Research & Innovation

Encouraging a Smarter, More Flexible Power Market

Stevens professor awarded grant from the National Science Foundation to advance distributed energy resource coordination research

Dr. Somayeh Moazeni, assistant professor of the School of Systems & Enterprises at Stevens Institute of Technology

Across industry and government, there is understanding that a smarter power grid integrates renewable energy resources to deliver a host of benefits for business and society as a whole, including cleaner energy, increased customer choices and efficiency. But how can utilities, regulators and policy makers effectively collaborate to integrate these resources?

With a new grant from the National Science Foundation (NSF), Dr. Somayeh Moazeni, assistant professor of the School of Systems & Enterprises (SSE) at Stevens Institute of Technology, will lead a collaborative effort to research market models with novel features for encouraging adoption and deployment of distributed flexible energy resources.

Beyond the focus of Clean Energy

Increased integration of renewable energy resources and recent advances in emerging technologies have attracted interest in distributed flexible resources and locally produced power.

However, there are barriers to their deployment due to today’s electricity market obligations, which are too complicated and risky for small participants. In addition, utilities, regulators and policy makers should deal with difficulties in evaluating the individual’s contributions to the operability of the power grid, designing compensation mechanisms, and eliciting participation.

“This research will investigate a proposed market model, which is simple and nonbinding for the individual flexible energy resource owners while maintaining the stability and operability of the power grid,” said Dr. Moazeni.

A major goal of this research is to provide key insights to utilities, regulators and policy makers that will enable them to deploy and control distributed energy resources.

“Coordinating the market participants and analyzing compensation mechanisms require establishing new theory in stochastic optimal control research,” said Dr. Moazeni. “The theory and algorithmic strategies investigated in this project can potentially be extended to coordinate and design other distributed systems, as well.”