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David C. Yu
Researcher at University of Wisconsin–Milwaukee
Publications - 62
Citations - 2249
David C. Yu is an academic researcher from University of Wisconsin–Milwaukee. The author has contributed to research in topics: Electric power system & Renewable energy. The author has an hindex of 20, co-authored 61 publications receiving 1913 citations. Previous affiliations of David C. Yu include University of Wisconsin-Madison.
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Optimal sizing of hybrid PV/diesel/battery in ship power system ☆
TL;DR: In this article, the optimal size of the photovoltaic (PV) generation system, diesel generator and the energy storage system in a stand-alone ship power system that minimizes the investment cost, fuel cost and the CO2 emissions is proposed.
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Economic Allocation for Energy Storage System Considering Wind Power Distribution
TL;DR: In this paper, a hybrid multi-objective particle swarm optimization (HMOPSO) approach is proposed to minimize the power system cost and improve the system voltage profiles by searching sitting and sizing of storage units under consideration of uncertainties in wind power production.
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Weather sensitive short-term load forecasting using nonfully connected artificial neural network
TL;DR: In this article, the authors presented an artificial neural network (ANN) model for forecasting weather-sensitive loads, which is capable of forecasting the hourly loads for an entire week and can differentiate between weekday loads and weekend loads.
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Microgrid Generation Capacity Design With Renewables and Energy Storage Addressing Power Quality and Surety
TL;DR: A generalized approach to design (determine the capacity requirements) is proposed and the management of microgrids with metrics to meet the power quality indexes is demonstrated.
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Correction of current transformer distorted secondary currents due to saturation using artificial neural networks
TL;DR: In this article, the use of artificial neural networks (ANN) to correct current transformer (CT) secondary waveform distortions is presented, which is trained to achieve the inverse transfer function of iron-core toroidal CTs which are widely used in protective systems.