scholarly journals Low Voltage Daily Energy Demand Temperature Dependent Representation by Using Circular Statistics

2019 ◽  
Vol 10 (03) ◽  
pp. 61-74
Author(s):  
Pucheta Julián ◽  
Salas Carlos ◽  
Piumetto Miguel ◽  
Herrera Martín ◽  
Rodriguez Rivero Cristian
Keyword(s):  
Energy Demand ◽  
Low Voltage ◽  
Circular Statistics ◽  
Temperature Dependent ◽  
Daily Energy

scholarly journals A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts

2020 ◽  
Author(s):  
Bogdan-Constantin Neagu ◽  
Ovidiu Ivanov ◽  
Gheorghe Grigoras ◽  
Mihai Gavrilas
Keyword(s):  
Electricity Market ◽  
Energy Demand ◽  
Low Voltage ◽  
Peer To Peer ◽  
Local Network ◽  
Financial Benefits ◽  
Daily Energy ◽  
New Vision ◽  
The Government ◽  
Energy Surplus

A growing number of households benefit from the government subsidies to install renewable generation facilities such as PV panels, used to gain independence from the grid and provide cheap energy. In the Romanian electricity market, these prosumers can sell their generation surplus only at regulated prices, back to the grid. A way to increase the number of prosumers is to allow them to make higher profit by selling this surplus back into the local network. This would also be an advantage for the consumers, who could pay less for electricity exempt from network tariffs and benefitting from lower prices resulting from the competition between prosumers. One way of enabling this type of trade is to use peer-to-peer contracts traded in local markets, run at microgrid (μG) level. This paper presents a new trading platform based on smart peer-to-peer (P2P) contracts for prosumers energy surplus trading in a real local microgrid. Several trading scenarios are proposed, which give the possibility to perform trading based on participants’ locations, instantaneous active power demand, maximum daily energy demand and the principle of first come first served implemented in an anonymous blockchain trading ledger. The developed scheme is tested on a low-voltage (LV) microgrid model to check its feasibility of deployment in a real network. A comparative analysis between the proposed scenarios, regarding traded quatities and financial benefits is performed.

scholarly journals A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 235 ◽  
Author(s):  
Bogdan-Constantin Neagu ◽  
Ovidiu Ivanov ◽  
Gheorghe Grigoras ◽  
Mihai Gavrilas
Keyword(s):  
Electricity Market ◽  
Energy Demand ◽  
Low Voltage ◽  
Peer To Peer ◽  
Local Network ◽  
Power Demand ◽  
Financial Benefits ◽  
Daily Energy ◽  
New Vision ◽  
Energy Surplus

A growing number of households benefit from government subsidies to install renewable generation facilities such as PV panels, used to gain independence from the grid and provide cheap energy. In the Romanian electricity market, these prosumers can sell their generation surplus only at regulated prices, back to the grid. A way to increase the number of prosumers is to allow them to make higher profit by selling this surplus back into the local network. This would also be an advantage for the consumers, who could pay less for electricity exempt from network tariffs and benefit from lower prices resulting from the competition between prosumers. One way of enabling this type of trade is to use peer-to-peer contracts traded in local markets, run at microgrid (μG) level. This paper presents a new trading platform based on smart peer-to-peer (P2P) contracts for prosumers energy surplus trading in a real local microgrid. Several trading scenarios are proposed, which give the possibility to perform trading based on participants’ locations, instantaneous active power demand, maximum daily energy demand, and the principle of first come first served implemented in an anonymous blockchain trading ledger. The developed scheme is tested on a low-voltage (LV) microgrid model to check its feasibility of deployment in a real network. A comparative analysis between the proposed scenarios, regarding traded quatities and financial benefits is performed.

scholarly journals Data Analytics for Profiling Low-Voltage Customers with Smart Meter Readings

2021 ◽  
Vol 11 (2) ◽  
pp. 500
Author(s):  
Fabrizio Pilo ◽  
Giuditta Pisano ◽  
Simona Ruggeri ◽  
Matteo Troncia
Keyword(s):  
Energy Demand ◽  
Data Analytics ◽  
Distribution Systems ◽  
Low Voltage ◽  
Renewable Energy Sources ◽  
A Priori ◽  
Energy Transition ◽  
Smart Meters ◽  
Large Databases ◽  
A New Technique

