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Ornstein-Uhlenbeck-Lévy Electricity Portfolios with Wind Energy Contracting

Ornstein-Uhlenbeck-Lévy Electricity Portfolios with Wind Energy Contracting To leverage the potential of integrating renewable sources into electricity portfolios the risk and cost trade-off of intermittency needs to be assessed. From the perspective of a Load Serving Entity (LSE), this work present the theoretical implications of energy allocation from two type of markets: bilateral long-term contracts and real-time trading. The purchasing of energy on both markets and from two different sources: wind energy and conventional generation is formulated with a stochastic procurement model (SPM). The unexpected jumps of spot market prices are modeled with a mean-reverting Lévy process. The wind energy availability is modeled with multiplicative Brownian motion transformed to a Rayleigh probability density function. The risk assessment is defined by the efficient frontier and a user defined risk level. The SPM is tested numerically. The contracted share of wind power is found to range between 8% and 16%. Moreover, the analysis shows the convergence of SPM to an optimal portfolio irrespectively of the wind farm autocorrelation decay rate. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Technology and Economics of Smart Grids and Sustainable Energy Springer Journals

Ornstein-Uhlenbeck-Lévy Electricity Portfolios with Wind Energy Contracting

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Nature Singapore Pte Ltd.
Subject
Energy; Energy Systems; Power Electronics, Electrical Machines and Networks; Energy Policy, Economics and Management
eISSN
2199-4706
DOI
10.1007/s40866-018-0054-9
Publisher site
See Article on Publisher Site

Abstract

To leverage the potential of integrating renewable sources into electricity portfolios the risk and cost trade-off of intermittency needs to be assessed. From the perspective of a Load Serving Entity (LSE), this work present the theoretical implications of energy allocation from two type of markets: bilateral long-term contracts and real-time trading. The purchasing of energy on both markets and from two different sources: wind energy and conventional generation is formulated with a stochastic procurement model (SPM). The unexpected jumps of spot market prices are modeled with a mean-reverting Lévy process. The wind energy availability is modeled with multiplicative Brownian motion transformed to a Rayleigh probability density function. The risk assessment is defined by the efficient frontier and a user defined risk level. The SPM is tested numerically. The contracted share of wind power is found to range between 8% and 16%. Moreover, the analysis shows the convergence of SPM to an optimal portfolio irrespectively of the wind farm autocorrelation decay rate.

Journal

Technology and Economics of Smart Grids and Sustainable Energy – Springer Journals

Published: Nov 10, 2018

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