scholarly journals Online pricing for demand‐side management in a low‐voltage resistive micro‐grid via a Stackelberg game with incentive strategies

2021 ◽  
Author(s):  
Fernando Genis Mendoza ◽  
George Konstantopoulos ◽  
Dario Bauso
Keyword(s):  
Low Voltage ◽  
Stackelberg Game ◽  
Demand Side Management ◽  
Demand Side ◽  
Incentive Strategies ◽  
Micro Grid ◽  
Online Pricing

Adaptive in-situ forecasting for demand-side management in low voltage power grids

2021 ◽  
Author(s):  
Christian Backe ◽  
Miguel Bande ◽  
Stefan Werner ◽  
Christian Wiezorek
Keyword(s):  
Low Voltage ◽  
Demand Side Management ◽  
Power Grids ◽  
Demand Side

scholarly journals Data-Driven Risk Analysis for Probabilistic Three-Phase Grid-Supportive Demand Side Management

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2514 ◽  
Author(s):  
Niels Blaauwbroek ◽  
Phuong Nguyen ◽  
Han Slootweg
Keyword(s):  
Time Horizon ◽  
Situational Awareness ◽  
Low Voltage ◽  
Demand Side Management ◽  
Power Sharing ◽  
Data Driven ◽  
Demand Side ◽  
Three Phase ◽  
Management Application ◽  
Data Driven Approach

Along with the emerging development of demand side management applications, it is still a challenge to exploit flexibility realistically to resolve or prevent specific geographical network issues due to limited situational awareness of the (unbalanced low-voltage) network as well as complex time dependent constraints. To overcome these problems, this paper presents a time-horizon three-phase grid-supportive demand side management methodology for low voltage networks by using a universal interface that is established between the demand side management application and the monitoring and network analysis tools of the network operator. Using time-horizon predictions of the system states that the probability of operational limit violations is identified. Since this analysis is computationally intensive, a data driven approach is adopted by using machine learning. Time-horizon flexibility is procured, which effectively prevents operation limit violation from occurring independent of the objective that the demand side management application has. A practical example featuring fair power sharing demonstrates the effectiveness of the presented method for resolving over-voltages and under-voltages. This is followed by conclusions and recommendations for future work.

Demand-Side Management in a Micro-Grid with Multiple Retailers: A Coalitional Game Approach

2021 ◽  
Author(s):  
Fernando Genis Mendoza ◽  
Pablo R. Baldivieso-Monasterios ◽  
Dario Bauso ◽  
George Konstantopoulos
Keyword(s):  
Demand Side Management ◽  
Coalitional Game ◽  
Demand Side ◽  
Micro Grid

scholarly journals Demand-Side Management for Improvement of the Power Quality in Smart Homes Using Non-Intrusive Identification of Appliance Usage Patterns with the True Power Factor

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4837
Author(s):  
Hari Prasad Devarapalli ◽  
Venkata Samba Sesha Siva Sarma Dhanikonda ◽  
Sitarama Brahmam Gunturi
Keyword(s):  
Power Quality ◽  
Power Factor ◽  
Distribution Systems ◽  
Low Voltage ◽  
Harmonic Distortion ◽  
Smart Homes ◽  
Demand Side Management ◽  
Usage Pattern ◽  
Demand Side ◽  
Current Harmonics

The proliferation of low-power consumer electronic appliances (LPCEAs) is on the rise in smart homes in order to save energy. On the flip side, the current harmonics induced due to these LPCEAs pollute low-voltage distribution systems’ (LVDSs’) supplies, leading to a poor power factor (PF). Further, the energy meters in an LVDS do not measure both the total harmonic distortion (THD) of the current and the PF, resulting in inaccurate billing for energy consumption. In addition, this impacts the useful lifetime of LPCEAs. A PF that takes the harmonic distortion into account is called the true power factor (TPF). It is imperative to measure it accurately. This article measures the TPF using a four-term minimal sidelobe cosine-windowed enhanced dual-spectrum line interpolated Fast Fourier Transform (FFT). The proposed method was used to measure the TPF with a National Instruments cRIO-9082 real-time (RT) system, and four different LPCEAs in a smart home were considered. The RT results exhibited that the TPF uniquely identified each usage pattern of the LPCEAs and could use them to improve the TPF by suggesting an alternative usage pattern to the consumer. A positive response behavior on the part of the consumer that is in their interest can improve the power quality in a demand-side management application.

Sign in / Sign up

Export Citation Format

Share Document