H
Hrvoje Pandzic
Researcher at University of Zagreb
Publications - 124
Citations - 2582
Hrvoje Pandzic is an academic researcher from University of Zagreb. The author has contributed to research in topics: Computer science & Electric power system. The author has an hindex of 23, co-authored 79 publications receiving 1786 citations. Previous affiliations of Hrvoje Pandzic include University of Washington.
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Near-Optimal Method for Siting and Sizing of Distributed Storage in a Transmission Network
TL;DR: In this paper, a three-stage planning procedure is described to identify the optimal locations and parameters of distributed storage units, and the optimal operation of the storage units is simulated to quantify the benefits that they would provide by reducing congestion.
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Optimal Operation and Services Scheduling for an Electric Vehicle Battery Swapping Station
TL;DR: In this article, the authors proposed an optimization framework for the operating model of battery swapping stations, which considers the day-ahead scheduling process and uses inventory robust optimization and multi-band robust optimization to model electricity price uncertainty.
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A Hybrid Stochastic/Interval Approach to Transmission-Constrained Unit Commitment
TL;DR: In this article, the authors proposed a transmission-constrained unit commitment method that combines the cost-efficient but computationally demanding stochastic optimization and the expensive but tractable interval optimization techniques to manage uncertainty on the expected net load.
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Enhanced Security-Constrained Unit Commitment With Emerging Utility-Scale Energy Storage
TL;DR: In this article, the authors introduce emerging utility-scale energy storage (e.g., batteries) as part of the set of control measures in a corrective form of the security-constrained unit commitment (SCUC) problem.
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Ensuring Profitability of Energy Storage
Yury Dvorkin,Ricardo Fernandez-Blanco,Daniel S. Kirschen,Hrvoje Pandzic,Jean-Paul Watson,Cesar A. Silva-Monroy +5 more
TL;DR: In this article, a bilevel program is proposed to determine the optimal location and size of storage devices to perform spatiotemporal energy arbitrage, which aims to simultaneously reduce the system-wide operating cost and the cost of investments in energy storage while ensuring that merchant storage devices collect sufficient profits to fully recover their investment cost.