Degree of Flexibility of Electricity Prices

4090 words (16 pages) Business Assignment

11th Jun 2020 Business Assignment Reference this

Tags: Business AssignmentsEnergyEconomics

Disclaimer: This work has been submitted by a student. This is not an example of the work produced by our Business Assignment Writing Service. You can view samples of our professional work here.

Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of BusinessTeacher.org.

1. Introduction

Reasoning for Project

Scottish Power Energy Networks are currently in the process of transitioning from a Distribution Network Operator (DNO) to a Distribution System Operator (DSO). With the UK building towards a low carbon future the demand for electricity is going to reach unprecedented levels as it replaces fossil fuels; the electrification of heating and transport will see demand for oil and gas fall sharply. As a result, SPEN and the other UK DNOs are no longer able to rely on a centralised energy generation system to supply customers.

SPEN are experiencing increasing volumes of Distributed Generation and Distributed Energy Resources, Smart Meters and electric vehicles. The National Grid has forecasted that there could as many as 36 million EVs in the UK by 2040.

SPEN need to adapt to these changes whilst maintaining low cost and security of supply to customers. In addition, there are an increasing number of customers becoming ‘prosumers’ (both consumers and producers of electricity). A fair market is required to facilitate for the services that they could provide to the electrical network.

An effective DSO model will reduce system balancing costs, whilst enabling the flexible networks necessary to facilitate customer’s use of low carbon technologies. SPEN plan to invest in network monitoring, control and communications, which ultimately would minimise the overall costs to customers.

The costs associated with reinforcing the network infrastructure in order to accommodate the immense increase in electricity consumption would be astronomical. Furthermore, increasing the capacity of the network would only be required at certain times of the day when demand reaches its peak; peaking around 9am and 6pm. For the rest of the day the increased capacity would remain idle.

The favoured option by SPEN and OFGEM is to implement a flexible network. Customers will be offered financial incentives in order to shift consumption of electricity away from the peak times. Shifting demand away from the peak times would alleviate the need to reinforce the capacity of the network.

Existing literature surrounding the transition the DSO suggests that flexibility is the key to accommodating the extra demand associated with EVs and electrification of heat. Several of the UK DNOs, including SPEN, have composed a DSO Vision laying out the step by step process. However, this is a brand new challenge that has never been undertaken before so there are many unknowns and assumptions. It has been suggested that this is the greatest challenge faced by the UK since the privatisation of the electricity network.

SPEN Overview

System Maximum Demand

The maximum system demand on the SP Distribution system for 2017/2018 was 3,575 MW and occurred in the half hour ending 17:30hrs on 12th December 2017. Over the five-year period of this Statement, the winter peak demand for the SP Distribution area is estimated to reach 3,682 MW by 2022/2023.


Annual Load Profile

Electricity consumption is expected to increase as the uptake of low carbon technologies continues to grow. Electric vehicles and heat pumps will be the largest contributors to the increase in electricity demand. The medium scenario projections for domestic LCTs are shown in the table below.

There could be as many as 700,000 EVs in SPD by 2032 with the acceleration of the 2040 EV uptake by 8 years. Average domestic EV would double domestic consumption, increasing average-diversity-maximum-demand (ADMD) between 1.5-2.5kW. The distribution network infrastructure would require an estimated investment of £200-300m by 2032.

Typical slow EV charger 7kW

  • Charges 100% in 3-4 hours
  • Equivalent of using 4 washing machines

Typical fast EV charger 145KW

  • Charges 80% in 30 minutes
  • Equivalent of 73 washing machines

Average UK household annual consumption

  • Without EV = 3200kWh
  • With EV = 6500kWh (Based on 10,000 miles per annum)

The chart below shows the typical daily load profile in SPD for summer and winter. The graph shows that demand for electricity peaks between 17:00 and 18:00 in winter and 18:00 and 19:00 during summer. Research has shown that typically EV owners will charge their car as soon as they arrive home from work, i.e. between 5pm and 6pm. As a result, load during this time will exceed the capacity of the network and will require reinforcement. The need to reinforce the network, which is both costly and time-consuming, could be delayed/avoided using flexibility services.

