The voluntary price for the small consumer: Real-time pricing in Spain

Fernández, Juan Manuel Roldán; Payán, Manuel Burgos; Santos, J.R.; García, Ángel Luis Trigo

doi:10.1016/j.enpol.2016.11.040

Cited by 28 publications

(12 citation statements)

References 23 publications

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“…During the past few years, DSR has been identified as a promising measure for, among others, providing system flexibility to reduce electricity demand, shifting peak demand, providing reserve capacity for unforeseen events, balancing electricity supply and demand and reducing congestion of the network and thus avoiding additional investments in new plants and network reenforcements (Bradley et al 2013;Strbac 2008). As a result, there are numerous studies focusing on consumers' reactions to pricing rates of various DSR schemes, such as static TOU, dynamic TOU and DLC (Asadinejad et al 2018;Bradley et al 2016;D'hulst et al 2015;Faruqui and George 2005;Roldán Fernández et al 2017;Thorsnes et al 2012). For instance, BC Hydro's residential TOU/CPP pilot study in British Columbia found that higher price ratio between peak and off-peak rates increased customers' reduction of energy use (Woo et al 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

“…There have been numerous studies aiming to explore consumers' engagement in DSR programmes. Most of them focused on consumers' aggregated reactions to pricing signals, such as static TOU tariff or dynamic pricing, but did not consider the possible influences of numerous socio-demographic factors (Asadinejad et al 2018;Roldán Fernández et al 2017). It has, however, been suggested that, in addition to financial incentives, socio-demographic backgrounds might also play a crucial role in consumers' decisions to participate in DSR (He et al 2012;Horne and Kennedy 2017;Xu et al 2018).…”

Section: Introductionmentioning

confidence: 99%

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Investigating UK consumers’ heterogeneous engagement in demand-side response

Keppo

Xenitidou

et al. 2020

Energy Efficiency

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Demand-side response (DSR), the incentivised time-shifting of energy use by consumers away from peak times, is regarded as a potentially effective measure to balance electricity supply and demand. This will be even more important in the low-carbon energy system of the future, with a high share of nondispatchable power, such as variable renewable energy and nuclear power. Most DSR programmes require consumers' active engagement in shifting end-use activities. Previous studies have, however, rarely revealed sociodemographic factors influential for consumers' willingness-to-shift specific end-use activities. This study thus aims to fill this research gap and, using a multinomial logistic model to analyse a nationwide survey, identify factors influential for DSR-related decisions. The nationwide survey for 1004 respondents was carried out to collect data about consumers' willingness-to-shift their daily activities. We focused on the activities that constitute the major part of domestic energy consumption, i.e. cooking, dish-washing, entertainment, heating, laundry and showering. According to the results, consumers' original timing of the end-use activities, sociodemographic factors, ownership of specific appliances and level of concern for energy-saving are influential for their willingness-to-shift activities. These findings can not only help policymakers make more targeted DSR promotion plans but also help to improve broader modelling tools to better consider consumers' willingness-to-shift their demand.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Investigating UK consumers’ heterogeneous engagement in demand-side response

Keppo

Xenitidou

et al. 2020

Energy Efficiency

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“…In Spain, the methodology for the calculation of the Voluntary Price for the Small Consumer, a real-time price tariff for small domestic consumers, came into force in 2014. The implementation of this real-time pricing scenario, as a tool of demand response, and the transposition of Directive 27/2014/EU, on energy saving, as a driver to improve the efficiency of the home appliances (for domestic consumers) was addressed in [13].…”

Section: Renewable Generation and Load-shifting: A Short Reviewmentioning

confidence: 99%

“…Consumers that apply for load-shifting programs expect to save in their electricity energy bills, due to the difference between the energy price at peak and off-peak hours [5], [7]- [10], [13], [14]. Nevertheless, when an important number of consumers shift an amount of energy from a peak hour to an off-peak hour, there is a resulting decrease in the price of the peak hour and an increase in the price of the off-peak hour, as can be observed in Fig.…”

Section: Load-shiftingmentioning

confidence: 99%

The Merit-Order Effect of Load-Shifting: An Estimate for the Spanish Market

Roldán-Fernández

Payán

Santos

2020

Environmental and Climate Technologies

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AbstractRenewable producers can offer selling bids with very low marginal cost since they are not obliged to include on any cost related to the use of energy from the wind or sun. Accordingly, when the Market Operator integrates a renewable bid in the merit-order generation curve, all the generators based on conventional technologies, with higher marginal cost due to the cost of fuels, are displaced to the right. The right-shifting of the merit-order generation curve leads to a lower clearing price, a small increment of the traded energy (almost inelastic demand curve), and a reduction of the total cost of the energy traded in the wholesale market. This is the key mechanism of the well-known merit-order effect of renewables. Load-shifting (demand-side management) plans are expected to yield a reduction of the cost of the traded energy for the customers, since the cost-saving due to the energy eschewed at peak hours would be greater than the extra cost due to the increased demand at off-peak hours. This work will show that the main effects of load-shifting on the market are qualitatively similar to that of renewables, which exemplify the existence a “merit-order effect of load-shifting”. To analyse the characteristics of the merit-order effect of load-shifting, a simplified model has been developed, based on the displacement of the generation and demand curves. A set of scenarios has been generated in order to quantify the main effects on the Spanish/Iberian market for 2015.

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“…These trends create both a need and an opportunity for dynamic pricing and demand response to help balance the power system. In a smart grid environment, price-responsive customers and devices can reschedule electricity loads from the times when electricity supply is scarce and production costs are high to times when supply is abundant and costs are low, thereby reducing bills and also improving the supply-demand balance for the power system as a whole [1][2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Control of Air Conditioning Improves Cost, Comfort and System Energy Balance

Izawa¹,

Fripp²

2018

Preprint

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A new model predictive control (MPC) algorithm is used to select optimal air conditioning setpoints for a commercial office building, considering variable electricity prices, weather, occupancy and lighting. This algorithm, Cost-Comfort Particle Swarm Optimization (CCPSO), is the first to combine a realistic, smooth representation of occupants' willingness to pay for thermal comfort with a bottom-up, non-linear model of the building and air conditioning system under control. We find that using a quadratic preference function for temperature can yield solutions that are both more comfortable and lower-cost than previous work that used a "brick wall" preference function with no preference for further cooling within an allowed temperature band and infinite aversion to going outside the allowed band. Using historical pricing data for a summer month in Chicago, CCPSO provided a 3% reduction in costs vs. a "brick-wall" MPC approach with similar comfort and 13% reduction in costs vs. a standard night setback strategy. CCPSO also reduced peak-hours demand by 3% vs. the "brick-wall" strategy and 15% vs. standard night-setback. At the same time, the CCPSO strategy increased off-peak energy consumption by 15% vs. the "brick-wall" strategy. This may be valuable for power systems integrating large amounts of renewable power, which can otherwise become uneconomic due to saturation of demand during off-peak hours. Keywords: HVAC model predictive control, demand response, EnergyPlus, particle swarm optimization (PSO), renewable energy, smart grids MSC: 49M37, 65K05, 90-04, 90B35, 90B50, 90C29, 90C56, 90C90, 91B08, 91B10, 91B26, 91B42, 91B74

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The voluntary price for the small consumer: Real-time pricing in Spain

Cited by 28 publications

References 23 publications

Investigating UK consumers’ heterogeneous engagement in demand-side response

Investigating UK consumers’ heterogeneous engagement in demand-side response

The Merit-Order Effect of Load-Shifting: An Estimate for the Spanish Market

Multi-Objective Control of Air Conditioning Improves Cost, Comfort and System Energy Balance

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