Power utilities are changing rapidly, with more distributed electricity generation, growing decarbonization policies and an increasingly competitive retail market that offers greater choice to consumers. Faced with rapidly falling levelized cost of renewable electricity and battery storage, rising investments in electrification of large parts of the economy, and aggressive regulatory innovation to incentivize distributed energy resources (DERs), including solar and wind energy, electric vehicles, energy storage, energy efficiency, and demand-side management, utilities are adopting new digital technologies and improving their abilities to respond quickly to demanding expectations from customers and regulators. While the United States has benefited from low-cost natural gas which has pushed gas-fired electricity generation to the top of the power mix, innovation in DER technology has led to major changes in electricity production, consumption and delivery systems. Regionally, a common trend for the increasing share of non-hydro renewable electricity generation and natural gas-fired combined cycle (CC) and combustion turbines is emerging in the PJM Interconnection, the world’s largest and most advanced regional transmission organization (RTO), thereby putting a renewed spotlight on the methods and tools for power system planning and grid modernization.

As the grid profile diversifies, what is the impact of the increasing natural gas-fired electricity generation assets on installed distributed solar PV systems? What role does a typology of policy, regulatory, and business model constructs for improving utility choices, including locational marginal pricing (LMP), electricity rate designs, customer engagement, and load capacity management have on solar capacity development? In this webinar, I present an assessment of empirical dynamic panel data model using system generalized method of moments (system-GMM) estimation approach. This approach accounts for the impact of past and current policy and changes in market structure over time, forecasting errors, and business cycles by controlling for the location of generation assets and year fixed effects.