The energy transition for decarbonization requires consumers’ and producers’ active participation to give the power system the necessary flexibility to manage intermittency and non-programmability of renewable energy sources. The accurate knowledge of the energy demand of every single customer is crucial for accurately assessing their potential as flexibility providers. This topic gained terrific input from the widespread deployment of smart meters and the continuous development of data analytics and artificial intelligence. The paper proposes a new technique based on advanced data analytics to analyze the data registered by smart meters to associate to each customer a typical load profile (LP). Different LPs are assigned to low voltage (LV) customers belonging to nominal homogeneous category for overcoming the inaccuracy due to non-existent coincident peaks, arising by the common use of a unique LP per category. The proposed methodology, starting from two large databases, constituted by tens of thousands of customers of different categories, clusters their consumption profiles to define new representative LPs, without a priori preferring a specific clustering technique but using that one that provides better results. The paper also proposes a method for associating the proper LP to new or not monitored customers, considering only few features easily available for the distribution systems operator (DSO).

scholarly journals Synchronized Control of Voltage and Current Harmonics in Distributed Generation System using Fuzzy Controller

2019 ◽  
Vol 8 (12) ◽  
pp. 1179-1182
Keyword(s):  
Distributed Generation ◽  
Energy Demand ◽  
Power Flow ◽  
Fuzzy Controller ◽  
Low Voltage ◽  
Load Condition ◽  
Control Technique ◽  
Current Harmonics ◽  
Simultaneous Control ◽  
Unbalanced Load

The worldwide energy demand is increasing due to increase in population and economic growth. The grid is gradually replaced by Distributed generation systems (DGs). Recently low voltage DG interfacing converter on the non linear load compensation is performed by unified power flow converter. The proposed control technique is analyzed for Simultaneous control of voltage and power under unbalanced load condition using MATLAB/SIMULINK software

scholarly journals Wavelet Analysis of Daily Energy Demand and Weather Variables

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Abdou Latif Bonkaney ◽  
Ibrah Seidou Sanda ◽  
Ahmed A. Balogun
Keyword(s):  
Wind Speed ◽  
Phase Analysis ◽  
Energy Demand ◽  
Electricity Demand ◽  
Weather Variables ◽  
Daily Energy ◽  
Wavelet Transform Coherence ◽  
Average Coherence ◽  
The Relationship ◽  
Insight Into

In this paper, we applied the Wavelet Transform Coherence (WTC) and phase analysis to analyze the relationship between the daily electricity demand (DED) and weather variables such as temperature, relative humidity, wind speed, and radiation. The DED data presents both seasonal fluctuations and increasing trend while the weather variables depict only seasonal variation. The results obtained from the WTC and phase analysis permit us to detect the period of time when the DED significantly correlates with the weather variables. We found a strong seasonal interdependence between the air temperature and DED for a periodicity of 256-512 days and 128-256 days. The relationship between the humidity and DED also shows a significant interdependence for a periodicity of 256-512 days with average coherence equal to 0.8. Regarding the radiation and wind speed, the correlation is low with average coherence less than 0.5. These results provide an insight into the properties of the impacts of weather variables on electricity demand on the basis of which power planners can rely to improve their forecasting and planning of electricity demand.

scholarly journals A GIS-Based Planning Approach for Urban Power and Natural Gas Distribution Grids with Different Heat Pump Scenarios

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4052 ◽  
Author(s):  
Jolando M. Kisse ◽  
Martin Braun ◽  
Simon Letzgus ◽  
Tanja M. Kneiske
Keyword(s):  
Co2 Emissions ◽  
Heat Pump ◽  
Energy Demand ◽  
Low Voltage ◽  
Primary Energy ◽  
Heat Pumps ◽  
Slight Reduction ◽  
Single Family ◽  
Gas Distribution ◽  
Public Data

Next to building insulation, heat pumps driven by electrical compressors (eHPs) or by gas engines (geHPs) can be used to reduce primary energy demand for heating. They come with different investment requirements, operating costs and emissions caused. In addition, they affect both the power and gas grids, which necessitates the assessment of both infrastructures regarding grid expansion planning. To calculate costs and CO2 emissions, 2000 electrical load profiles and 180 different heat demand profiles for single-family homes were simulated and heat pump models were applied. In a case study for a neighborhood energy model, the load profiles were assigned to buildings in an example town using public data on locations, building age and energetic refurbishment variants. In addition, the town’s gas distribution network and low voltage grid were modeled. Power and gas flows were simulated and costs for required grid extensions were calculated for 11% and 16% heat pump penetration. It was found that eHPs have the highest energy costs but will also have the lowest CO2 emissions by 2030 and 2050. For the investigated case, power grid investments of 11,800 euros/year are relatively low compared to gas grid connection costs of 70,400 euros/year. If eHPs and geHPs are combined, a slight reduction of overall costs is possible, but emissions would rise strongly compared to the all-electric case.

