Download or read book Strategic Investment in Power Generation Under Uncertainty written by Diana Kudakwashe Chiyangwa and published by . This book was released on 2010 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this study is to develop a strategy for investment in power generation technologies in the future given the uncertainties in climate policy and fuel prices. First, such studies are commonly conducted using deterministic methods which assume a given likelihood of the carbon and gas price levels. In this study a probabilistic approach is used to address these uncertainties. Secondly, capacity expansion models conventionally apply average estimates to predict the amount of power that each generator will produce based on the technology chosen. I propose an alternate method which determines the actual generation hour-by-hour of a generator. Using this method, I also capture the variability of wind generation across the year. To accomplish this goal, I used the Electric Reliability Council of Texas (ERCOT) as a case study. I investigated the effect of different scenarios of generation technology investments projected over a period of twenty years. I conducted two sets of analysis; first assuming that Carbon Capture and Storage (CCS) technologies will be available after 2020, then assuming that they will not. Using a dispatch model, I simulated the hours of a load duration curve for 2020 and 2030. In the first period 2010-2020, I assumed the price of carbon to either be $0 or $50/ton CO2. In the second period, I take the carbon price to be at either a low of $25/ton of CO2 or a high of $100/ton of CO2 . The price of natural gas used was either a high of $15/MMBtu or a low of $3/MMBtu in both periods. Using a Monte Carlo, I sample the wind generation based on the season and the time of day. The system costs with the new investment scenarios were then evaluated in a decision tree to establish the socially optimal solution. I find that the optimal strategy to be taken today depends on the availability of CCS technologies in 2030. Assuming that there is CCS in 2030, the more dominant strategy would be to build natural gas generators today. If we assume that there is no CCS in 2030, the strategy would depend on the probabilities of the levels of gas and carbon prices in 2020.
Download or read book Strategic Power Plant Investment Planning Under Fuel and Carbon Price Uncertainty written by Ansgar Geiger and published by KIT Scientific Publishing. This book was released on 2014-08-20 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The profitability of power plant investments depends strongly on uncertain fuel and carbon prices. In this doctoral thesis, we combine fundamental electricity market models with stochastic dynamic programming to evaluate power plant investments under uncertainty. The application of interpolation-based stochastic dynamic programming and approximate dynamic programming allows us to consider a greater variety of stochastic fuel and carbon price scenarios compared to other approaches.
Download or read book Optimal Investment Strategies in Decentralized Renewable Power Generation Under Uncertainty written by Stein-Erik Fleten and published by . This book was released on 2012 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper presents a method for evaluation of investments in decentralized renewable power generation under price uncertainty. The analysis is applicable for a building owner with an electricity load and a renewable resource that can be utilized for power generation. The owner of the building has a deferrable opportunity to invest in one local power generating unit, with the objective to maximize the profits from the opportunity. Renewable electricity generation can serve local load when generation and load coincide in time, and surplus power can be exported to the grid. The problem is to find the price intervals and the capacity of the generator at which to invest. Results from a case with wind power generation for an office building suggests it is optimal to wait for higher prices than the net present value break-even price under price uncertainty, and that capacity choice can depend on the current market price and the price volatility. With low price volatility there can be more than one investment price interval for different units with intermediate waiting regions between them. High price volatility increases the value of the investment opportunity, and therefore, makes it more attractive to postpone investment until larger units are profitable.
Download or read book Investment in Electricity Generation and Transmission written by Antonio J. Conejo and published by Springer. This book was released on 2016-06-10 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an in-depth analysis of investment problems pertaining to electric energy infrastructure, including both generation and transmission facilities. The analysis encompasses decision-making tools for expansion planning, reinforcement, and the selection and timing of investment options. In this regard, the book provides an up-to-date description of analytical tools to address challenging investment questions such as: How can we expand and/or reinforce our aging electricity transmission infrastructure? How can we expand the transmission network of a given region to integrate significant amounts of renewable generation? How can we expand generation facilities to achieve a low-carbon electricity production system? How can we expand the generation system while ensuring appropriate levels of flexibility to accommodate both demand-related and production-related uncertainties? How can we choose among alternative production facilities? What is the right time to invest in a given production or transmission facility? Written in a tutorial style and modular format, the book includes a wealth of illustrative examples to facilitate comprehension. It is intended for advanced undergraduate and graduate students in the fields of electric energy systems, operations research, management science, and economics. Practitioners in the electric energy sector will also benefit from the concepts and techniques presented here.
