Real Options Analysis on Valuation of Wind Farm in Colombia

Transcription

1 Real Options Analysis on Valuation of Wind Farm in Colombia Luis M. Jiménez 1, Natalia M. Acevedo 2, Erick Lambis 3 1,2,,3 Instituto Tecnológico Metropolitano ITM, Universidad Nacional de Colombia. Abstract Real Options Analysis (ROA) is an advanced valuation method that allows decision makers to take advantage of market opportunities, if future conditions evolve favorably. Investors should value the flexibility to change decisions as uncertainty develops. The main objective of this study is to evaluate a nonconventional renewable energy project in Colombia through ROA and traditional methodologies. Investments in electricity generation projects with wind sources are subject to irreversibility and uncertainty. This study applies this valuation technique in a wind farm in Colombia with the option to postpone the investment, the real option was assessed by the binomial tree method and Monte Carlo simulation was used to determine the volatility of the project. The results show that the valuation of the wind farm by traditional methods such as the Net Present Value the project is rejected and the investment would not be recommended. However, when introducing the price of energy as a variable of uncertainty and applying the ROA method, the project would not be rejected, the decision would be to defer the investment until the market conditions are favorable. Keywords: Real options Analysis, Uncertainty, Flexibility wind farm, energy price INTRODUCTION In uncertain environments, managerial flexibility in projects has significant economic value. Methods were developed that recognize the monetary value of the options incorporated in the investment opportunities, among the methods the one of real options stands out or also called ROA (Real Options Analysis). The ROA is an adaptation of the financial option method applied to the valuation of physical or real assets, evaluates the implicit value of managerial flexibility in investment projects, so the real options theory is an extension of option pricing theory [1] [3]. Managerial flexibility refers to the fact that investment plans are modified or deferred in response to the arrival of new information or until uncertainty is resolved. Thus, the project management takes advantage of new opportunities mitigating and preventing losses. On the other hand, the energy sector, since 1970, it presents regulatory and technological changes. In this new context, traditional valuation methods projects are no longer sufficient to adequately evaluate investments in this sector. In fact, this sector has gone from a regulated and monopolistic sector to a liberalized, uncertain and highly competitive sector [4]. Energy generation investment projects are characterized because they are irreversible investments because the capital of the industry cannot be used in other sectors or by different companies [5]. Furthermore, investors should evaluate options under uncertainty associated with the liberalized electricity market [6]. Finally, the investment is flexible over time, in other words, can invest today or postpone the decision in order to obtain better information. In consecuense, in the valuation of these projects, methodologies must be adopted that take into account the risks and uncertainties with respect to the investment [7]. In Colombia, the generation of energy is 80.61% hydraulic capacity, followed by thermal sources, 19.25%, and other sources with a proportion of 4.53%. Wind energy represents 0.14% of installed capacity. These data reflect the lack of diversification of energy sources. The main reason for the low representation of wind energy is due to the costs of this technology, which are higher than those of conventional technologies, despite the abundant wind in some areas [8]. Moreover, diversifying Colombia's energy market would provide greater security and mitigate the risk of scarcity of the water resource that has the highest proportion in generation. In this order of ideas, assess wind farms in Colombia by methodologies that quantify the uncertainty of the sector is appropriate to determine economic viability of these projects, which contributes (1) Increased reliability in the electric sector, (2) increase participation unconventional renewable sources, (3) reduction of fossil fuel consumption y (4) decrease of gas emission. The main objective of this study is to evaluate a nonconventional renewable energy project in Colombia through ROA and traditional methodologies. The article proceeds as follows: first the antecedents related to the application of the Real Options on energy projects are presented, then, the real options method is presented starting from the financial options method and then the case study of the wind farm is shown. the case study will analyze an investment in a wind farm by traditional methods; finally, the ROA is applied, considering the price of energy in the stock market as the variable of uncertainty. A. Background We highlight some studies that applied the methodology of real options in renewable energy projects. Davis y Owens [9], they estimated the value of a real option in wind energy projects by adding to the model the uncertain variable of the price of fossil fuels. Zhou [10], they combined the wind speed and the distribution of the price of electricity to determine the revenues in a wind farm, through real options valuation. Dykes y De Neufville [11], they compared investments in large wind farms with investments in small wind farms with a real growth option and the price of electricity as an uncertain variable. Kumbaroglu, Madlener y Demirel [12], propose a policy planning model through real options, considering costs in 6433

