Prepared Remarks of Edison International CEO and CFO
Second Quarter 2022 Earnings Teleconference
July 28, 2022, 1:30 p.m. (PT)
Pedro Pizarro, President and Chief Executive Officer, Edison International
Edison International reported core earnings per share of $0.94 compared to $0.94 a year ago. Based on our year-to-date performance and outlook for the remainder of the year, we are reaffirming our 2022 core EPS guidance range of $4.40 to $4.70. I also want to emphasize that we remain fully confident in our long-term EPS growth target of 5 to 7% through 2025. Maria will discuss our financial performance in her remarks.
I would like to begin with an update on the tremendous progress SCE has made in wildfire mitigation. In preparing for this year’s peak wildfire season, SCE has a higher level of confidence in its ability to mitigate wildfires associated with its equipment. During the quarter, SCE achieved a significant grid hardening milestone — it has now replaced over 3,500 circuit miles of bare wire with covered conductor in just over three and a half years. SCE expects to have covered approximately 40% of its overhead distribution power lines in high fire risk areas, or HFRA, by the end of 2022. In many locations throughout SCE’s service area, covered conductor is the primary grid hardening tool since it balances risk reduction, cost, and timely execution. SCE plans to continue its current pace of installing about 1,200 miles per year of covered conductor for the next couple of years. I am pleased with the utility’s execution of this program, which has and will continue to substantially improve safety for customers.
SCE has achieved the majority of wildfire risk reduction through covered conductor and other system hardening measures, vegetation management and equipment inspections. Public Safety Power Shutoffs, or PSPS, provide additional risk reduction that is critical during extreme weather and fuel conditions. SCE also continues to implement cutting-edge technologies to mitigate against high impact wildfires. For example, the utility is leveraging machine learning to improve the accuracy of wind-speed forecasts at around 500 SCE weather station locations, which will help better predict which areas may reach or exceed PSPS thresholds.