Supporting high penetrations of renewable generation via implementation of real-time electricity pricing and demand response

By Andrew J. Roscoe, Graham W. Ault. 2010

299 citations recorded by the source corpus.

The rollout of smart meters raises the prospect that domestic customer electrical demand can be responsive to changes in supply capacity. Such responsive demand will become increasingly relevant in electrical power systems, as the proportion of weather-dependent renewable generation increases, due to the difficulty and expense of storing electrical energy. One method of providing response is to allow direct control of customer devices by network operators, as in the UK `Economy 7` and `White Meter` schemes used to control domestic electrical heating. However, such direct control is much less acceptable for loads such as washing machines, lighting and televisions. This study instead examines the use of real-time pricing of electricity in the domestic sector. This allows customers to be flexible but, importantly, to retain overall control. A simulation methodology for highlighting the potential effects of, and possible problems with, a national implementation of real-time pricing in the UK domestic electricity market is presented. This is done by disaggregating domestic load profiles and then simulating price-based elastic and load-shifting responses. Analysis of a future UK scenario with 15 GW wind penetration shows that during low-wind events, UK peak demand could be reduced by 8-11 GW. This could remove the requirement for 8-11 GW of standby generation with a capital cost of £2.6 to £3.6 billion. Recommended further work is the investigation of improved demand-forecasting and the price-setting strategies. This is a fine balance between giving customers access to plentiful, cheap energy when it is available, but increasing prices just enough to reduce demand to meet the supply capacity when this capacity is limited.

Subfields: Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/ad243215f1e72bb90f0752706d411859b1dfd272

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In Electrical and Electronic Engineering

In Renewable Energy, Sustainability and the Environment

Citations in the corpus

Renewables, nuclear, or fossil fuels? Scenarios for Great Britain’s power system considering costs, emissions and energy security (2015, background): “Second, the shape of the demand curve may change, for example due to large-scale demand response [24] or to additional sectors (heating and transport) becoming electrified.”
A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches (2015, background): “To reduce such a cost so as to support high penetrations of renewable generation, demand response has been more and more leveraged and implemented to smooth the stochastic and fluctuate renewable energy [48].”
The feasibility of 100% renewable electricity systems: A response to critics (2018, background): “Flexible, dispatchable power stations and storage technologies [45,46,49], together with demand response [102,103], are the appropriate partners.”
Review of demand response under smart grid paradigm (2011, background): “Authors in [11] examined the use of real-time electricity pricing in the domestic sector in supporting the penetration”
Social implications of residential demand response in cool temperate climates (2012, background): “Roscoe and Ault (2010) discuss the relative acceptability of shifting different end-uses, with modelling that indicates that UK load could be reduced by over 10% during times of high demand and low wind generation3 .”
On demand: Can demand response live up to expectations in managing electricity systems? (2019, background): “1 Forms of DR in represented in models and the role of automation or DLC Three modelling studies reviewed, [62], [69] and [71], specifically include real time pricing.”
Combined Operations of Renewable Energy Systems and Responsive Demand in a Smart Grid (2011, background): “In [17], it has been reported that the value of the implementation of real-time pricing in the U.”
Controlling Electricity Consumption by Forecasting its Response to Varying Prices (2013, background): “Furthermore, the use of price-responsive demand to support a high penetration of fluctuating generation (such as wind or solar power) through real-time pricing is studied in [5]–[7].”