Using Flexibility Information for Energy Demand Optimization in the Low Voltage Grid

2015 ◽  
Author(s):  
Sandford Bessler ◽  
Domagoj Drenjanac ◽  
Eduard Hasenleithner ◽  
Suhail Ahmed-Khan ◽  
Nuno Silva
Keyword(s):  
Energy Demand ◽  
Low Voltage

scholarly journals Time-Series Temperature-Dependent Power Flow Considering Unbalanced Thermoelectric Equivalent Circuits for Underground LV and MV Cables

2021 ◽  
Author(s):  
Evangelos Pompodakis ◽  
Andreas I. Chrysochos ◽  
Arif Ahmed ◽  
Minas C. Alexiadis
Keyword(s):  
Time Series ◽  
Power Flow ◽  
Low Voltage ◽  
Distribution Networks ◽  
Temperature Dependent ◽  
Underground Cables ◽  
Thermal Circuit ◽  
Three Phase ◽  
Homogeneous Soil ◽  
Conductor Temperature

<p>This manuscript proposes a time-series temperature-dependent power flow method for unbalanced distribution networks consisting of underground cables. A thermal circuit model for unbalanced three-phase multi-core cables is developed to estimate the conductor temperature and resistance of Medium and Low Voltage distribution networks. More specifically, a novel approach is proposed to model and estimate the parameters of the three-phase thermal circuit of 3/4-core cables, using the results of Finite Element Method and Particle Swarm Optimization. The proposed approach is generic and can be accurately applied to any kind of 3- or 4-core cables buried in homogeneous or non-homogeneous soil. Furthermore, it is applicable in cases where one or more adjacent cables exist. Using the proposed approach, the conductor temperature of each phase can be individually and precisely calculated even in networks with highly unbalanced loads. The proposed approach is expected to be an important tool for simulating the steady state of unbalanced distribution networks and estimating the conductor temperatures. The proposed thermal circuit is validated using two 4-core LV and one 3-core MV cables buried in different depths in homogeneous or non-homogeneous soil. Time-series power flow for a whole year is performed in a 25-bus unbalanced LV network consisting of multicore underground cables.</p>

scholarly journals Design of a photovoltaic power plant connected to the grid to cover the daytime energy demand of the Jenmer cia ltda service station

2021 ◽  
Vol 7 (1) ◽  
pp. 10-24
Author(s):  
Antonio Vázquez Pérez ◽  
Fabián Ignacio Carpio Zambrano ◽  
Alcira Magdalena Velez Quiroz ◽  
Gino Mieles Mieles ◽  
Carlos Gustavo F. Villacreses Viteri
Keyword(s):  
Energy Consumption ◽  
Energy Demand ◽  
Low Voltage ◽  
Field Research ◽  
Service Station ◽  
Photovoltaic Power ◽  
Electricity Bill ◽  
Photovoltaic Technology ◽  
Photovoltaic Plant

The work presents an analysis linked to one of the sustainable energy alternatives that are currently being adopted with success worldwide. Putting the field research method into practice, the results of a study related to an application of technological innovation are shown to reduce the amount of the electricity bill at the JENMER CIA LTDA Service Station, through the introduction of photovoltaic technology connected to the low voltage network of the institution. The results of the study of load and hourly energy consumption of said entity are shown and its methodology is deployed for the technological design of a photovoltaic plant connected to the grid, which can avoid the energy consumption of the conventional grid, reducing the amount of the electricity bill of the institution, at the same time that it is possible to reduce losses, improve the quality of electricity service and reduce COemissions2 into the atmosphere. The energy, economic, environmental, and social impacts associated with the penetration of photovoltaic technology are exposed.

ANALYSING SPANISH DAILY ENERGY DEMAND BY PROGRAMMING A GRAPHICAL IMPLEMENTATION WITH R

2014 ◽  
Author(s):  
JOSE MANUEL VELASCO ◽  
BEATRIZ GONZÁLEZ-PÉREZ ◽  
GUADALUPE MIÑANA ◽  
VICTORIA LÓPEZ ◽  
RAQUEL CARO
Keyword(s):  
Energy Demand ◽  
Daily Energy
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