To Invest or Not to Invest: The Exploration of Preferred Investment Strategies in Corporate Renewable Power Purchase Agreements
Open Access
- Author:
- Li, Daiwei
- Graduate Program:
- Energy and Mineral Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- March 03, 2020
- Committee Members:
- Seth Adam Blumsack, Thesis Advisor/Co-Advisor
Jeffrey Brownson, Committee Member
Zhen Lei, Committee Member
Mort D Webster, Program Head/Chair - Keywords:
- Multi-Objective Optimization Problem
Single-Objective Optimization Problem
Real Option Valuation
Power Purchase Agreement
Greenhouse Gas Emission
Wholesale Electricity Price
Binomial Lattice Pricing Method
Unit Commitment
Monte Carlo Simulation
Single-Objective Optimization Problem
Real Option Valuation
Power Purchase Agreement
Greenhouse Gas Emission
Wholesale Electricity Price
Binomial Lattice Pricing Method
Unit Commitment
Monte Carlo Simulation - Abstract:
- The modern society has seen a continuously growing electricity consumption and its associated environmental consequences. With recent technology advancements, renewable energy has been considered by many as a source of electricity that is both economically feasible and environmentally friendly. The investment of renewable energy projects can be intriguing, however. This research first developed a theoretical model using Multi-Objective Optimization Problem to determine the preferred investment strategies that considers both the economic and environmental benefit of a special kind of investment in renewable energy projects – Corporate Renewable Power Purchase Agreement (PPA). The proposed methods were implemented on the case study of The Pennsylvania State University in central Pennsylvania, United States. The general version of the Multi-Objective Optimization Problem required making significant assumptions that reduced the computation complexity. The study explored the uncertainty in future Wholesale Electricity Prices, which was assumed to be the source of electricity for the investors of these renewable energy projects had there been no investments made. The use of Binomial Lattice Pricing Model, Monte Carlo Simulation, and Unit Commitment produced the feasible solutions of the Multi-Objective Optimization Problem in which the corresponded Pareto Set was identified. The simplified version of the proposed Multi-Objective Optimization Problem was reduced into several Single-Objective Optimization Problems of the economic benefits of PPA investments, in which they also represent some Real Option Valuation Problems under specific conditions. While making other assumptions to maintain the tractability of these problems, the optimal solutions of the Single-Objective Optimization Problem and the Value of Options were identified. One of these Single-Objective Optimization Problem monetized the environmental benefits of PPA investments using Social Cost of Carbon published by EPA. Finally, Sensitivity Analyses were applied in some of these Optimization Problems, producing the corresponding solutions.