Search Results for author: Audun Botterud

Found 11 papers, 1 papers with code

Uncertainty-Informed Renewable Energy Scheduling: A Scalable Bilevel Framework

no code implementations6 Dec 2023 Dongwei Zhao, Vladimir Dvorkin, Stefanos Delikaraoglou, Alberto J. Lamadrid L., Audun Botterud

Furthermore, we find that when transmission capacity increases, the proposed bilevel model will still reduce the system cost, whereas the myopic strategy may incur a much higher cost due to over-scheduling of VRES in the day-ahead market and the lack of flexible conventional generators in real time.

Bilevel Optimization Scheduling

An Integer Clustering Approach for Modeling Large-Scale EV Fleets with Guaranteed Performance

no code implementations3 Oct 2023 Sijia Geng, Thomas Lee, Dharik Mallapragada, Audun Botterud

Large-scale integration of electric vehicles (EVs) leads to a tighter integration between transportation and electric energy systems.

Clustering Computational Efficiency +1

Cost-effective Planning of Decarbonized Power-Gas Infrastructure to Meet the Challenges of Heating Electrification

no code implementations31 Aug 2023 Rahman Khorramfar, Morgan Santoni-Colvin, Saurabh Amin, Leslie K. Norford, Audun Botterud, Dharik Mallapragada

Applying the framework to study the U. S. New England region in 2050 across 20 weather scenarios, we find high electrification of the residential sector can increase sectoral peak and total electricity demands by up to 56-158% and 41-59% respectively relative to business-as-usual projections.

Uniform Pricing vs Pay as Bid in 100%-Renewables Electricity Markets: A Game-theoretical Analysis

no code implementations21 May 2023 Dongwei Zhao, Audun Botterud, Marija Ilic

We prove that UP can incentivize suppliers to withhold bidding quantities and lead to price spikes.

Differentially Private Algorithms for Synthetic Power System Datasets

1 code implementation20 Mar 2023 Vladimir Dvorkin, Audun Botterud

While power systems research relies on the availability of real-world network datasets, data owners (e. g., system operators) are hesitant to share data due to security and privacy risks.

Privacy Preserving

Market Mechanisms for Low-Carbon Electricity Investments: A Game-Theoretical Analysis

no code implementations14 Dec 2022 Dongwei Zhao, Sarah Coyle, Apurba Sakti, Audun Botterud

To reduce the impact of excessive scarcity prices, we present a new market mechanism, which consists of a Penalty payment for lost load, a supply Incentive, and an energy price Uplift (PIU).

A Scalable Bilevel Framework for Renewable Energy Scheduling

no code implementations25 Nov 2022 Dongwei Zhao, Vladimir Dvorkin, Stefanos Delikaraoglou, Alberto J. Lamadrid L., Audun Botterud

Accommodating the uncertain and variable renewable energy sources (VRES) in electricity markets requires sophisticated and scalable tools to achieve market efficiency.

Scheduling

Strategic Storage Investment in Electricity Markets

no code implementations7 Jan 2022 Dongwei Zhao, Mehdi Jafari, Audun Botterud, Apurba Sakti

Each investor decides the storage investment over a long investment horizon, and operates the storage for arbitrage revenues in the daily electricity market.

Optimization of Electrolyte Rebalancing in Vanadium Redox Flow Batteries

no code implementations7 Jul 2021 Mehdi Jafari, Apurba Sakti, Audun Botterud

This paper presents a novel algorithm to optimize energy capacity restoration of vanadium redox flow batteries (VRFBs).

Planning low-carbon distributed power systems: Evaluating the role of energy storage

no code implementations20 Sep 2020 Jiachen Mao, Mehdi Jafari, Audun Botterud

This paper introduces a mathematical formulation of energy storage systems into a generation capacity expansion framework to evaluate the role of energy storage in the decarbonization of distributed power systems.

Bounding Regression Errors in Data-driven Power Grid Steady-state Models

no code implementations30 Oct 2019 Yuxiao Liu, Bolun Xu, Audun Botterud, Ning Zhang, Chongqing Kang

Results identify how the bounds decrease with additional power grid physical knowledge or more training data.

regression

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