TY - JOUR
T1 - Ornstein-Uhlenbeck-Lévy Electricity Portfolios with Wind Energy Contracting
T2 - A Theoretical Approach
AU - Longoria, Genaro
AU - Davy, Alan
AU - Shi, Lei
N1 - Funding Information:
This work was partially funded by 1) Waterford Institute of Technology and 2) Science Foundation Ireland via the CONNECT research centre (grant no. 13/RC/2077).
Publisher Copyright:
© 2018, Springer Nature Singapore Pte Ltd.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - 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.
AB - 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.
KW - Contract management
KW - Electricity portfolio
KW - Renewable energy sources
KW - Risk analysis
KW - Strategic planning
UR - http://www.scopus.com/inward/record.url?scp=85070104052&partnerID=8YFLogxK
U2 - 10.1007/s40866-018-0054-9
DO - 10.1007/s40866-018-0054-9
M3 - Article
AN - SCOPUS:85070104052
VL - 3
JO - Technology and Economics of Smart Grids and Sustainable Energy
JF - Technology and Economics of Smart Grids and Sustainable Energy
SN - 2199-4706
IS - 1
M1 - 16
ER -
