Executive Summary
With the upcoming impacts of Brexit, the UK energy market is under increasing pressure on budget planning and future investment decisions particularly reaching environmental targets. BP is increasingly working towards expanding its renewable energy sector and is currently facing uncertainties regarding how Brexit will impact the European Investment Bank’s subsidy program therefore impacting future investment opportunities. This report will investigate the investment choice of renewable energy sources wind or solar panels based on profitability and minimising costs. Factors that will be specifically looked at include the likelihood of subsidies being changed as well as the size of the subsidy being assigned to each renewable source.
1 Introduction
BP is a British multinational oil and gas company headquartered in London. Recently, the company has become a leading player in advancing the energy transition away from fossil fuels and hydocarbons towards renewable energy sources. Chief Executive Bob Dudley reports ‘BP faces major challenges currently as the world demands more energy whilst delivering it with fewer emissions’ (Dudley, 2019). This is known as the dual challenge in the energy sector which continues to be significant in company’s decision making.
BP’s ‘reduce, improve, create’ framework created in 2018 (BP, 2019) focuses around the whole of BP reducing emissions therefore efficient investment decisions are vital for the successful future of BP. As a company they have been investing in renewable energy for many years and now the focus is on biofuels, biopower wind and solar energy. The company plans to diversify its business therefore as said by chief executive Dudley the industry is in a period of major change (Dudley, 2019).
Presence in the energy industry gives the firm a pivotal role in meeting the climate change agreements and recent environmental targets (Gov, 2019). Recently, the company is facing a shareholder challenge to set carbon targets in line with the Paris agreement therefore the need for investing in renewable energy is now more significant (Hepburn, 2017).
For these high cost large scale investment projects subsidies and funding are vital in providing initial capital. Analysing the profit maximising and efficiency of renewable energy sources wind and solar are of critical importance given the impeding Brexit decision as well as environmental struggle. Specially in consideration are the higher start-up costs of solar energy but higher efficiency and revenue in generation. BP faces the decision of whether it should focus future investment on solar energy production or wind production, considering the uncertainty regarding EU subsidy payments.
2 Analysis
In order to run a comparison of the profitability of both renewable energy sources the general model will be introduced as well as stating the underlying assumptions and variables. Following this a detailed payoff analysis of expected utility for British Gas will be provided. Lastly, different scenarios will be discussed providing an insight effects of expected utility caused by altering risk preferences and probabilities.
2.1 Model
〖EU〗_wind=〖P [ R-(LCOE-0.115LCOE)]〗^α+(1-P) 〖[R-LCOE]〗^α
〖EU〗_solar=〖P [ R-(LCOE-0.115LCOE)]〗^α+(1-P) 〖[R-LCOE]〗^α
In this report the decision maker is British Gas. They have the options of either investing in solar farm energy production or wind production. Due to Brexit the uncertainty they face is whether EU subsidies will continue to be payed post Brexit or whether the subsidies will be cut. Based on research this means the subsidies will either be equivalent to the current subsidies which currently stand at 11.5% (Allen & Overy, 2016) or be cut to 0. In the model P denotes the probability of subsidies being changed post Brexit and 1-P denotes the probability of the alternative outcome so subsidies being erased. The conclusions we gain from the model and subsequent analysis will be according to the expected utility theory.
Based on our client and the market we are investigating our model will be in terms of profit maximisation per Mwh. This will be decided through minimising costs whilst choosing the most efficient generation of electricity. As a result, the model will use energy terminology such as LCOE (levied cost on energy per Mwh) and R (revenue per Mwh). The overall cost will therefore be calculated by taking LCOE figures as well as taking into account subsidies from the European Investment Bank which based on their current figures will be – 0.0115LCOE. The revenue per Mwh for solar panel generation and wind generation differ slightly with solar panels having a R value of 95.25 compared to winds value of 89.71 (US Energy Information Administration, 2019). Similarly, the LCOE values differ with wind’s LCOE being 42.92 and solars LCOE being 48.81 (2019). This model will be based solely on a simple cost benefit analysis however to extend the model additional variables could be added for example impacts on the wider community through spill over effects.
