Location: Computing Research and Education Building (CoRE) Lecture Hall, Room 101
Abstract: To incentive renewable energy installations in the power system, more than half of U.S. states have employed renewable energy policies in terms of renewable portfolio standards (RPSs) and renewable energy credits (RECs), which leads to the gaining prominence of a new environmental market form, namely REC markets. In REC markets, for each MWh generated from renewable energy source, a unit of REC is issued. The renewable energy generator can sell its RECs in the REC marketplaces to a Load Serving Entity (LSE) who is subject to the annual compliance RPS requirement on the percentage of electricity procured from renewable energy sources. REC markets can be considered as an alternative form of subsidizing renewable energy.
In this talk, I will highlight my recent work at Rutgers with Prof. Frank A. Felder “Generation Expansion Planning with Renewable Energy Credit Market: A Bilevel Programming Approach”. I will first review US renewable energy policies in term of RPS and REC. Then, I will discuss the coupling effects between renewable energy policies and the power system operations. I will present how we can mathematically model these policies and integrate them to the conventional generation expansion planning framework using bilevel optimization approach. Finally, I will illustrate how we can use our model to examine some observed and predicted impacts of renewable energy policies on the power systems such as the merit order effect, the die out of nuclear power, and the paradox of renewables on electricity retail prices. This work is supported by the National Science Foundation under Grant CMMI 1825225. The abstract of our paper is as follows:
“This paper presents a novel generation expansion planning (GEP) problem that integrates the renewable energy market to the power system operations. We consider the gaining prominence for renewable energy credits (REC) used to implement renewable portfolio standards, a politically popular renewable energy policy employed in many US states. The overall problem is formulated as a bilevel optimization where the offering prices, supplies, and demands in the REC markets are considered as functions of power system optimal operations. The problem is solved effectively by the proposed combination of the KKT reformulation methods and the fixed-point iterative algorithm. Key findings on the impacts of renewable energy policies on GEP solutions such as the merit order effects, the changes in retail electricity prices, and the RPS dilution, which are consistent with practical observations, are presented. Our model provides an effective framework for evaluating the long-term impacts of renewable energy policies.”
Bio: Hieu Trung Nguyen is currently a postdoctoral research associate at the Center for Energy, Economics & Environmental Studies, Bloustein School of Planning and Public Policy, Rutgers, New Jersey, USA where he is working modeling energy systems with environmental policies. From 2017-2019, he was a postdoctoral research associate at the University of Utah, Salt Lake City, Utah, and Iowa State University, Ames, Iowa, USA respectively where he worked on resilience enhancement strategies for power systems against natural disasters and transactive energy market designs for integrated power transmission & distribution networks. He obtained his Ph.D. in Telecommunication from the University of Quebec, INRS, Montreal, Canada in 2017 where he worked on demand-side management for smart grid. His general research focuses on developing mathematical models and computationally algorithms for economic-engineering analysis of power energy system operation and planning. He was the recipient of the PERSWADE fellowship from the Natural Sciences and Engineering Research Council of Canada at INRS and the 2018 best reviewer award from IEEE Transactions on Smart Grid.
For additional information, please contact Dr. Ahmed Aziz at firstname.lastname@example.org or at 848-445-3625.