Download or read book Strategic Power Plant Investment Planning Under Fuel and Carbon Price Uncertainty written by Ansgar Geiger and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Technology Investment Decisions Under Uncertainty written by Nidhi Santen and published by . This book was released on 2013 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Effectively balancing existing technology adoption and new technology development is critical for successfully managing carbon dioxide (CO2) emissions from the fossil-dominated electric power generation sector. The long infrastructure lifetimes of power plant investments mean that deployment decisions made today will influence carbon dioxide emissions long into the future. New technology development and R&D decisions can help reduce the overall costs of reducing emissions, but there are multiple technology investments to choose from, and returns to R&D are inherently uncertain. These features of the technology "deployment versus development" question create unique challenges for decision makers charged with managing cumulative carbon dioxide emissions from the electricity sector. Unfortunately, current quantitative decision support tools ultimately lack one or more of three overarching features jointly necessary to provide useful insights about an optimal balance between R&D program and power plant investments. They lack (1) resolution of the critical structure of the electricity sector, (2) an explicit endogenous representation of the effects of learning-by-searching technological change, and/or (3) an efficient decision-analytic framework to explore multiple technology investment options under uncertainty in the returns to R&D. This dissertation presents a new quantitative decision support framework that allows for the study of socially optimal R&D and capital investment decisions for the power generation sector. Through a novel integration of classical electricity generation investment planning methods, economic modeling of endogenous R&D-driven technological change, and emerging numerical stochastic optimization techniques, the new framework (1) explicitly accounts for the complementary roles that generating technologies play within the electric power system, (2) considers the characteristics of the uncertainty in the technology innovation process, and (3) identifies flexible, adaptive R&D investment strategies for multiple technologies for decision makers to consider. A series of numerical experiments with the new model reveal that (1) the optimal near-term R&D investment strategy under technological change uncertainty and adapting between decisions can be different than the optimal strategy assuming perfect foresight, and may be higher or lower; (2) the timing that a technology should be deployed to meet a specific carbon target dictates the direction and magnitude of the difference in these decisions; (3) increasing the level of uncertainty tends to increase near-term R&D investments; and (4) increasing right-skewness of the uncertainty (i.e., decreasing the likelihood of higher than average returns), reduces R&D spending throughout the planning horizon.
Download or read book Long Term Infrastructure Investments Under Uncertainty in the Electric Power Sector Using Approximate Dynamic Programming Techniques written by Michael Seelhof and published by . This book was released on 2014 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: A computer model was developed to find optimal long-term investment strategies for the electric power sector under uncertainty with respect to future regulatory regimes and market conditions. The model is based on a multi-stage problem formulation and uses approximate dynamic programming techniques to find an optimal solution. The model was tested under various scenarios. The model results were analyzed with regards to the optimal first-stage investment decision, the final technology mix, total costs, the cost of ignoring uncertainty and the cost of regulatory uncertainty.
Download or read book Real Options and Investment Under Uncertainty written by Eduardo S. Schwartz and published by MIT Press. This book was released on 2004 with total page 890 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of investment under uncertainty was stagnant for several decades until developments in real options revitalized the field. The topics covered in this book include the reasons behind the under-investment programme.