2.2 Risk Preferences
Risk Averse
Firstly, due to the uncertainties and concerns raised around Brexit and the energy market we will model BP’s risk preference as risk averse. This is because with increased worries we will assume BP will be additional cautious with decisions. A risk averse preference describes a firm that would choose a certain outcome over a fair gamble where the expected utility is the same. Therefore, the firm’s utility function adjusts as the second order derivative needs to be negative implying the diminishing marginal utility a firm faces.
This means our general model needs to change therefore for risk averse = ½.
So, the model changes to:
〖EU〗_x=〖P [ R-(LCOE-0.115LCOE)]〗^(1/2)+(1-P) 〖[R-LCOE]〗^(1/2)
The calculation undertaken to compare the profitability can be seen below:
〖EU〗_wind=〖 1/2[ 89.71-(42.92-0.115*42.92)]〗^(1/2)+1/2 〖[89.71-42.92]〗^(1/2)
〖EU〗_wind=〖 1/2[ 51.72]〗^(1/2)+1/2 〖[46.79]〗^(1/2)
〖EU〗_wind=7.016
〖EU〗_solar=〖1/2 [ 95.25-(48.81-0.115*48.81)]〗^(1/2)+1/2 〖[95.25-48.81]〗^(1/2)
〖EU〗_solar=〖1/2 [ 52.05]〗^(1/2)+1/2 〖[46.44]〗^(1/2)
〖EU〗_solar=7.014
Due to no general agreement and implications of Brexit being unknown we will assume the probability of subsidies remaining unchanged is 0.5 (P). Consequently, the probabilities of subsidies being reduced to 0 is estimated to be 0.5 (1-P). The R values and LCOE values are therefore substituted into the model and two different expected utilities per Mwh are computed. From the figures we can compare the expected utility from the two renewable energy choices. As can be seen the expected utility from wind generation exceeds the utility from solar generation marginally by 0.001. This means wind production will be preferred compared to solar for a risk averse preference. Based on research behind the model the reasoning is due to the higher initial costs from solar therefore a higher reliance on subsidies.
To widen the analysis another scenario which can be investigated is the impact Brexit could have on the other variables. The uncertainty aspect of our analysis can differ keeping all other variables constant. For example, research suggests due to innovation and investment the LCOE for both energy production will fall in future years. Data shows solar production LCOE could fall by 40% by 2020 (IREA, 2019) creating a new figure of 29.29. Meanwhile, wind production could fall by 25% calculating a LCOE of 31.52.
Therefore keeping all other variables the same if we adjust the LCOE’s accordingly the expected utilities and therefore preferred investment choice will adjust.
〖EU〗_wind=〖 1/2[ 89.71-(31.52-0.115*31.52)]〗^(1/2)+1/2 〖[89.71-31.52]〗^(1/2)
〖EU〗_wind=〖 1/2[ 61.81]〗^(1/2)+1/2 〖[58.19]〗^(1/2)
〖EU〗_wind=7.75
〖EU〗_solar=〖1/2 [ 95.25-(29.29-0.115*29.29)]〗^(1/2)+1/2 〖[95.25-29.29]〗^(1/2)
〖EU〗_solar=〖1/2 [ 69.33]〗^(1/2)+1/2 〖[65.96]〗^(1/2)
〖EU〗_solar=8.22
Therefore as can be seen by both expected utility figures if predicted cost patterns stay on track solar energy is greatly preferred to wind therefore BP would choose to invest in solar as the return is greater.
Risk seeking
However, arguably Brexit could be positive for the energy market and therefore the future could have a more positive outlook. As technology progresses the initial costs of solar farming are reducing with forecasts suggesting a drop of 40% by 2020 (New Energy Update, 2018) therefore affecting the efficiency of production. This increased market optimism could create greater risk tolerance change the risk preferences of BP to risk seeking behaviour. This preference can be defined as preferring the fair gamble over the certain outcome. Therefore, the second order derivative of utility is positive representing the increased marginal utility a firm experience. As a risk seeking firm they accept greater uncertainty for increased anticipated returns.
