Similarly, we employ the developed valuation framework to value a peaking hydroelectric power plant. By considering an illustrative power plant operating in Ontario, we show effects of gas-imbalance on dispatch strategies on a daily cycling operation basis and the resulting impact on net revenue. Inability of a power generator to match its gas supply and consumption in real time, leading to unauthorized gas over-run or under-run, attracts penalty charges from the gas supplier to the extent that the generator can not manage the imbalance through other means. Natural gas markets in North America operate on a day-ahead basis while power plants are dispatched in real time. This source of uncertainty arises because of mismatch between natural gas and electricity wholesale markets. This work built on previously published real options valuation methodologies for gas-fired thermal power plants by factoring in uncertainty from gas supply/consumption imbalance which is usually faced by gas-fired power generators. The developed valuation framework was adapted for a gas-fired thermal power plant, a peaking hydroelectric power plant and a baseload power plant. The solution algorithm employed is the Least Squares Monte Carlo (LSM) method. The problem is then solved dynamically by decomposing it into a series of two-stage sub-problems according to Bellman's optimality principle. Specifically, the framework developed conceptualizes the operation of a power asset as a multi-stage decision making problem where the operator has to make a decision at every stage to alter operating mode given currently available information about key value drivers. The developed framework accounts for the uncertain nature of key value drivers by representing them with appropriate stochastic processes. As a current decision to switch operating modes may affect future operating flexibilities of the asset and hence cash flows, a dynamic optimization framework is employed. The modeling framework developed conceptualizes operating flexibilities of power assets as "switching options' whereby the asset operator decides at every decision point whether to switch from one operating mode to another mutually exclusive mode, within the limits of the equipment constraints of the asset. ![]() The valuation framework must also be able to capture the reality of power market rules and opportunities, as well as technical constraints of different assets. The goal is to develop a modeling framework that can be adapted to different energy assets with different types of operating flexibilities and technical constraints and which can be employed for various purposes such as capital budgeting, business planning, risk management and strategic bidding planning among others. The focus of this work is to develop a robust valuation framework for physical power assets operating in competitive markets such as peaking or mid-merit thermal power plants and baseload power plants.
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