Download or read book Investment Under Uncertainty in Electricity Generation written by Klaus Gugler and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Electricity Generation and Emissions Reduction Decisions Under Uncertainty written by Jennifer Faye Morris and published by . This book was released on 2013 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: The electric power sector, which accounts for approximately 40% of U.S. carbon dioxide emissions, will be a critical component of any policy the U.S. government pursues to confront climate change. In the context of uncertainty in future policy limiting emissions, society faces the following question: What should the electricity mix we build in the next decade look like? We can continue to focus on conventional generation or invest in low-carbon technologies. There is no obvious answer without explicitly considering the risks created by uncertainty. This research investigates socially optimal near-term electricity investment decisions under uncertainty in future policy. It employs a novel framework that models decision-making under uncertainty with learning in an economy-wide setting that can measure social welfare impacts. Specifically, a computable general equilibrium (CGE) model of the U.S. is formulated as a two-stage stochastic dynamic program focused on decisions in the electric power sector. In modeling decision-making under uncertainty, an optimal electricity investment hedging strategy is identified. Given the experimental design, the optimal hedging strategy reduces the expected policy costs by over 50% compared to a strategy derived using the expected value for the uncertain parameter; and by 12-400% compared to strategies developed under a perfect foresight or myopic framework. This research also shows that uncertainty has a cost, beyond the cost of meeting a policy. Results show that uncertainty about the future policy increases the expected cost of policy by over 45%. If political consensus can be reached and the climate science uncertainties resolved, setting clear, long-term policies can minimize expected policy costs. Ultimately, this work demonstrates that near-term investments in low-carbon technologies should be greater than what would be justified to meet near-term goals alone. Near-term low-carbon investments can lower the expected cost of future policy by developing a less carbon-intensive electricity mix, spreading the burden of emissions reductions over time, and helping to overcome technology expansion rate constraints--all of which provide future flexibility in meeting a policy. The additional near-term cost of low-carbon investments is justified by the future flexibility that such investments create. The value of this flexibility is only explicitly considered in the context of decision-making under uncertainty.
Download or read book Clean Energy Investments in an Uncertain Future written by Jessica Kit Harrison and published by . This book was released on 2005 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: (Cont.) Ultimately, it suggests a framework for considering the problem of clean energy investments under uncertainty. It considers a real options approach and system dynamics, despite their limitations, as a start for developing sophisticated tools to help grapple with investment uncertainties and to create thoughtful, strategic plans.
Download or read book Strategic Investment written by Han T. J. Smit and published by Princeton University Press. This book was released on 2012-01-12 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Corporate finance and corporate strategy have long been seen as different sides of the same coin. Though both focus on the same broad problem, investment decision-making, the gap between the two sides--and between theory and practice--remains embarrassingly large. This book synthesizes cutting-edge developments in corporate finance and related fields--in particular, real options and game theory--to help bridge this gap. In clear, straightforward exposition and through numerous examples and applications from various industries, Han Smit and Lenos Trigeorgis set forth an extended valuation framework for competitive strategies. The book follows a problem-solving approach that synthesizes ideas from game theory, real options, and strategy. Thinking in terms of options-games can help managers address questions such as: When is it best to invest early to preempt competitive entry, and when to wait? Should a firm compete in R&D or adopt an accommodating stance? How does one value growth options or infrastructure investments? The authors provide a wide range of valuation examples, such as acquisition strategies, R&D investment in high-tech sectors, joint research ventures, product introductions in consumer electronics, infrastructure, and oil exploration investment. Representing a major step beyond standard real options or strategy analysis, and extending the power of real options and strategic thinking in a rigorous fashion, Strategic Investment will be an indispensable guide and resource for corporate managers, MBA students, and academics alike.
Download or read book Dynamic Decision Making Under Uncertainty in Renewable Energy Portfolio Management and Inventory Management written by Jianjun Deng and published by . This book was released on 2012 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: "It is challenging and important for a firm to make effective decisions under uncertainties, such as random fluctuations of products prices or demands, etc. This dissertation formulates mathematic models to help decision makers in energy and retail industries make optimal timing and optimal operational decisions when facing uncertain electricity prices and demands. As for energy portfolio management, the optimal entry and dispatch strategies are investigated for an electricity generating firm to introduce a renewable power plant as an alternative method for generating electricity, with or without construction delay. In addition, the abandonment strategies of considering shutting down one of the two power plants in the energy portfolio are studied. To develop these strategies, the expected per unit profit is maximized over a finite time horizon by assuming that the price of electricity follows mean reversion stochastic process. This problem is formulated as a mixed optimal stochastic control and optimal stopping problem. The original problem is solved numerically through two auxiliary problems. Numerical experiments are conducted to confirm the results. The sensitivity analysis of the parameters is conducted to reveal how the uncertainty of electricity price, investment, operation cost, and production rate affect the decisions. A dynamic inventory model is also developed to study optimal control policy in a finite planning horizon with consideration of debt financing and tax. The model assumes that the retailer raises funds from the financial market and replenishes its stock under the constraint of its cash flow facing random demand. The objective is to maximize the expected terminal wealth. The optimal inventory policy and the optimal debt financing decision with the capital constraint and the effect of tax are obtained"--Abstract, leaf iii.