Considering this preference, the second model can be introduced where = 2 for a risk seeking BP. The model adjusts as can be seen below where as well as substituting in the original LCOE and r values are additionally inputted leading to the new expected utility and calculations below.
〖EU〗_x=〖P [ R-(LCOE-0.115LCOE)]〗^2+(1-P) 〖[R-LCOE]〗^2
〖EU〗_wind=〖 1/2[ 89.71-(42.92-0.115*42.92)]〗^2+1/2 〖[89.71-42.92]〗^2
〖EU〗_wind=〖 1/2[ 51.73]〗^2+1/2 〖[46.79]〗^2
〖EU〗_wind=2432.43
〖EU〗_solar=〖1/2 [ 95.25-(48.81-0.115*48.81)]〗^2+1/2 〖[95.25-48.81]〗^2
〖EU〗_solar=〖1/2 [ 52.05]〗^2+1/2 〖[46.44]〗^2
〖EU〗_solar=2433.10
The new expected utilities show that if BP takes a risk seeking preference solar production is preferred to wind generation as the expected utility is 0.67 greater. This kind of preference can occur due to the cognitive bias of ‘overconfidence’ which leads to an increased risk in investment decisions as the expected returns make the decision more favourable (Asberto et al, 2014)
2.3 Probability Analysis
So far in the analysis our model has been based on the underlying assumption of probability of each outcome occurring being 0.5 (50%) however in general we are uncertain of the impact of Brexit and therefore the likelihood of subsidies being cut is also unknown. To generalise the model, a new scenario can be created by assigning different weights on probability of the potential outcome.
To carry out this analysis we will revert back to the risk averse preference and model.
〖EU〗_x=〖P [ R-(LCOE-0.115LCOE)]〗^(1/2)+(1-P) 〖[R-LCOE]〗^(1/2)
For this analysis the probability of receiving subsidies post Brexit for solar generation will be P whilst the probability of subsidies being cut will be set to 1-P. Following the utility calculations and solving for P we can generate the probability weight assigned to receiving funding for solar production that makes the decision maker (BP) indifferent between wind and solar generation.
〖EU〗_solar=P〖 [ 52.05]〗^(1/2)+(1-P) 〖[46.44]〗^(1/2)=7.016
〖EU〗_solar=7.21P+6.81-6.81P=7.016
0.4P=0.206
P=0.515
Therefore P = 51.5% and 1-P = 48.5%
As a result, when P > 51.5% solar generation will be preferred
When P < 51.5% wind generation will be preferred
The results show that if the probability of receiving subsidies for solar generation increases by more than 1.5%, BP would prefer to invest in solar technology as expected utility will be greater due to the impact of changing probability weightings.
The likelihood of such probability weightings occurring is debatable. With continuous investment being funded into renewable energy subsidies may continue. However currently, the UK aims to move towards a subsidy free renewable environment to reduce dependency of energy production. Such development would imply a reduction in the likelihood of receiving subsidies in general (Aurora Energy Research, 2018).
Conclusion
This report analysed and summarised the decisions of BP on whether to invest in solar or wind energy production, anticipating the uncertainty surrounding Brexit and subsidies.
Whilst undertaking the analysis we showed a variety of factors need to be taken in account particularly defining the decision maker and their risk preferences. Due to behavioural biases these may differ between a firm and depend on market optimism. Additionally, the probability weighting assigned to the likelihood of each event occurring also strongly affects the expected utility outcome.
Overall based on all calculations of the expected utility model, it would be suggested that considering the scale of production investment in wind energy is preferred due to less dependency on subsidies. This is because currently initial costs and maintenance costs are lower in monetary terms.
However, like many models’ limitations of the analysis can be recognised. Firstly, the model relies heavily on estimations of variables. For example, figures for profit and probabilities are all estimates and the exact figures are unknown. Furthermore, additional obdurate cost and benefits factors such as environmental impact or potential job prospects have not been considered. Factors like public perception and the impact on the local community could also be investigated into. This could impact the overall profit of each energy generation therefore widen the analysis. Finally, factors like climate change should be investigated into. With impacts on weather patterns the future effectiveness of both energy production could be under threat therefore affecting the expected utility.
3.11.2019