2 renewable energy projects, availability factor, capacity factor, learning rate, and construction times. Martínez-Ceseña y Mutale [13], propose an advanced model of real options in the planning of renewable energy generation projects with the comparison of case studies of hydroelectric energy projects. Muñoz, Contreras, Caamano y Correia [14], they used the real options approach in the evaluation of wind farm investment decisions based on the uncertainty of the price of electricity. Santos [7] valued a hydroelectric project with real options and made a comparison between traditional valuation methods and the real options method, conclude that these types of projects are rejected by traditional methods, but when assessing flexibility with real options, they are accepted. Also, Lee [15], assesses on a wind power project with real options, analyzing the impact of the input variables for the construction of the binomial tree on the value of the project. On the other hand, [2] conducted a review of the literature on the valuation of energy projects with real options, the time window was from 1987 to the study classified the documents found per year, by application in the energy sector and method of solution. Determined that there is an increase in academic interest in the implementation of real options in decision making in the electricity sector. REAL OPTIONS For a better understanding of the theory of real options, it is important to introduce the concepts of financial options and then the definition of Real Options. A. Financial options A financial option is a security grants the right to buy or sell an asset, subject to certain conditions, an agreed price and within certain time. The options represent a right, whether to buy or sell, therefore, the performance of an option can never be less than zero, regardless of the underlying asset. There are two types of basic options, those that grant the right to buy an asset at an agreed price in a specific period, they are commonly called call options, the options that grant the right to sell an asset in exchange for receiving a price agreed in a specific period are called put options. The agreed price is called the exercise price [2]. The options can be European or American. When the option can only be exercised at a certain future date, that option is designated as a European option. On the other hand, when the option allows exercise at any time until the expiration date, it is an American option. The numerical method for valuing American options is through the binomial tree developed by Cox, Ross y Rubinstein in According to this method, you value the option when deciding if it is more beneficial to exercise the option or wait until the expiration date, at each instant in time. This model assumes that the expiration date of the option can be divided into discrete periods, whose dimension is represented by T. The price of the underlying asset is subject to a given behavior and is multiplied by the coefficient of ascent u or coefficient of decrease d, in each period or T, these coefficients depend on the standard deviation of the underlying asset and the periods, that is, it depends on σ and ΔT. These two movements of the price are the same for all nodes of the binomial tree. This reflects the favorable or unfavorable market conditions [16]. Figure 1 shows a binomial tree for the price of the underlying asset. Figure 1. Evolution of the price of the underlying asset in the binomial tree. 6434

3 The coefficient of ascent (u) and descent (d) are given by equations 1 and 2. u = e σ T [1] d = e σ T [2] The probability that the price of the underlying asset goes up or down is given by the theory of risk neutral probabilities. Thus, increases or decreases in price have a probability of increase p and decrease q (see equations 3 and 4). p = (e r T d) (μ d) [3] q = 1 p [4] After determining these parameters, the option value was obtained using a binomial tree. The binomial tree represents the profit obtained by the price of the underlying asset. In the case of a call option, this value is given by the maximum difference between the value of the asset (S) and the exercise price (K), and zero, max(s K; 0). In the case of a put option, the value corresponds to the maximum difference between the exercise price (K) and the price of the asset (S), and zero, max(k S; 0). From the values of the option on the nodes on the right of the tree, the value of the other nodes is determined by applying the neutral probabilities to the risk in each pair of vertically adjacent values [16]. Mathematically it is represented by equation 5. C t = [pc u t+1 + (1 p)c d t+1 ]e r T [5] When the price of the underlying asset is determined by this method, the binomial tree is built from left to right, different trajectories followed for the price are obtained until reaching the nodes of the expiration date of the option. As for the value of the option, a route from right to left is adopted, based on the prices defined in each node. B. Taxonomy of real options Real options are a conceptual extension of the theory of financial options applied to real or physical assets. A financial option is a security that gives the