Power and Energy
Optimal current tracking performance is crucial for the control of high-speed permanent magnet synchronous motors (PMSMs). In this study, an innovative discrete model-free predictive current control (MFPCC) method is proposed to address the challenges presented by flux-weakening (FW) and low-frequency ratio (LFR) conditions, which limit the conventional MFPCC's applicability in the high-speed range.
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The purpose of this supplement is to provide the direct outcomes of the proposed procedure for the three examples investigated in the main body of the paper. The exit probabilities from the safe subset $(-pi/2, \pi/2)$ are computed according to the numerical result of our proposed procedure of each power line. The proposed procedure is not shown in detail but referred to as the reference [55] in the reference list of the first part which is from page 1 to page 26 of this PDF document.
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This dataset comprises residential energy data from the UK, covering a nearly five-year period from 2015 to 2020. It includes a total of 201,605 data points, each meticulously recorded at 15-minute intervals, ensuring a high level of granularity. The dataset provides detailed attributes such as the date, time, residential energy load (measured in kilowatts), electricity price (in GBP), solar energy generation (in kilowatts), wind energy generation (in kilowatts), and various weather-related parameters.
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This dataset includes the actual operational data from twelve wind turbines at Zhangbei wind farm in Hebei province, China. The SCADA data of twelve wind turbines was collected at 60-second intervals from March 2014 to March 2015. The specification of the wind turbines in the wind farm is as follows: the cut-in wind speed is 1m/s, the rated wind speed is 12m/s, the cut-out wind speed is 25m/s, and the rated power is 1500kW. four simulated data manually generated for data cleaning.
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Large-scale penetration of renewable energy generation brings various challenges to the power system in the fields of safety, reliability, economy, and flexibility. Since wind power and solar energy have naturally complementary characteristics, that is, solar irradiation is abundant during the day, while the wind is strong during the night. In summer, there is adequate solar irradiation and scare winds. In winter and spring, there are stronger winds and insufficient solar irradiation.
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The dataset consists of data for the IEEE 118-bus system, IEEE 300-bus system, and a modified 3266-bus system based on the practical provincial grid of China for unit commitment. The dataset includes one year of load information, renewable energy generation data, and the necessary parameters for solving the unit commitment problem, such as units, lines, and buses.
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735 Views
Existing AC/DC power flow computations necessi- tate sequential convergence-oriented trial-and-error under vari- ous DC control modes, rising computational burden. This paper thus proposes a physics-guided multi-agent graph learning (PG- MAGL) method towards real-time power flow analysis with DC control mode adaptation. The tailored graph structure with built- in DC control modes and state variables is firstly advanced to ensure topology adaptability. Then, MAGL is proposed to enable adaptive jump over DC control modes.
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This dataset is sourced from an integrated energy system in a region of northern China, encompassing a wide range of energy data including wind power, photovoltaic power, electricity load, thermal load, and cooling load. The dataset features a time resolution of one hour, with a 24-hour timescale for each selected day. A total of five typical days have been chosen, representing different seasonal and weather conditions, to capture the variations in energy production and consumption patterns.
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355 Views
This dataset supports the manuscript titled “Strategies for Mitigating Degradation of Medium Voltage Electrical Equipment in Harsh Saline Environments.” The study focuses on identifying and addressing the challenges faced by medium voltage equipment in coastal environments characterized by high salinity, humidity, and extreme weather conditions. The dataset includes:
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110 Views
As port clusters continue to evolve as critical hubs for global trade, there is an increasing emphasis on sustainability and operational efficiency. The integration of advanced energy systems, including electrified and hydrogen-powered container logistics, is essential for enhancing port operations while minimizing environmental impact. This dataset provides comprehensive parameters and data for integrated energy and container logistics systems within a port cluster, including detailed configuration information on energy units and logistics facilities.
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