Download or read book Hedging Strategies written by and published by . This book was released on 2018 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given uncertainty in long-term carbon reduction goals, how much non-carbon generation should be developed in the near-term? This research investigates the optimal balance between the risk of overinvesting in non-carbon sources that are ultimately not needed and the risk of underinvesting in non-carbon sources and subsequently needing to reduce carbon emissions dramatically. We employ a novel framework that incorporates a computable general equilibrium (CGE) model of the U.S. into a two-stage stochastic approximate dynamic program (ADP) focused on decisions in the electric power sector. We solve the model using an ADP algorithm that is computationally tractable while exploring the decisions and sampling the uncertain carbon limits from continuous distributions. The results of the model demonstrate that an optimal hedge is in the direction of more non-carbon investment in the near-term, in the range of 20-30% of new generation. We also demonstrate that the optimal share of non-carbon generation is increasing in the variance of the uncertainty about the long-term carbon targets, and that with greater uncertainty in the future policy regime, a balanced portfolio of non-carbon, natural gas, and coal generation is desirable.
Download or read book Investment under Uncertainty written by Robert K. Dixit and published by Princeton University Press. This book was released on 2012-07-14 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: How should firms decide whether and when to invest in new capital equipment, additions to their workforce, or the development of new products? Why have traditional economic models of investment failed to explain the behavior of investment spending in the United States and other countries? In this book, Avinash Dixit and Robert Pindyck provide the first detailed exposition of a new theoretical approach to the capital investment decisions of firms, stressing the irreversibility of most investment decisions, and the ongoing uncertainty of the economic environment in which these decisions are made. In so doing, they answer important questions about investment decisions and the behavior of investment spending. This new approach to investment recognizes the option value of waiting for better (but never complete) information. It exploits an analogy with the theory of options in financial markets, which permits a much richer dynamic framework than was possible with the traditional theory of investment. The authors present the new theory in a clear and systematic way, and consolidate, synthesize, and extend the various strands of research that have come out of the theory. Their book shows the importance of the theory for understanding investment behavior of firms; develops the implications of this theory for industry dynamics and for government policy concerning investment; and shows how the theory can be applied to specific industries and to a wide variety of business problems.
Download or read book The Low carbon Transition of the European Electricity Sector written by Elsa Barazza and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2015 Paris Agreement seeks to limit global temperature increase to well below 2°C above pre-industrialised levels before the end of the century. To achieve this ambitious target the electricity sector needs to be decarbonised. This low-carbon transition requires substantial financial flows, and a re-allocation of capital towards low-carbon investments. However, clean-energy investments in Europe are declining, and a diversified investors landscape is becoming increasingly important to bridge the financing-gap, as strong financial pressures threaten incumbent utilities" role as investors. In order to support private sector actors" low-carbon investments, and prevent the lock-in of existing high carbon technologies, effective policies are needed, which acknowledge the heterogeneity and different micro-economic decisions of private sector actors. This research develops an agent-based model called BRAIN-Energy (Bounded Rationality Agents INvestments) which analyses the strategic investment decisions in power generation assets of different market players with bounded-rationality, and the effects of their myopic and path-dependent choices and their interactions on the long-run evolution of the electricity sector to 2050. BRAIN-Energy aims to address a gap in existing energy-modelling literature, where most studies assume homogeneous and perfectly rational agents, and lack attention to the actors" heterogeneity and bounded-rationality. Case studies are the UK, the German and the Italian electricity markets. Results from BRAIN-Energy show how conducive conditions for an effective allocation of investments between low-carbon and conventional generation technologies are determined by the interplay of the government"s and the market players" strategies. Moreover, BRAIN-Energy shows how an electricity sector with heterogeneous actors requires a stronger CO2 price to be decarbonised, which should be supported by frequent carbon budgets to be effective. Results also show how market players" heterogeneity and bounded-rationality create barriers to climate change mitigation efforts, by affecting the scenarios environmental performance and political dimension, especially when government intervention is lower. Hence, assuming rational and homogeneous agents in energy system models could lead to ineffective policies for energy transitions.
Download or read book Using Probabilistic Analysis to Value Power Generation Investments Under Uncertainty written by Fabien A. Roques and published by . This book was released on 2006 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt:
