About Energy Royalty Partners
Energy Royalty Partners is an asset management firm which deploys advanced data analytics in highly fragmented markets in the energy sector to acquire assets on behalf of its investment funds with a current AUM of ~ $75MM.
The principals of Energy Royalty Partners ("ERP") Luis Castillo, Grant Eidson and Ken Scott, have a combined 75 years of experience investing in and managing assets in the energy industry. Primarily, this experience has been in the application of emergent data science tools to better understand, invest, and optimize assets for stakeholders, which have ranged in size from family offices to multinational public companies.
ERP has partnered with an established U.S.-based private equity firm to apply its proprietary data science tools and processes to expanding opportunities in the renewable energy industry. Our objective is to provide our investors with attractive risk-adjusted returns through investment in real assets, while optimizing for capital deployment efficiency and continually mitigating downside risk.
Renewable Royalties
ERP's current fund is primarly dedicated to acquiring royalties from utility-scale renewable projects in the United States.
If you would like to discuss our current fund, or selling your royalties, please contact us.
Discipline
ERP strives to invest in assets that have proven resiliency over time. Our disciplined approach allows ERP to seek to mitigate downside risk, meet our objectives, and minimize cost along the way. We understand the macroeconomic forces bearing upon the investment and the microeconomic forces producing the opportunity.
Methodology
ERP's team has decades of experience sourcing, evaluating, acquiring and managing energy portfolios. Our proven process-oriented approach allows for efficient and effective investment of the capital entrusted to us.
Data Aggregation
ERP utilizes in-house developed proprietary software to aggregate its datasets. We believe our unique aggregation tools and predictive analytics produce opportunistic, data-driven investment opportunities.
Machine Learning Data Analysis
Through the integration of multiple spatial and temporal datasets, ERP's proprietary software continuously evolves to produce accurate evaluations of energy assets in a dynamic market.
Relational
ERP endeavors to honor the capital. This means we must be good stewards of the trust and capital with which we have been vested. That begins with the culture within ERP and extends to all those with whom we transact.