scholarly journals Three-Stage Analysis of the Maximum Accommodation Capacity of a Distribution System with High Photovoltaic Penetration

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4325
Author(s):  
Jiaqi Gu ◽  
Fei Mei ◽  
Jixiang Lu ◽  
Jinjun Lu ◽  
Jingcheng Chen ◽  
...  
Keyword(s):  
Energy Storage ◽  
Distribution System ◽  
Distribution Network ◽  
Monte Carlo Algorithm ◽  
Pv Inverter ◽  
Standard Distribution ◽  
Timing Simulation ◽  
Node Voltage ◽  
Scheme Selection ◽  
Pv Penetration

The safety and stability of a distribution network will be affected by high photovoltaic (PV) penetration. Therefore, it is of great significance to evaluate the PV accommodation capacity of a distribution network and to select an appropriate PV accommodation scheme. This paper assesses the PV accommodation capacity of a distribution network with an improved algorithm and optimizes the accommodation scheme with a comprehensive index. First, the PSO (particle swarm optimization)–Monte Carlo algorithm is used to evaluate the maximum accommodation capacity of a distribution network with PV integration. Second, a year-round voltage timing simulation is performed to analyze the node voltage that exceeds the limit under the planned PV capacity, which is higher than the previously evaluated maximum accommodation capacity. Finally, the staged control strategy of the PV inverter and energy storage is carried out to select the scheme for the sizing and siting of energy storage. The simulation tests use a 10 kV standard distribution network as an example for PV evaluation and PV accommodation scheme selection to verify the feasibility and effectiveness of the proposed model.

scholarly journals Rooftop Solar PV Penetration Impacts on Distribution Network and Further Growth Factors—A Comprehensive Review

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 55
Author(s):  
Busra Uzum ◽  
Ahmet Onen ◽  
Hany M. Hasanien ◽  
S. M. Muyeen
Keyword(s):  
Solar Energy ◽  
Power Quality ◽  
Distribution System ◽  
Renewable Energy Sources ◽  
Distribution Network ◽  
System Stability ◽  
Solar Pv ◽  
Voltage Quality ◽  
Solution Methods ◽  
Pv Penetration

In order to meet the electricity needs of domestic or commercial buildings, solar energy is more attractive than other renewable energy sources in terms of its simplicity of installation, less dependence on the field and its economy. It is possible to extract solar energy from photovoltaic (PV) including rooftop, ground-mounted, and building integrated PV systems. Interest in rooftop PV system applications has increased in recent years due to simple installation and not occupying an external area. However, the negative effects of increased PV penetration on the distribution system are troublesome. The power loss, reverse power flow (RPF), voltage fluctuations, voltage unbalance, are causing voltage quality problems in the power network. On the other hand, variations in system frequency, power factor, and harmonics are affecting the power quality. The excessive PV penetration also the root cause of voltage stability and has an adverse effect on protection system. The aim of this article is to extensively examines the impacts of rooftop PV on distribution network and evaluate possible solution methods in terms of the voltage quality, power quality, system protection and system stability. Moreover, it is to present a comparison of the advantages/disadvantages of the solution methods discussed, and an examination of the solution methods in which artificial intelligence, deep learning and machine learning based optimization and techniques are discussed with common methods.

Study on System Loss in Distribution Network with DG

2014 ◽  
Vol 672-674 ◽  
pp. 1085-1089
Author(s):  
Jia Meng ◽  
Zai Lin Piao ◽  
Feng Zhou
Keyword(s):  
Theoretical Analysis ◽  
Real Number ◽  
Distribution System ◽  
Distribution Network ◽  
Output Current ◽  
Load Current ◽  
Radial Distribution System ◽  
Operation Optimization ◽  
Voltage Deviation ◽  
Node Voltage

The access of DG changes the operation and structure of traditional distribution network. This study mainly focused on controlling DG output current to reduce network loss of the system. Select a simple radial distribution system as example for theoretical analysis and derive the expressions of load current and node voltage. Assuming that there exists a real number k between DG output current and load. Then list the network loss and voltage deviation expressions. For the purpose of operation optimization, k can be determined by mathematical calculations. It proves that the method has a certain rationality to be effective in controlling network loss.

scholarly journals Optimal Operation of Community Energy Storage using Stochastic Gradient Boosting Trees

2021 ◽  
Author(s):  
Juan Sebastian Giraldo ◽  
Mauricio Salazar ◽  
Pedro P. Vergara ◽  
Georgios Tsaousoglou ◽  
Nikolaos Paterakis ◽  
...  
Keyword(s):  
Energy Storage ◽  
Distribution System ◽  
Synthetic Data ◽  
Optimal Operation ◽  
Stochastic Gradient ◽  
Training Dataset ◽  
Gradient Boosting ◽  
Optimal Solutions ◽  
Stochastic Gradient Boosting ◽  
Pv Penetration

