Hybrid simulation-based policy evaluation for solar power generation systems

To encourage the adoption of solar energy, state and federal governments have employed various incentives, such as rebates, tax return opportunities, and net metering credits. Meanwhile, the governments are concerned with a potential steep growth of solar, which may increase the electricity price and threaten the stability of existing transmission systems. The goal of this research is to develop a decision-support tool to analyze the effectiveness of various policies ensuring a proper growth rate of photovoltaic (PV) systems avoiding the instability of the transmission system or steep rising of the electricity price. We propose a hybrid two-level simulation modeling framework, which is more detailed than the structures commonly used in most policy evaluations. The lower-level model calculates the PV system payback period of individual household based on incentive levels, PV module prices, and hourly PV generation, consumptions and electricity price (grid). The higher-level model concerns the household adoptions of the PV systems influenced by various factors, including payback period, household income, word-of-mouth effect and advertisement effect. Agent-based and system dynamics modeling techniques are leveraged. Experiments have been conducted for two different residential areas to illustrate the impact of policies in different regions.