Understanding that it’s all about what you do with the analytics, TROVE Solvers are software models that apply machine learning, deep learning, and AI to uncover opportunities in data and solve specific needs. The models are applied without human bias, so the data will speak for itself to provide insights and support data-driven decision making.
“TROVE Solvers are analytic models created with the latest machine-learning and deep-learning tools to create value for our clients by solving specific business problems with a clear, measurable benefit. No platform, no overhead, simply AI software that completely addresses clients' needs.”– Dr. Adam Stotz, CTO, TROVE
TROVE Solvers are easily configurable to meet clients’ unique needs. This configuration is handled by our expert team of data scientists, the Science Squad®, as part of TROVE’s Agile Data Science process.
What is the impact of not engaging with prospects and customers on a personal level?
Successful consumer companies understand that successful customer engagement throughout the lifecycle requires a deep understanding of customer behaviors andpreferences. Personalized offers, campaigns and servicing lead to higher sales and customer satisfaction.
How can we be more efficient with capital deployment and O&M expenses?
Utility load growth is flat-to-declining in most parts of the United States. This coupled with large capital expenditures to modernize the grid and only modest customer price increases creates a tough earnings environment for utilities and has resulted in a concentrated focus on reducing O&M costs and optimizing capital expenditures.
How do we optimize our product and service portfolio as DER growth becomes more impactful?
Forecasts show the implementation of distributed energy resources (DERs) doubling over the next 5 years. These customer-driven changes will have an important role in the future of the grid, requiring an integrated approach to an expanded portfolio of demand-side resources to support grid services, deferral of capital expenses, and utility revenue streams. While much of the DER discussion to date has centered on solar and storage, it is also being shaped by a renaissance in precision demand response and energy efficiency along with new time-of-use (TOU) rates and electric vehicles. The flexibility and precision of DER resources can make them a valuable component in the active management of the distribution grid.
How do we prepare grid operations and forecasting if we want to become the Utility of the Future?
The Utility of the Future must be able to accommodate the doubling of distributed energy resources over the next 5 years, resulting in two-way and intermittent power flow on the distribution grid. System-level forecasts and generic assumptions about load flow being evenly distributed downstream of the substation will no longer be adequate.