ARPA-E’s Grid Optimization (GO) Competition comprises a series of prize challenges to accelerate the development and comprehensive evaluation of new software solutions for tomorrow’s electric grid. Key areas for development include but are not limited to optimal utilization of conventional and emerging technologies, management of dynamic grid operations (including extreme event response and restoration), and management of millions of emerging distributed energy resources (DER).

Challenge 1

The first challenge of the GO Competition is an algorithm competition to develop solutions to the electric power sector’s security-constrained optimal power flow (SCOPF) problem. Optimal power flow requires determining generator settings that best enable power to be routed to customers across a complex grid in a reliable and cost-effective manner. Algorithms will be tested on complex, realistic power system models, and participants will be scored on how well their algorithms perform relative to other competitors’. Winning teams will efficiently find a minimum-cost solution to the SCOPF problem.

Additional challenges are planned beginning in 2019 in topics including DERs, intermittent resources, storage, grid resilience, grid restoration, grid dynamics, and cyber threats.

Existing grid software was designed for a power grid based on conventional generation and transmission technologies which are dominated by large, centralized power plants. The rapid development in recent years of new resources, including DERs, intermittent resources (wind and solar), and storage has created a new set of challenges for grid management. Currently, grid management software does not allow for new forms of generation and storage to be used at full potential. Existing grid software makes several simplifying assumptions that produce suboptimal power flow solutions and result in increased electricity costs; the effects of these assumptions grow as the number of DERs grows. Furthermore, increasing emphasis on grid resilience demands innovative management of more diverse and decentralized resources, which existing grid software is not equipped to handle. Innovation is needed regarding the underlying modeling, optimization, and control methods to increase grid flexibility, reliability, and resilience while substantially reducing system costs and barriers to fully integrated emerging technologies.

If successful, GO Competition participants will further the development of advanced software to enable a responsive, resilient, and efficient power grid