Integrated economic adoption model for residential grid-connected photovoltaic systems: An Australian case study - Omar Ellabban; Abdulrahman Alassi (Energy Reports, 2019)
Photovoltaic (PV) systems, like most renewable energy resources, are characterized by large initial capital investments by the energy user. The high upfront cost (for which many residential customers are unwilling to take risks) is and will remain one of the main obstacles that need to be tackled in order to achieve a faster and a greater deployment of the distributed PV technology in the residential sector as a local generation source. Understanding the economics of the residential PV installation is a key aspect to determine whether the financial investment in this sector is economically feasible and reasonable or not. Thus, it is essential to conduct a comprehensive economic analysis to encourage residential consumers to be PV adopters. The main purpose of this work is to present an Integrated Economic Adoption Model (IEAM) for distributed PV systems. This IEAM is composed of four modules: (1) economic assessment of four different proposed electricity retail tariff structures; (2) profitability analysis of these proposed electricity retail tariff structures based on the most common economic indicators: Net Present Value (NPV), Internal Rate of Return (IRR), Discounted Payback Period (DPBP), and Profitability Index (PI); (3) sensitivity analysis of different variables which strongly affect the PV system profitability; and finally, (4) Levelized Cost of Electricity (LCOE) probability distribution based on the Monte Carlo Analysis (MCA). The model is implemented using Microsoft Excel spreadsheet based on a real dataset for one year of PV generation and residential load consumption for 54 customers in the Ausgrid's electricity network, New South Wales (NSW), Australia (as case study) under the current market arrangements and PV support policies. The model can be easily adapted to any location by changing the generation and load profiles and the relevant economic assumptions and electricity regulatory policies. The outcomes of this IEAM should guide the decision makers in different distribution networks in designing their retail tariff structure and PV support policies and to conduct economic feasibility analysis for residential and commercial PV projects with different sizes in different locations within their networks. Also, the IEAM answers the investment profitability questions for the household owners under real integrated system uncertainty.
Keywords: 330; Economic Adoption Model; Feed in tariff; Monte Carlo analysis; Net metering; Profitability analysis; Sensitivity analysis