Demo Data from VLDB 2026 / reviewers in the wild / expert
Wujing Huang
dblp:237/1423
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0001-7957-2586ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Energy systems and smart grids · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Energy systems and smart grids
multienergy systems |
0.4 | 1 | 2020 | Multienergy Networks Analytics: Standardized Modeling, Optimization, and Low Carbon Analysis · Proc. IEEE 2020 |
Energy systems and smart grids › energy management
energy system planning |
0.1 | 1 | 2020 | Multienergy Networks Analytics: Standardized Modeling, Optimization, and Low Carbon Analysis · Proc. IEEE 2020 |
Methods — techniques the papers use, named apart from their topics
optimization · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Multienergy Networks Analytics: Standardized Modeling, Optimization, and Low Carbon AnalysisabstractMultienergy systems (MESs) are able to unlock the energy system flexibility using the coupling across multiple energy sectors. Such coupling contributes to improving the overall energy efficiency and promoting the accommodation of renewable energy. Among a wide range of literature, this article provides a perspective of network analytics on how to model, optimize, and conduct low-carbon analysis on MESs. The energy sector coupling involves different levels, for example, from a single building to nationwide. In this article, we categorize multienergy networks into two levels, that is, the district level that covers a relatively small area such as a campus or a community, where the energy conversion and utilization is the major focus, and the multiregion level that covers a relatively large area such as a big city, a province, or the whole country, where the energy transmission is the major concern. We first review the state-of-the-art multienergy networks standardized modeling approaches including: 1) energy hub (EH) model for district level energy networks; 2) network models, including power, heat, and gas steady-state and dynamic network models, for multiregion level energy networks; and 3) load models, including electricity, heat, and gas load forecasting models. Second, we explore the planning and operation methods for both district level and multiregion level energy networks. Third, we introduce a special technique named the carbon emission flow (CEF) model that is able to calculate the equivalent CO2 emission associated with the energy flows in multienergy networks. We also demonstrate how the technique can help multienergy networks planning and operation toward a low carbon society. Finally, we envision several further key research topics in the field of multienergy networks. Wujing Huang, Ning Zhang 0008, Yaohua Cheng, Jingwei Yang 0001, Yi Wang 0022, Chongqing Kang |
Proc. IEEE | 1 |