holder a right, but not an obligation, to buy (or sell) a financial asset in a certain period of time, in exchange for a certain amount of money. Similarly, a real option gives its holder the right, but not the obligation, to take a part that affects a real physical asset, at a previously determined cost during a pre-established time, in other words, a company that makes investments has the right, but not the obligation, to take advantage of opportunities that arise in the future. Thus, an investment opportunity can be considered as a source of cash flow, plus a set of options in exchange for an initial outlay. These opportunities are what give you flexibility in investments [3], [7]. An investment opportunity is similar to a call option. If a company with an opportunity to invest, has the option to spend money (exercise price) in exchange for a real physical asset (machinery, land, buildings, among others), the company would invest if it receives a positive net payment, ie, exercise the real option. Otherwise, the company would not invest to avoid negative profitability, the option is not exercised [2]. Depending on the nature of the real options that are applied to investment projects, the real options are classified into four categories: option to defer, option to modify the operation scale, option to leave and option to switch. Accordingly, a real option is the right, not the obligation, to defer, abandon, or adjust a project in response to the evolution of uncertainty. A real option is any action that the project administration can use to modify the original project plan. So the project is flexible if it can be deferring, abandoned, or resized. The objective of flexibility is to maximize profitability or minimize losses in different scenarios. Flexibility increases the expected value of the project [17]. In this paper the option to defer on investment is applied in a wind farm in Colombia C. Option to defer The option of postponing gives the holder the ability to wait to invest in the project. This means investing now or waiting to get more information about the investment. The option to defer is similar to a call option on the present value of the cash flows expected from the project and exercise price equal to the cost of investing in the project. The option to defer investment in the project acts as an opportunity cost, comparing the anticipated realization of the project with the value of not doing it and waiting until the market conditions favor the investment [18]. Case study: application of the methodology of the real options to a wind power generation project. The project under study is valued by traditional methods and by the real options method by implementing an option to defer. Cash flow discount methods such as VPN and IRR are used in the valuation of a wind farm in Colombia, then, the flexibility of postponing the investment is considered, postponing the investment until favorable conditions are obtained and the project generates economic benefits, that is, until economic viability is achieved. A wind power generation project located in the La Guajira region of Colombia is stipulated for its wind potential [19]. The installed capacity of the project is 100 Megawatts (MW). The cash flow projection is 15 years, approximate life time of the wind turbines and time granted by the Colombian government of exempt income for this type of projects (Decreto 2755 del 2003 del Ministerio de Hacienda y Crédito Público, 2003). La tasa de descuento para estos proyectos en Colombia es de 14,37% [20]. The US Department of Energy, through the EIA (U.S. Energy Information Administration), provides data for the projection of cash flow, as shown in table

4 Table 1. Data for cash flow projection [21]. O & M fixed costs $ (USD/kW-año) Nominal capacity 100 MW Wind turbine capacity 1.5 MW Costs for a nominal capacity of 100 MW, in thousands Civil works and installation $ 26,640,000 USD Mechanical distribution and installation equipment $ 132,946,000 USD Electrical distribution and installation $ 28,683,000 USD Indirect costs of the project $ 8,393,000 USD EPC costs (Engineering, Purchase and Construction) before incidentals and fees $ 196,662,000 USD Contingencies $ 12,007,000 USD Total cost of the project for 100 MW $ 208,669,000 USD Without considering flexibility in the execution of the wind farm, the present value of the cash flows of the project is USD 145,662,234, that with an initial investment of USD 208,669,000, the project's NPV is negative, - USD 63,006,766, in this way, the project is rejected. The same is confirmed by the project IRR of 7.82%, lower than the discount rate of 14.37%. However, the project is accepted by evaluating it by the real options method, as described below. The flexibility considered in the project is to invest only until the market conditions are favorable, the term to consider this option is five years, the time to expiration of the option is five years. Thus, the project is valued with the real option of deferring valued by the binomial tree method with five steps. Likewise, two assumptions are taken into account. First, all the data provided by traditional project evaluation methods is considered. Second, operating costs are not affected by high levels of uncertainty. Similarly, uncertainties such as technological innovations were not considered. Therefore, the only factor of uncertainty is the volatility of electricity prices. The prices considered in this study were the