Financial and computational models in electricity markets

Option pricing;Convolution;Affine jump diffusion;Demand response;Thermostatically controlled load;Contract design;Model predictive control;Renewable energy;Emission permit;Volatility mitigation

Xu, Li ; Deng, Shijie Industrial and Systems Engineering Thomas, Valerie M. Hackman, Steve Sun, Andy Meliopolos, A. P. Sakis ; Deng, Shijie

University:Georgia Institute of Technology

Department:Industrial and Systems Engineering

关键词: Option pricing;    Convolution;    Affine jump diffusion;    Demand response;    Thermostatically controlled load;    Contract design;    Model predictive control;    Renewable energy;    Emission permit;    Volatility mitigation;   

Others  :  https://smartech.gatech.edu/bitstream/1853/51849/1/XU-DISSERTATION-2014.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

This dissertation is dedicated to study the design and utilization of financial contracts and pricing mechanisms for managing the demand/price risks in electricity markets and the price risks in carbon emission markets from different perspectives. We address the issues pertaining to the efficient computational algorithms for pricing complex financial options which include many structured energy financial contracts and the design of economic mechanisms for managing the risks associated with increasing penetration of renewable energy resources and with trading emission allowance permits in the restructured electric power industry. To address the computational challenges arising from pricing exotic energy derivatives designed for various hedging purposes in electricity markets, we develop a generic computational framework based on a fast transform method, which attains asymptotically optimal computational complexity and exponential convergence. For the purpose of absorbing the variability and uncertainties of renewable energy resources in a smart grid, we propose an incentive-based contract design for thermostatically controlled loads (TCLs) to encourage end users' participation as a source of DR. Finally, we propose a market-based approach to mitigate the emission permit price risks faced by generation companies in a cap-and-trade system. Through a stylized economic model, we illustrate that the trading of properly designed financial options on emission permits reduces permit price volatility and the total emission reduction cost.