Top Downloads Research Articles

End-to-End Top-Down Load Forecasting Model for Residential Consumers

This study presents an efficient end-to-end (E2E) learning approach for the short-term load forecasting of hierarchically structured residential consumers based on the principles of a top-down (TD) approach. This technique employs a neural network for predicting load at lower hierarchical levels based on the aggregated one at the top. A simulation is carried out with 9 (from 2013 to 2021) years of energy consumption data of 50 houses located in the United States of America. Simulation results demonstrate that the E2E model, which uses a single model for different nodes and is based on the principles of a top-down approach, shows huge potential for improving forecasting accuracy, making it a valuable tool for grid planners. Model inputs are derived from the aggregated residential category and the specific cluster targeted for forecasting. The proposed model can accurately forecast any residential consumption cluster without requiring any hyperparameter adjustments. According to the experimental analysis, the E2E model outperformed a two-stage methodology and a benchmarked Seasonal Autoregressive Integrated Moving Average (SARIMA) and Support Vector Regression (SVR) model by a mean absolute percentage error (MAPE) of 2.27%.

Achieving Optimal Value of Solar: A Municipal Utility Rate Analysis

Wind and solar renewable energy in the United States is projected to triple by 2050 to nearly 30% of total electric energy generation. The upper Midwest region (Iowa, Minnesota, and North and South Dakota in particular) is considered wind energy country and not historically known for solar energy development. In this work, Value of Solar (VOS) is developed as a photovoltaic (PV) optimization measure and analysis tool using a northwest Iowa municipality as a representative case study. By applying a top-down load duration curve system analysis, VOS is used to optimize PV orientation and compare electric rate structures for increasing levels of total PV energy contribution. VOS of a fixed south-southwest orientation exceeds the levelized annual costs of installation with a larger net benefit than a one-axis-tracking solar system. Production-data modeled VOS is up to 12% higher than Typical Meteorological Year (TMY) predictions, indicating significant correlation between PV generation and peak municipal demand. Compared to alternative time-of-use rates, a demand/energy rate structure better matches VOS economic value and optimal orientation. This VOS methodology is an easy-to-use yet meaningful tool for municipalities and smaller utilities to evaluate strategic installation of and investment in PV for their local community.

Field Tests on Bearing Characteristics of Large-Diameter Combined Tip-and-Side Post Grouted Drilled Shafts

This paper presents a field study on the axial behavior of four large-diameter drilled shafts embedded in coarse sand. The grouting and loading test procedures were reported. The bearing capacity of shafts (TS1 and TS2) and grouted drilled shafts (TS3 and TS4) were herein determined by the bi-directional static test and top-down load test, respectively. The enhancement mechanism of bearing characteristics of the grouted shafts was discussed in detail. The test results indicate that the bearing characteristics and load transfer mechanisms of the test shafts were significantly affected by the quantity of pressurized cement slurry and the mechanical properties of the soil surrounding the shafts. Furthermore, the tip resistance of shaft can be mobilized more rapidly and fully after grouting, the side and tip resistance are mobilized in a more synchronized and coordinated manner due to the pre-mobilization of the grouted cement. Additionally, the standard penetration test (SPT) prediction model was introduced to calculate and predict the SPT blow counts of soil after grouting. The results show that the post grouting has a more obvious improvement on the strength of cohesionless soil.

A Comparison of Top-down Load Forecasting and Bottom-up Load Forecasting in Distribution Network

In this paper, the electricity load of a certain region is taken as the research object. Firstly, the back propagation neural network (BP) model is used to predict the macro load of the region from top to bottom. Then, on the premise of comprehensive consideration of the region’s meteorological, economic, large user registration and other causes, the power grid of the region is divided. On this basis the differential integration moving average autoregressive (ARIMA) model is used to carry out the bottom-up micro load forecasting: First, the load forecasting of each cell is carried out, and then the prediction results are summarized in proportion to obtain the overall prediction results of the region. Through the comparative analysis of the two load forecasting results, it is found that although the two forecasting errors are fewer than 9%, the bottom-up load forecasting method which combines grid partition and fine classification has a prediction error of fewer than 5 %. The results show that the bottom-up load forecasting method is better.

Top Downloads on IEEE Xplore [Reader's Choice

Presents a list of articles published by the IEEE Signal Processing Society (SPS) that ranked among the top 100 most downloaded IEEE Xplore articles.

Top Downloads on IEEE Xplore [Reader's Choice

Presents a list of articles published by the IEEE Signal Processing Society (SPS) that ranked among the top 100 most downloaded IEEE Xplore articles.

