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Found 21 papers, 9 papers with code
Distributional Principal Autoencoders
Dimension reduction techniques usually lose information in the sense that reconstructed data are not identical to the original data.
Joint Planning of Active Distribution Network and EV Charging Stations Considering Vehicle-to-Grid Functionality and Reactive Power Support
This paper proposes a collaborative planning model for the active distribution network (ADN) and electric vehicle (EV) charging stations that fully considers the vehicle-to-grid (V2G) function and reactive power support of EVs in different regions.
Invariant Probabilistic Prediction
In recent years, there has been a growing interest in statistical methods that exhibit robust performance under distribution changes between training and test data.
A Robust Planning Model for Offshore Microgrid Considering Tidal Power and Desalination
First, a deterministic planning model (DPM) is formulated for the OM with TPG and SDU.
Causality-oriented robustness: exploiting general additive interventions
In a linear setting, we prove that DRIG yields predictions that are robust among a data-dependent class of distribution shifts.
Engression: Extrapolation for Nonlinear Regression?
Our experimental results indicate that this model is typically suitable for many real data sets.
A Smart Switch Configuration and Reliability Assessment Method for Large-Scale Offshore Wind Farm Electrical Collector System
With the development of offshore wind farms (OWFs) in far-offshore and deep-sea areas, each OWF could contain more and more wind turbines and cables, making it imperative to study high-reliability electrical collector system (ECS) for OWF.
Optimal Planning for Electrical Collector System of Offshore Wind Farm with Double-sided Ring Topology
We propose a planning method for offshore wind farm electrical collector system (OWF-ECS) with double-sided ring topology meeting the "N-1" criterion on cable faults, in which the submarine cables layout of OWF is optimized considering cable length and power losses.
Asymptotic Statistical Analysis of $f$-divergence GAN
We show that for parametric generative models that are correctly specified, all $f$-divergence GANs with the same discriminator classes are asymptotically equivalent under suitable regularity conditions.
Reframed GES with a Neural Conditional Dependence Measure
In this paper, we revisit the Greedy Equivalence Search (GES) algorithm, which is widely cited as a score-based algorithm for learning the MEC of the underlying causal structure.
A Stochastic Planning Method for Low-carbon Building-level Integrated Energy System Considering Electric-Heat-V2G Coupling
The concept of low-carbon building is proposed to ameliorate the climate change caused by environmental problems and realize carbon neutrality at the building level in urban areas.
A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction
In a modern power system, real-time data on power generation/consumption and its relevant features are stored in various distributed parties, including household meters, transformer stations and external organizations.
Accuracy and Application Scope Analysis for Linearized Branch Flow Model in Radial Distribution Systems
An in-depth analysis of linearized branch flow (LBF) model considering current injection and absolute value of impedance is proposed in this paper.
Large-scale Offshore Wind Farm Electrical Collector System Planning: A Mixed-Integer Linear Programming Approach
In this paper, we propose a planning method for large-scale offshore wind farm (OWF) electrical collector system (ECS) based on mixed integer linear programming, in which the sizing and siting of offshore substations and the lines between wind turbines (WTs) are optimized.
Two-stage Planning for Electricity-Gas Coupled Integrated Energy System with CCUS Considering Carbon Tax and Price Uncertainty
In this article, we propose two-stage planning models for Electricity-Gas Coupled Integrated Energy System (EGC-IES), in which traditional thermal power plants (TTPPs) are considered to be retrofitted into carbon capture power plants (CCPPs), with power to gas (PtG) coupling CCPPs to gas system.
A Conditional Value-at-Risk Based Planning Model for Integrated Energy System with Energy Storage and Renewables
Owing to the potential higher energy supply efficiency and operation flexibility, integrated energy system (IES), which usually includes electric power, gas and heating/cooling systems, is considered as one of the primary forms of energy carrier in the future.
A Federated Learning Framework for Smart Grids: Securing Power Traces in Collaborative Learning
For example, power consumption data are stored in numerous transformer stations across cities; mobility data of the population, which are important indicators of power consumption, are held by mobile companies.
Weakly Supervised Disentangled Generative Causal Representation Learning
This paper proposes a Disentangled gEnerative cAusal Representation (DEAR) learning method under appropriate supervised information.
CausalVAE: Structured Causal Disentanglement in Variational Autoencoder
Learning disentanglement aims at finding a low dimensional representation which consists of multiple explanatory and generative factors of the observational data.
Bidirectional Generative Modeling Using Adversarial Gradient Estimation
This paper considers the general $f$-divergence formulation of bidirectional generative modeling, which includes VAE and BiGAN as special cases.