This paper proposes an algorithm for the optimal operation of community energy storage systems (ESSs) using a machine learning (ML) model, by solving a nonlinear programming (NLP) problem iteratively to obtain synthetic data. The NLP model minimizes the network's total energy losses by setting the operation points of a community ESS. The optimization model is solved recursively by Monte Carlo simulations in a distribution system with high PV penetration, considering uncertainty in exogenous parameters. Obtained optimal solutions provide the training dataset for a stochastic gradient boosting trees (SGBT) ML algorithm. The predictions obtained from the ML model have been compared to the optimal ESS operation to assess the model's accuracy. Furthermore, the sensitivity of the ML model has been tested considering the sampling size and the number of predictors. Results showed an accuracy of 98% for the SGBT model compared to optimal solutions, even after a reduction of 83% in the number of predictors.

scholarly journals Optimal Operation of Community Energy Storage using Stochastic Gradient Boosting Trees

2020 ◽  
Author(s):  
Juan Sebastian Giraldo ◽  
Mauricio Salazar ◽  
Pedro P. Vergara ◽  
Georgios Tsaousoglou ◽  
Nikolaos Paterakis
Keyword(s):  
Energy Storage ◽  
Distribution System ◽  
Synthetic Data ◽  
Optimal Operation ◽  
Stochastic Gradient ◽  
Training Dataset ◽  
Gradient Boosting ◽  
Optimal Solutions ◽  
Stochastic Gradient Boosting ◽  
Pv Penetration

This paper proposes an algorithm for the optimal operation of community energy storage systems (ESSs) using a machine learning (ML) model, by solving a nonlinear programming (NLP) problem iteratively to obtain synthetic data. The NLP model minimizes the network's total energy losses by setting the operation points of a community ESS. The optimization model is solved recursively by Monte Carlo simulations in a distribution system with high PV penetration, considering uncertainty in exogenous parameters. Obtained optimal solutions provide the training dataset for a stochastic gradient boosting trees (SGBT) ML algorithm. The predictions obtained from the ML model have been compared to the optimal ESS operation to assess the model's accuracy. Furthermore, the sensitivity of the ML model has been tested considering the sampling size and the number of predictors. Results showed an accuracy of 98% for the SGBT model compared to optimal solutions, even after a reduction of 83% in the number of predictors.

scholarly journals Optimal Siting and Sizing of Battery Energy Storage Systems for Distribution Network of Distribution System Operators

Batteries ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. 56
Author(s):  
Panyawoot Boonluk ◽  
Apirat Siritaratiwat ◽  
Pradit Fuangfoo ◽  
Sirote Khunkitti
Keyword(s):  
Energy Storage ◽  
Distribution System ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Distribution Network ◽  
Energy Storage System ◽  
Power Losses ◽  
Battery Energy Storage ◽  
Battery Energy Storage Systems ◽  
Battery Energy

In this work, optimal siting and sizing of a battery energy storage system (BESS) in a distribution network with renewable energy sources (RESs) of distribution network operators (DNO) are presented to reduce the effect of RES fluctuations for power generation reliability and quality. The optimal siting and sizing of the BESS are found by minimizing the costs caused by the voltage deviations, power losses, and peak demands in the distribution network for improving the performance of the distribution network. The simulation results of the BESS installation were evaluated in the IEEE 33-bus distribution network. Genetic algorithm (GA) and particle swarm optimization (PSO) were adopted to solve this optimization problem, and the results obtained from these two algorithms were compared. After the BESS installation in the distribution network, the voltage deviations, power losses, and peak demands were reduced when compared to those of the case without BESS installation.

scholarly journals VOLTAGE REGULATION CONTROL USING BATTERY ENERGY STORAGE SYSTEM IN DISTRIBUTION NETWORK WITH HIGH PV PENETRATION STRENGTH

2021 ◽  
Vol 83 (6) ◽  
pp. 203-209
Author(s):  
Nur Muhammad Alif Ramli ◽  
Siti Maherah Hussin ◽  
Dalila Mat Said ◽  
Norzanah Rosmin ◽  
Amirjan Nawabjan
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Distribution Network ◽  
Energy Storage System ◽  
Voltage Regulation ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Voltage Rise ◽  
Battery Energy ◽  
Pv Penetration

In recent years, the increasing integration of PV generations into distribution network systems is becoming a huge concern as it introduces various complications such as voltage rise problems, especially during high PV penetration levels. Conventional mitigation methods using voltage regulating devices are not designed to mitigate this particular problem while emerging methods requires sacrifices in term of cost and profit to be made by PV system owners. Thus, mitigation using a battery energy storage system (BESS) is proposed in this paper, where it is specifically designed to solve the voltage rise problem in the distribution system during high PV penetration. This is achieved by controlling the charging and discharging of the BESS accordingly. To validate the effectiveness of the proposed BESS, a simulation using MATLAB/Simulink software of 25 distributed PV generations with respective loads connected to a distribution network power system is done. The penetration level is set from 0% to 100% and the voltage level is measured at the point of common coupling for each increment. The findings show that the BESS can regulate the voltage rise that occurred during high PV penetration of 80% and 100% from 1.11 p.u. and 1.13 p.u. to an acceptable voltage of 1.01 pu.

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