The Influence of Short Video Platform on Audience Use and Reflections—Take TikTok as an example

In the context of the strict prevention and control of the epidemic in 2021, short video platforms have become a popular choice for entertainment, and it is common for TikTok to be the top download of video and audio in the mobile client app download list. In the four months from mid-December 2020 to mid-April 2021, downloads have grown from 5.04 billion to 5.8 billion. While TikTok has a large number of users, its shortcomings, such as vulgar, plagiarism and privacy disclosure, cannot be ignored. How to solve them has become a top priority. Whether TikTok can meet users' demands and guide users to think about whether they can co-existence and how to balance both of them will need to be further explored.

Top Downloads in IEEE Xplore [Reader's Choice

Presents a list of articles published by the IEEE Signal Processing Society (SPS) that ranked among the top 100 most downloaded IEEE Xplore articles.

Top Download Article in Computer Science & Information Technology Research: October 2020

Top Download Article in Computer Science & Information Technology Research: October 2020

Top Downloads in IEEE Xplore [Reader's Choice

Top Downloads in IEEE Xplore [Reader's Choice

Top Downloads in IEEE Xplore [Reader's Choice

Top Downloads in IEEE Xplore [Reader's Choice

Top Downloads in IEEE Xplore [Reader's Choice

Top Downloads in IEEE Xplore [Reader's Choice

Top Downloads in IEEE Xplore [Reader's Choice

Presents a list of articles published by the IEEE Signal Processing Society (SPS) that ranked among the top 100 most downloaded IEEE Xplore articles.

Top Downloads in IEEE Xplore [Reader's Choice

Top Downloads in IEEE Xplore [Reader's Choice

Application of static loading tests to steel pipe piles with large diameters in Chinese offshore wind farms

In this paper, three kinds of static loading test methods were introduced by referencing three offshore wind farms in China. In the first project, O-cell tests were performed on four steel pipe piles, namely, two vertical piles and two inclined piles, with diameters of 1.7 m and embedment depths from 67.24 to 69.70 m. Next, the equivalent load-settlements for top-down load and pull-out load tests at the pile heads were given by using a conversion method. Then, the conversion results were verified using different methods. Finally, the rationality of utilizing the coefficient factors of γ1 and γ2, which were 0.8 and 1.1 in the first project, were verified by studying three piles in two other offshore wind farm projects, where a top-down load test and pull-out load test were conducted on each pile. The results show that the O-cell test can successfully determine the axial compression capacity and uplift capacity by the proposed conversion method.

Top Downloads in IEEE Xplore [Reader's Choice

Top Downloads in IEEE Xplore [Reader's Choice

Top Downloads in IEEE Xplore [Reader's Choice

Presents a list of articles published by the IEEE Signal Processing Society (SPS) that ranked among the top 100 most downloaded IEEE Xplore articles.

PyPSA-Eur: An open optimisation model of the European transmission system

PyPSA-Eur, the first open model dataset of the European power system at the transmission network level to cover the full ENTSO-E area, is presented. It contains 6001 lines (alternating current lines at and above 220 kV voltage level and all high voltage direct current lines), 3657 substations, a new open database of conventional power plants, time series for electrical demand and variable renewable generator availability, and geographic potentials for the expansion of wind and solar power. The model is suitable both for operational studies and generation and transmission expansion planning studies. The continental scope and highly resolved spatial scale enables a proper description of the long-range smoothing effects for renewable power generation and their varying resource availability. The restriction to freely available and open data encourages the open exchange of model data developments and eases the comparison of model results. A further novelty of the dataset is the publication of the full, automated software pipeline to assemble the load-flow-ready model from the original datasets, which enables easy replacement and improvement of the individual parts. This paper focuses on the description of the network topology, the compilation of a European power plant database and a top-down load time-series regionalisation. It summarises the derivation of renewable wind and solar availability time-series from re-analysis weather datasets and the estimation of renewable capacity potentials restricted by land-use. Finally, validations of the dataset are presented, including a new methodology to compare geo-referenced network datasets to one another.

Top Downloads in IEEE Xplore [Reader's Choice

Presents a list of articles published by the IEEE Signal Processing Society (SPS) that ranked among the top 100 most downloaded IEEE Xplore articles.

Product quality and competition: evidence from the broadband industry

ABSTRACTAccess to high-quality broadband internet is important in many different respects such as in communication, education, commerce and information acquisition. We investigate the relationship between the number of broadband providers in an area and the quality of broadband service provided where download speed is used as a proxy for quality. We find that increased competition in an area positively affects the access to fast download speeds. This finding is robust to three different top download speeds tested. Additionally, a theoretical model is provided which shows that competition can decrease the profits associated with offering slow speeds; this gives an incentive for providers to offer higher speeds as a way to increase profits.