GEOSPATIAL ANALYSES FOR SOLAR ENERGY: IMPACTS OF PV PENETRATION ON ENERGY DEMAND AND PRICE
Open Access
- Author:
- Bayrakci Boz, Mesude
- Graduate Program:
- Energy and Mineral Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- November 17, 2017
- Committee Members:
- Jeffrey Brownson, Dissertation Advisor/Co-Advisor
Jeffrey Brownson, Committee Chair/Co-Chair
Seth Adam Blumsack, Committee Member
Mort D Webster, Committee Member
Susan W Stewart, Outside Member - Keywords:
- Solar
Photovoltaics
GIS
Geospatial
Energy Demand
Solar Assesment
PV Penetration
Locational Marginal Prices
Copula
SUR - Abstract:
- The success of PV energy systems in the future relies in large part on how the assessment of long term solar power potential is determined, and the impact of solar electric installations on the demand curve, congestion and locational marginal prices of a region. Having accurate and reliable solar irradiation data and identifying suitable geographic areas are two crucial steps for obtaining more accurate assessments of production potential and likely patterns of development. This study presents a method for identifying rooftops that are suitable for solar energy systems over large geographic areas by extracting roof segments and using Light Detection and Ranging (LIDAR) data as well as building footprints. This method is applied to create a model of Philadelphia, PA. This model is then used to calculate PV power production and to analyze how the demand curve changes with PV penetration in the Philadelphia Electricity Company (PECO) zone in the PJM region. Next, the model is used to predict locational marginal prices in all PJM regions according to PV penetration in the PECO zone using the Seemingly Unrelated Regression (SUR) approach. The optimal power flow is then identified to show how decisions regarding the installation sites of PV systems with energy demands affect locational marginal prices and transmission losses regarding such energy demands. The model ultimately provides a framework for generating simulated solar irradiation data using a copula with beta distributions.