2. Flexibility

Flexibility in a distribution network is the ability to react to the fluctuating needs of the power network whilst ensuring the security of supply to the customers. Flexibility services, such as demand response, would be used to shift peak load to times where demand is much lower, essentially flattening the daily demand curve.

Benefits of demand response to transmission grids:

  • Able to mitigate transmission congestion
  • Delay transmission expansion projects
  • Improve the reliability of the transmission grid

Benefits of demand response at distribution level:

  • Relieve voltage problems
  • Reduce congestion at distribution substations

Other benefits of demand response include:

  • Lower line losses
  • Reductions in thermal damage to system components
  • Easier integration of renewable energy sources
  • Successful demand response programmes can reduce the cost of electricity for all consumers on a system

Dynamic pricing is used to control the consumption of electricity.

Dynamic electricity is a pricing mechanism that changes prices in accordance with imbalances in the demand and supply conditions for electricity, thus incentivising customers to use electricity more efficiently or change their consumption behaviour.

Smart meters are essential to ascertain the amount of electricity being consumed in homes and commercial establishments during different time periods.

Dynamic pricing includes the following types:

  1. Critical Peak Pricing (CPP)

Electricity prices rise only when the electricity demand-supply balance is under strain. It is only in these specific times during the day that a higher price is presented to the consumer. Customers receive an ex-Ante notification of these moments in time and can therefore plan their consumption.

  1. Peak Time Rebates (PTR)

Electricity prices increase but pays rebates to households that save electricity during peak times

  1. Real Time Pricing (RTP)

Synchronises retail prices with wholesale prices. The user receives a changing price per time step (e.g. 15 minutes) and the customer will shift demand consumption accordingly.

Critical Peak Pricing together with the options for baseline adjustments are specifically incentivising the shift of electricity consumption away from a specific moment in time. A driver for such incentives could relate to, for example, high wholesale market prices or jeopardised system reliability.

Dynamic Electricity Pricing Trial

Using the ceiling cost calculation model – developed by the SPEN Economics department – we can calculate the maximum annual payment to flexibility that will give a Net Present Value equal to a reinforcement scheme. In other words, it is the cost of flexibility that would equal the cost of reinforcement. Lowering the annual payment to flexibility below the maximum would make flexibility the more economic option.

We can determine the cost of flexibility, i.e. the % increase in the price of electricity required to lower demand by χ%, using the price elasticity of electricity. The equation is shown below:

Economic Model to illustrate the cost of flexibility

The percentage change in price is equal to the percentage change in demand divided by the price elasticity of electricity (

The price elasticity of demand is a measure used in economics to show the responsiveness, or elasticity, of the quantity demanded of a good or service to a change in its price when nothing but the price changes.

According to economic theory, electricity demand will fall as the energy price increases; holding all other factors constant. The consumer’s sensitivity to price changes can be measured by the coefficient of price elasticity: the percentage change in demand divided by the percentage change in price (holding constant all the other determinants of demand).

Price elasticity is a normalised measure (for the relative price change) of the intensity of how the usage of a good (in this case electricity) changes when its price changes by one percent. It facilitates a comparison of the intensity of load changes among customers, since the price change has been factored out; the price elasticity is a relative measure of response.

Constraint (1)

T proc = process horizon

The deployment of flexibility does not increase/decrease total electricity consumption within the process horizon. It simply shifts electricity consumption away from the peak load. In terms of industrial consumption, production performance will not be affected.

The following table gives a summary of the literature on the price elasticity for electricity demand:

Understanding the values of price elasticity of demand ()

  1. If = 0:

Demand is said to be perfectly inelastic. This means that demand does not change at all when the price changes – the demand curve will be drawn as vertical.

  1. If is between 0 and 1:

(I.e. the percentage change in demand from A to B is smaller than the percentage change in price), then demand is inelastic.

  1. If = 1:

(I.e. the percentage change in demand is exactly the same as the percentage change in price), then demand is said to unit elastic. A 15% rise in price would lead to a 15% contraction in demand leaving total spending by the same at each price level.

