Wind power investment in thermal system and emissions reduction

This paper presents an analytical model for wind power investment. Most generation planning problems are formulated in multiperiod mixed integer programming with cost minimization as objective. We try to resort to finance literature for models able to systematically characterize return and risk. Real option theory is chosen. A primitive function is defined for the fuel cost able to be saved as the revenue of a wind power project. Subsequently the real project is described as a contingent claim on the stochastic fuel prices. Theoretical valuation of the project is thus given by the solution of a partial differential equation derived by Ito lemma. This formulation avoids the ambiguity in analyzing wind power investment based on non-market-based tariffs, but focuses on the welfare to the system as a whole. Finally a hypothetical scenario of carbon emission price is included to demonstrate the incentive it could offer to renewable generation. ©2010 IEEE.published_or_final_versionThe IEEE Power and Energy Society (PES) General Meeting, Minneapolis, MN., 25-29 July 2010. In Proceedings of PES, 2010, p. 1-

Formulating hedging strategies for financial risk mitigation in competitive U.S. electricity markets

The challenges currently facing participants in the competitive electricity markets are unique and staggering: unprecedented price volatility, fluctuations in the demand, a lack of historical market data on which to test the new modeling approaches, increased competition and continuously changing regulatory structure...Electricity plant owners and purchasers of electricity may benefit from various techniques to manage price volatility. For electricity, however, no futures market is actively traded. The electricity forward market in NYMEX is in its nascent stage and is low in liquidity. Producers and purchasers of electricity may find cross-hedging electricity with natural gas futures contracts to be effective in reducing exposure to price volatility. The objective of this study is to estimate the cross-hedge relationship and strategies between spot electricity price and the NYMEX natural gas futures market for the cross-hedging horizon of one month --Introduction, page 10-11

Information requirements for strategic decision making: energy market

Over the last two decades, the electricity sector has been involved in a challenging restructuring process in which the vertical integrated structure (monopoly) is being replaced by a horizontal set of companies. The growing supply of electricity, flowing in response to free market pricing at the wellhead, led to increased competition. In the new framework of deregulation, what characterizes the electric industry is a commodity wholesale electricity marketplace. This new environment has drastically changed the objective of electricity producing companies. In the vertical integrated industry, utilities were forced to meet all the demand from customers living in a certain region at fixed rates. Then, the operation of the Generation Companies (GENCOs) was centralized and a single decision maker allocated the energy services by minimizing total production costs. Nowadays, GENCOs are involved not only in the electricity market but also in additional markets such as fuel markets or environmental markets. A gas or coal producer may have fuel contracts that define the production limit over a time horizon. Therefore, producers must observe this price levels in these other markets. This is a lesson we learned from the Electricity Crisis in California. The Californian market\u27s collapse was not the result of market decentralization but it was triggered by other decisions, such as high natural gas prices, with a direct impact in the supply-demand chain. This dissertation supports generation asset business decisions -from fuel supply concerns to wholesale trading in energy and ancillary services. The forces influencing the value chain are changing rapidly, and can become highly controversial. Through this report, the author brings an integrated and objective perspective, providing a forum to identify and address common planning and operational needs. The purpose of this dissertation is to present theories and ideas that can be applied directly in algorithms to make GENCOs decisions more efficient. This will decompose the problem into independent subproblems for each time interval. This is preferred because building a complete model in one time is practically impossible. The diverse scope of this report is unified by the importance of each topic to understanding or enhancing the profitability of generation assets. Studies of top strategic issues will assess directly the promise and limits to profitability of energy trading. Studies of ancillary services will permit companies to realistically gauge the profitability of different services, and develop bidding strategies tuned to competitive markets