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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 EnergySpringer Journals

Published: Nov 10, 2018

References