Monte Carlo Valuation of natural gas investments

This paper deals with the valuation of energy assets related to natural gas. In particular, we evaluate a baseload Natural Gas Combined Cycle (NGCC) power plant and an ancillary instalation, namely a Liquefied Natural Gas (LNG) facility, in a realistic setting; specifically, these investments enjoy a long useful life but require some non-negligible time to build. Then we focus on the valuation of several investment options again in a realistic setting. These include the option to invest in the power plant when there is uncertainty concerning the initial outlay, or the option's time to maturity, or the cost of CO2 emission permits, or when there is a chance to double the plant size in the future. Our model comprises three sources of risk. We consider uncertain gas prices with regard to both the current level and the long-run equilibrium level; the current electricity price is also uncertain. They all are assumed to show mean reversion. The two-factor model for natural gas price is calibrated using data from NYMEX NG futures contracts. Also, we calibrate the one-factor model for electricity price using data from the Spanish wholesale electricity market, respectively. Then we use the estimated parameter values alongside actual physical parameters from a case study to value natural gas plants. Finally, the calibrated parameters are also used in a Monte Carlo simulation framework to evaluate several American-type options to invest in these energy assets. We accomplish this by following the least squares MC approach.real options, power plants, stochastic revenues and cost, CO2 allowances, LNG

Valuing Flexibility: The case of an Integrated Gasification Combined Cycle Power Plant

In this paper we analyze the valuation of options stemming from the flexibility in an Integrated Gasification Combined Cycle (IGCC) Power Plant. First we use as a base case the opportunity to invest in a Natural Gas Combined Cycle (NGCC) Power Plant, deriving the optimal investment rule as a function of fuel price and the remaining life of the right to invest. Additionally, the analytical solution for a perpetual option is obtained. Second, the valuation of an operating IGCC Power Plant is studied, with switching costs between states and a choice of the best operation mode. The valuation of this plant serves as a base to obtain the value of the option to delay an investment of this type. Finally, we derive the value of an opportunity to invest either in a NGCC or IGCC Power Plant, that is, to choose between an inflexible and a flexible technology, respectively. Numerical computations involve the use of one- and two-dimensional binomial lattices that support a mean-reverting process for the fuel prices. Basic parameter values refer to an actual IGCC power plant currently in operation.real options, power plants, flexibility, stochastic costs

Income risk of EU coal-fired power plants after Kyoto

Coal-fired power plants may enjoy a significant advantage relative to gas plants in terms of cheaper fuel cost. Still, this advantage may erode or even turn into disadvantage depending on CO2 emission allowance price. This price will presumably rise in both the Kyoto Protocol commitment period (2008-2012) and the first post-Kyoto years. Thus, in a carbon-constrained environment, coal plants face financial risks arising in their profit margins, which in turn hinge on their so-called "clean dark spread". These risks are further reinforced when the price of the output electricity is determined by natural gas-fired plants' marginal costs, which differ from coal plants' costs. We aim to assess the risks in coal plants' margins. We adopt parameter values estimated from empirical data. These in turn are derived from natural gas and electricity markets alongside the EU ETS market where emission allowances are traded. Monte Carlo simulation allows to compute the expected value and risk profile of coal-based electricity generation. We focus on the clean dark spread in both time periods under different future scenarios in the allowance market. Specifically, bottom 5% and 10% percentiles are derived. According to our results, certain future paths of the allowance price may impose significant risks on the clean dark spread obtained by coal plants.clean spark spread, clean dark spread, EU Emissions Trading Scheme, Monte Carlo

Optimal Abandonment of Coal-Fired Stations in the EU

Carbon-fired power plants could face some difficulties in a carbon-constrained world. The traditional advantage of coal as a cheaper fuel may decrease in the future if CO2 allowance prices start to increase. This paper seeks to answer empirically the most drastic question that an operating coal-fired power plant may ask itself: under what conditions would it be optimal to abandon the plant and obtain its salvage value? We try to assess this question from a financial viewpoint following a real option approach at firm level so as to attract the interest of utilities and the broader investment community. We consider the specific case of a coal-fired power plant that operates under restrictions on carbon dioxide emissions in an electricity market where gas-fired plants are considered as marginal units. We also consider three sources of uncertainty or stochastic variables: the coal price, the gas price and the emission allowance price. These parameters are derived from future markets and are used in a three-dimensional binomial lattice to assess the value of the option to abandon. Our results (and sensitivity analysis) show the conditions that have to be met for the abandonment option to be exercised. This option to abandon coalfired plants is, however, hardly likely to be exercised if plants can operate as peaking plants. However, the decision may go differently in different circumstances, such as high CO2 allowance prices, very low volatility of allowance price or a decrease in the price of gas. The decision is also influenced by the remaining lifetime of the plant and its thermal efficiency. In any case the price of CO2 will work to bring forward the decision to abandon in older and less efficient coal-fired plants, which are less likely to be retrofitted in the future.power plants, coal, natural gas, emission allowances, futures markets, stochastic processes, abandonment, real options