  1. If > 1:

Then demand responds more than proportionately to a change in price i.e. demand is elastic. For example, a 20% increase in the price of a good might lead to a 30% drop in demand. The price elasticity of demand for this price change is –1.5.

Factors affecting ε:

  1. The number of close substitutes for a good

The more close substitutes in the market, the more elastic is demand because consumers can easily switch their demand if the price of one product changes relative to others. Electricity can be substituted with gas for domestic/industrial heating and cooking. Petrol/diesel can also be used instead of electricity for transport. However, as a society we are aiming towards a low carbon future where green electricity will replace fossil fuels where possible.

  1. The cost of switching between products

There may be significant costs involved in switching between products. In this case, demand tends to be relatively inelastic. The UK electricity retail market is dominated by the 6 electricity providers: British Gas, EDF, E.on, Npower, Scottish Power and SSE. Although they are selling a homogeneous product (electricity) they offer a variety of rates, from variable to fixed contracts over a certain period i.e. 12 months. UK customers are able to switch provider to receive better deals. There may be costs in doing so.

  1. The degree of necessity or whether the good is a luxury

Goods and services deemed by consumers to be necessities tend to have an inelastic demand whereas luxuries tend to have a more elastic demand. Electricity is very much an essential commodity and is not considered a luxury. As the efficiency ratings of most domestic and industrial appliances improves, consumers are using less electricity. However, as society moves towards a low carbon future, areas such as heating and transport will become electrified, thus, adding to our reliance on electricity.

  1. The % of a consumer’s income allocated to spending on the good

Goods and services that take up a high proportion of a household’s income will tend to have a more elastic demand than products where large price changes make little or no difference to someone’s ability to purchase the product. In the UK, household electricity prices for 2019 are £0.19/kWh (World Energy Council, 2018). In 2018 the average annual electricity bill in the UK was £672 (average annual domestic standard electricity bills by home and non-home supplier based on consumption of 3,800kWh/year) (BEIS, 2019). The average salary in the UK is estimated at £26,156 (Office of National Statistics, 2019), and the average electricity bill accounts for 2.57% of the average salary in the UK

  1. The time period allowed following a price change

Demand tends to be more price elastic, the longer that we allow consumers to respond to a price change. Customers could react instantly to price increases in a scenario where the retail price of electricity is influenced by CPP and RTP. Customers will know in advance to shift their consumption of electricity away from peak times to avoid higher rates. It is assumed the peak times are constant.

  1. Whether the good is subject to habitual consumption – when this occurs, the consumer becomes less sensitive to the price of the good in question because their default position is to buy the same products at regular intervals. Consumers of electricity are creatures of habit.
  1. Peak and off-peak demand – demand tends to be price inelastic at peak times and more elastic at off-peak times. The daily demand for electricity peaks between 5-6pm. This varies slightly depending on the time of year. The aim of CPP and RTP is to shift demand from peak times. This would help to increase the degree of elasticity.

The price elasticity of electricity demand in South Australia

In 2011, Shu Fan and Rob Hyndman produced a paper to estimate the price elasticity of electricity demand for South Australia. First they undertake a review of the scholarly literature regarding electricity price elasticity for different regions and systems. Then they performed an empirical evaluation of the historic South Australian price elasticity, focussing on the relationship between price and demand quantiles at each half-hour of the day.

Fan and Hyndman found that the best annual demand model is found to include the GDP, the lagged average price and (cooling and heating) degree days, with the following coefficients (the percentage changes of demand with regard to the increments of GDP, price and degree days):

  • The coefficient of GDP is . That is, annual demand increases by1.44% for every additional $1 billion of GDP.
  • The coefficient of the price variable is 0.03442. That is, annual demand decreases by = 3.38% for every additional cent/kWH that the price increases.
  • The coefficient of cooling degree-days is 1.37104. That is, annual demand increases by = 1.38% for every additional 100 cooling degree-days.
  • The coefficient of heating degree-days is 2.155104. That is, annual demand increases by = 2.18% for every additional 100 heating degree-days.