electricity prices of long-term contracts taken from the Derivex - Commodities Energy Derivatives Market, with data for a period of 12 years ( ). The stochastic variable that was taken for the project is the price of energy in the stock market. For the projection of this variable the mean and standard deviation of the log changes in the price of electricity was removed and a simulation was performed assuming the price behaves according to a stochastic process or geometric Brownian motion. The mean and standard deviation of the yields were 15.61% and 21.90%, respectively, with an annual continuous composition. With the above data and project cash flow projection, a Monte Carlo simulation with 10,000 iterations was performed to calculate the volatility of the project. The results showed a standard deviation of 60.28% of the cash flows, which corresponds to the volatility of the project. The deferred option applied in the paper corresponds to an American call option, in which the investment decision is now made if the present value of the cash flows of the project is greater than the value of the deferred option. These options are usually valued through the binominal tree, developed by Cox, Ross and Rubinstein. The parameters used to construct the tree are presented in table 2. VARIABLE Table 2. Parameters of the binomial tree. VALUE Present value cash flows (S) [USD] 145,662,234 Exercise price (K) [USD] 208,669,000 Expiration time real option [años] 5 Volatility cash flows (σ) 60.28% Risk-free rate (Rf) 6.67% Number of steps (n) 5 ΔT 1 u d p The tree in figure 2 shows the possible evolution of the price of the underlying asset and the value of the deferred option, from left to right. As for the underlying asset, the value presented in the first node of the tree is the current price of the underlying asset, that is, the present value of the cash flows of the wind farm. The price can increase or decrease depending on the coefficients u and d, respectively. The last column of the binomial tree represents the possible values of the underlying asset on the expiration date of the option to defer. 6436

5 Figure 2. Binomial tree of the project. Because the option to defer is similar to a call option, the last values of the tree are determined by subtracting the values of the underlying asset with the exercise price. The result fluctuates between S - K and 0. The other values are determined by the application of neutral risk probabilities in each pair of values of the underlying asset vertically. The value of the option to defer investment is $ 71,844,901, which is higher than the VPN without flexibility, which takes negative (- USD 63,006,766). So the new VPN project, VPN with flexibility, is USD 8,838,165. The value of the option to defer is greater than the value of investing immediately. The project must be postponed until more favorable investment conditions appear. Because investment decisions are subject to the opportunity cost of deferring the decision, the investment must be made only when the NPV is greater than the value of the option to defer. This is because investing now involves a loss of opportunity to invest further in time, which corresponds to the delay value of the option. In consecuense, the value generated by the project could not cover the investment, but it must be high enough to cover the option to defer. The application of these assumptions in the tree is shown in the decision tree of figure 3, which shows the decision to invest or postpone the project, at each moment in time. Figure 3. Decision tree. 6437

6 The decision tree in figure 3 shows that the option to invest is better when the underlying asset reaches the highest values. If the underlying asset has lower values, then the option to postpone the project for the next period is the best option. In other words, it will only be invested if the evaluation of the remuneration of the energy exceeds the investment and opportunity costs of not postponing the project. The decision to invest in the wind farm is postponed to obtain more information in order to reduce the uncertainty of the project. The decision tree shows that the project will be postponed since the value of the option to defer is higher and converts the VPN into positive values. However, in the last year, the investor must determine if there are favorable conditions to invest or not, because the option to postpone the project will no longer be available, it will arrive at the expiration date. In this case, the investor will only invest if the price of electricity is high enough. In general, the application of the real options methodology gives the investor more flexibility to re-evaluate the project and redefine the strategy. The VPN method does not take flexibility into account; it underestimates the value of the project. Consequently, the incorporation of real options increases the net present value of the project. CONCLUSIONS This study evaluates a wind energy project through the application of real options. The main characteristics and the uncertainties of this type of investments are identified, which justifies the use of real options together with traditional methods. Through the application of real options, project management can analyze market conditions as information is obtained and uncertainty is reduced. This obtaining of more complete and realistic information, allows to avoid losses and obtain greater profits of the project during the five years of evaluation. In addition, the case study is not profitable because it has a negative VPN, which shows that an analysis based on the traditional NPV is not enough. On the other hand, it should be noted that small unfavorable changes in project yields could jeopardize viability. On the other hand, the review of the literature shows that due to the high degree of uncertainty, methods for evaluation in energy investment projects are applied. So the decision should not be limited to the determination to invest now or never. In fact, some degree of management flexibility must be included. Traditional methods of project evaluation, such as VPN and IRR, do not allow an investor to define the optimal time to invest or to estimate the real value of the project's uncertainties. However, the methodology of the real options is used to evaluate real assets that considers the flexibility in the management during the life of the project. Also, when considering new information and the uncertainties are resolved, the project management can make decisions that positively influence the final value of the project. Therefore, real options maximize profits in favorable situations and minimize losses in unfavorable ones. None of the evaluation methods is considered absolute. However, this does not mean that there is no need to look for evaluation methods that take into account the characteristics of the investment, uncertainties and flexibility in the management. Although real options are a difficult and uncommon method for companies, it is the most current and appropriate method to apply to issues related to uncertainty. Therefore, if an analysis takes uncertainty into account over time and includes real options in the project, the decision-making process will be more realistic. As future work, modeling the price of energy with models with jumps and with a reversion to the average could be considered. These models are more approximate to the behavior of the variable. Also, other valuation methods of options such as the Black-Scholes method and Monte Carlo simulation could be considered. REFERENCES [1] M. Amram and N. Kulatilaka, Real Options - Managing Strategic Investment in an Uncertain World. Boston, [2] B. Fernandes, J. Cunha, and P. Ferreira, The use of real options approach in energy sector investments, Renew. Sustain. Energy Rev., vol. 15, no. 9, pp , [3] R. Pringles, F. Olsina, and F. Garcés, Real option valuation of power transmission investments by stochastic simulation, Energy Econ., vol. 47, pp , [4] S. Awerbuch, J. Dillard, T. Mouck, and A. Preston, apital budgeting, technological innovation and the emerging competitive environment of the electric power industry, Energy Policy, vol. 24, p , [5] A. Menegaki, Valuation for renewable energy: A comparative review, Renew. Sustain. Energy Rev., vol. 12, no. 9, pp , [6] R. Haas, C. Panzer, G. Resch, M. Ragwitz, G. Reece, and A. Held, A historical review of promotion strategies for electricity from renewable energy sources in EU countries., Renew. Sustain. Energy Rev., vol. 15, pp , [7] L. Santos, I. Soares, C. Mendes, and P. Ferreira, Real Options versus Traditional Methods to assess Renewable Energy Projects, Renew. Energy, vol. 68, pp , [8] J. Contreras and Y. E. Rodríguez, Incentives for wind power investment in Colombia, Renew. Energy, vol. 87, pp , [9] G. Davis and B. Owens, Optimizing the level of renewable electric R&D expenditures using real options analysis., Energ Policy, vol. 31, no. 15, pp ,

7 [10] H. Zhou, Y. Hou, Y. Wu, H. Yi, C. Mao, and G. Chen, Analytical assessment of wind power generation asset in restructured electricity industry. United Kingdom: Universities Power Engineering Conference, [11] K. Dykes and R. De Neufville, Real options for a wind farm in Wapakoneta, Ohio: incorporating uncertainty into economic feasibility studies for community wind., in World Wind Energy Conference, [12] G. Kumbaroglu, R. Madlener, and M. Demirel, A real options evaluation model for the diffusion prospects of new renewable power generation technologies, Energ Econ, vol. 4, pp , [13] E. Martínez-Ceseña and J. Mutale, Application of an advanced real options approach for renewable energy generation projects planning, Renew., Sustain Energy Rev, vol. 15, no. 4, pp , [14] J. Muñoz, J. Contreras, J. Caamano, and P. Correia, Risk assessment of wind power generation project investments based on real options., in Proceedings of IEEE PowerTech., [15] S.-C. Lee, Using real option analysis for highly uncertain technology investments: The case of wind energy technology, Renew. Sustain. Energy Rev., vol. 15, no. 9, pp , [16] J. Hull, Introducción a los mercados de futuros y opciones. México: Pearson Education, [17] E. A. Martínez Ceseña, J. Mutale, and F. Rivas- Dávalos, Real options theory applied to electricity generation projects: A review, Renew. Sustain. Energy Rev., vol. 19, pp , [18] J. Mascareñas, P. Lamothe, F. López Lubian, and W. De Luna, Opciones reales y valoración de activos. Madrid: Prentice Hall, [19] C. Maya Ochoa, J. D. Hernández Betancur, and Ó. M. Gallego Múnera, La valoración de proyectos de energía eólica en colombia bajo el enfoque de opciones reales., Cuad. Adm., vol. 25, no. 44, pp , [20] L. M. JIMENEZ, N. M. ACEVEDO, and M. D. ROJAS, Valoración de opción real en proyectos de generación de energía eólica en Colombia, Espacios, vol. 37, no. N o 26, [21] EIA, Updated Capital Cost Estimates for Utility Scale Electricity Generating Plants, Washington, DC, United States,