Optimal Investment in Energy Efficiency under Uncertainty

This paper deals with the optimal time to invest in an energy efficiency improvement. There is a broad consensus that such investments quickly pay for themselves in lower energy bills and spared emission allowances. However, investments that at first glance seem worthwhile are frequently not undertaken. Our aim is to shed some light on this issue. In particular, we try to assess these projects from a financial point of view so as to attract sufficient interest from the investment community. We consider the specific case of a firm or utility already in place that consumes huge amounts of coal and operates under restrictions on carbon dioxide emissions. In order to reduce both coal and carbon costs the firm may undertake an investment to enhance energy efficiency. We consider three sources of uncertainty: the fuel commodity price, the emission allowance price, and the overall investment cost. The parameters of the coal price process and the carbon price process are estimated from observed futures prices. The numerical parameter values are then used in a three-dimensional binomial lattice to assess the value of the option to invest. As usual, maximising this value involves determining the optimal exercise time. Thus we compute the trigger investment cost, i.e. the threshold level below which immediate investment would be optimal. A sensitivity analysis is also undertaken. Our results go some way towards explaining the so-called energy efficiency paradox.Energy efficiency, Real options

Climate change and heatwaves in the main coastal cities of the Basque Country

In this paper we analyse the probabilistic behaviour of heatwaves (HWs) in the main coastal cities of the Basque Country (Bayonne, Bilbao and Donostia-San Sebastian) in the twentyfirst century. We estimate HW behaviour using data from eight climate circulation models under two representative concentration pathways (RCP 8.5 and RCP 4.5). We model HWs according to three factors: number per annum, duration and intensity, including correlations, and find very different results for each climate model. This highlights the problem of using a single model. Under RCP 8.5, we find an expected mean excess over the 30C temperature threshold of 4.19C for Bayonne, 4.05C for Bilbao and 4.14C for Donostia-San Sebastian in 2100. These expected values are based on incomplete information, so we also calculate several risk measures. © 2020 Servicio Central Publicaciones. Gobierno vasco.This research is supported by the Basque Government through the BERC 2018-2021 programme and by the Spanish Ministry of the Economy and Competitiveness (MINECO) through BC3 Mar?a de Maeztu excellence accreditation MDM-2017-0714. Additionally, Luis M. Abadie gratefully acknowledges financial support from The Spanish Ministry of Science and Innovation (RTI2018-093352-B-I00). Marek Smid acknowledges the H2020 EU project COACCH-grant agreement N. 776479

Market-based valuation of transmission network expansion. A heuristic application in GB

Transmission investments are currently needed to meet an increasing electricity demand, to address security of supply concerns, and to reach carbon emissions targets. A key issue when assessing the benefits from an expanded grid concerns the valuation of the uncertain cash flows that result from the expansion. We develop a valuation model which combines optimization techniques, Monte Carlo simulation over the expansion project lifetime, and market data from futures contracts on commodities. The model allows for random failures in generation and transmission infrastructure. Uncertainty stems also from nodal loads, fuel prices, allowance prices, wind generation, and hydro generation. Thus the model accounts for the stochastic dynamics on both the demand side and the supply side. To demonstrate the model by example, we consider a simplified network with two nodes. It is intended to broadly resemble the power generation sectors in England/Wales and Scotland. We then focus on the proposed Western HVDC subsea link. We simulate the whole distribution of effects on system costs, carbon emissions, and unserved load

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Energy Market Prices in Times of COVID-19: The Case of Electricity and Natural Gas in Spain

The COVID-19 pandemic is having a strong impact on the economies of all countries, negatively affecting almost all sectors. This paper compares Spanish electricity and natural gas prices in the first half-year of 2020 with the prices expected for that period at the end of 2019. The half-year of 2020 selected coincides with the period of greatest impact of COVID-19 on Spanish society. Expected prices and their future probability distributions are calculated using a stochastic model with deterministic and stochastic parts; the stochastic part includes mean-reverting and jumps behaviour. The model is calibrated with 2016–2019 daily spot prices for electricity and with day-ahead prices for natural gas. The results show large monthly differences between the prices expected at the end of the year 2019 and the actual prices for the half-year; in May 2020, wholesale electricity prices are found to be EUR 31.60/MWh lower than expected, i.e., 60% lower. In the case of natural gas, the prices in the same month are EUR 8.96/MWh lower than expected, i.e., 62% lower. The spark spread (SS) is positive but lower than expected and also lower than in the same months of the previous year