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Found 8 papers, 0 papers with code
Tractable Data Enriched Distributionally Robust Chance-Constrained CVR
To better consider the impacts of load and PV generation uncertainties on CVR implementation in distribution systems and provide less conservative solutions, this paper develops a data-based DRCC-CVR model with tractable reformulation and data enrichment method.
Analyzing Photovoltaic's Impact on Conservation Voltage Reduction in Distribution Networks
The results show that the allocations of solar PV have the most significant effect on the CVR performance, where a dispersed allocation of solar PV will help flatten voltage profile and achieve deeper voltage reductions at the substation, less energy consumption and line losses.
A Two-layer Approach for Estimating Behind-the-Meter PV Generation Using Smart Meter Data
In this paper, we have come up with a novel two-layer approach to disaggregate the unknown PV generation and native demand from the known hourly net demand data recorded by smart meters: 1) At the aggregate level, the proposed approach separates the total PV generation and native demand time series from the total net demand time series for customers with PVs.
A Hierarchical Deep Actor-Critic Learning Method for Joint Distribution System State Estimation
To maintain monitoring accuracy, the two levels exchange boundary information with each other at the secondary nodes, including transformer voltages (first layer to second layer) and active/reactive total power injection (second layer to first layer).
Computational Efficiency
Hierarchical Reinforcement Learning
Multi-Source Data Fusion Outage Location in Distribution Systems via Probabilistic Graph Models
A novel aspect of the proposed approach is that it takes multi-source evidence and the complex structure of distribution systems into account using a probabilistic graphical method.
Enriching Load Data Using Micro-PMUs and Smart Meters
The key to our approach is to statistically recover the high-resolution load data, which is masked by the low-resolution data, using trained probabilistic models of service transformers that have both high and low-resolution data sources, i. e, micro-PMUs and smart meters.
Distributed Optimal Conservation Voltage Reduction in Integrated Primary-Secondary Distribution Systems
This paper proposes an asychronous distributed leader-follower control method to achieve conservation voltage reduction (CVR) in three-phase unbalanced distribution systems by optimally scheduling smart inverters of distributed energy resources (DERs).
Disaggregating Customer-level Behind-the-Meter PV Generation Using Smart Meter Data and Solar Exemplars
In most cases, PVs are installed behind-the-meter (BTM), and only the net demand is recorded.