As stated before, the own-price elasticity of electricity demand is calculated as:

Where is the price elasticity, P is the electricity price and Q is the demand.

Note that the numerator and denominator are expressed as a percentage of the change. This elasticity coefficient indicates the relative change in the demand for electricity that would result from a change in the electricity price. Then, the price elasticity is

Where is the coefficient of price, and is the price in year .

This equation indicates that price elasticity is correlated with price levels, and that there is a unique price elasticity coefficient for a given equilibrium point. By using this equation, the overall price elasticity is calculated as ranging from 0.363 to 0.428, and the value estimated at the sample median is 0.386.

For example, in order to avoid reinforcement demand in a particular area needs to be reduced by 50%. Using the mean value of elasticity of 0.386 we find that the price levels need to be increased by 130%.

The graph below shows the price elasticity of electricity during a typical day in South Australia, for Winter, Summer and the entire year. The day is divided into 48 half-hour periods.

Price elasticity coefficients for each half-hourly period, for the median demand of the entire year, winter and summer:

Summary of the price elasticity for different demand quantiles in Southern Australia:

Summary of the price elasticity at each half-hourly period, for the entire year, winter and summer:

The overall price elasticity in South Australia, estimated using historical data, ranges from 0.363 to 0.428, showing a moderate responsiveness of electricity consumption to changes in prices. For the demand median, the strongest price responsiveness appears approximately at the peak period; i.e., around 4 o’clock in the afternoon for summer and 7 o’clock in the evening for winter.

The price elasticity varies throughout the day, which suggests that flexible pricing schemes like TOU pricing could be an effective measure for abating the demand in peak periods, and balancing the ratio of peak to off-peak usage.

A similar study conducted in 2005 by Taylor et al. concluded that the price elasticity of electricity ranged from 0.05 to 0.26 in the United Kingdom.

  • An elasticity of 0.05 would require prices to increase by 1000% to reduce demand by 50%
  • An elasticity of 0.26 would require prices to increase by 190% to reduce demand by 50%

The values of elasticity calculated by Taylor et al. suggest that electricity is more price inelastic in the UK. This means that the demand for electricity is less responsive to a change in price than it is in Southern Australia. This is most likely a result of the colder temperatures in the UK, especially during winter months when the demand for heating is much higher.

3. Conclusion

In conclusion, the degree of flexibility of electricity can be measured using the price elasticity of demand for electricity.

The price elasticity of electricity is not constant. It varies depending on the time of year and even varies half-hourly on a daily basis. Other factors that influence the elasticity are population, GDP, price of electricity and climate indexes (winter heating degree days and summer cooling degree days).

Determining the price elasticity of demand will allow the user to ascertain how much price must increase in order to reduce demand by a predetermined level. This will then be used to set critical peak pricing levels in order to reduce demand during peak times.

Furthermore, the price elasticity can be used to determine how much price levels should be reduced in order to increase the demand for electricity during off peak times.

This framework could be used to provide an estimate for the cost of flexibility. The next step would be to perform a cost-benefit analysis of flexibility and compare this to reinforcement of the network.

References

  • Department for Business, Energy & Industrial Strategy (2019). Quarterly Energy Prices: United Kingdom, Quarter 1 (January – March). London.
  • Fan, S. and Hyndman, R. (2011). The price elasticity of electricity demand in South Australia. Energy Policy, 39(6), pp.3709-3719.
  • Ida, T. (2013). Can the smart grid save us from the power crisis?. Nihon Keizai Shimbun.
  • SP Energy Networks (2017). Scottish Government workshop. Glasgow: SP Energy Networks.
  • SP Energy Networks (2018). Distribution: Long Term Development Statement. Glasgow: SP Energy Networks.
  • The Office for National Statistics (2019). Average weekly earnings in Great Britain: July 2019. London.
  • World Energy Council (2018). World Energy Trilemma Index: 2018. London: World Energy Council, p.143.

Cite This Work

To export a reference to this article please select a referencing stye below:

Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.

Related Services

View all

DMCA / Removal Request

If you are the original writer of this assignment and no longer wish to have your work published on the UKDiss.com website then please: