution network and customers.

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“…Therefore, it is important for electric power system operators to make full use of household RTP. Recent studies mainly focused on how to increase proportion of using intermittent energy resources by RTP in electric markets [1][2][3][4][5][6][7][8][9]. Based on time-dependent and price-dependent characteristics of RTP, a RTP model used in day-ahead markets is built to minimize the expected total payment in [2].…”

Section: Introductionmentioning

confidence: 99%

“…Based on time-dependent and price-dependent characteristics of RTP, a RTP model used in day-ahead markets is built to minimize the expected total payment in [2]. A 24 9 24 price elasticity matrix is built to indicate the hourly varying rates to study the effects of demand reduction on system voltage [3]. RTP is modeled by adopting marginal pricing to justify the price function at a base price associated with base load level in a residential area [5].…”

Section: Introductionmentioning

confidence: 99%

Economic optimization of smart distribution networks considering real-time pricing

Zhang

Zhao

et al. 2014

J. Mod. Power Syst. Clean Energy

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With the development of smart meters, a realtime pricing (RTP) demand response is becoming possible for households in distribution networks. The power flow can be bidirectional in distribution networks which become smarter with distributed generators (DGs). It is expensive to import electricity from the generation far from load centers because of the cost of power loss and network use, so that it is more economical to use electricity generated by local distributed generators. Therefore, in order to curtail operating costs of distribution networks, this paper proposes a model of economic optimization conducted by distribution network operators. The electricity purchasing costs for distribution network operators are minimized by optimizing electric power from transmission systems and local distributed generators. Further, based on price elasticity, the formulations of load demand considering RTP are proposed with economic optimization of distribution networks. The economic optimization problems are resolved by an interior point method. The case study shows that peak load demand can be reduced about 3.5% because the household RTP and electricity purchasing costs of distribution network operators can save 28.86 £ every hour.

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Residential Demand Response model and impact on voltage profile and losses of an electric distribution network

Cited by 154 publications

References 9 publications

Discrete elastic residential load response under variable pricing schemes

Discrete elastic residential load response under variable pricing schemes

Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder

Economic optimization of smart distribution networks considering real-time pricing

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