scholarly journals Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1648
Author(s):  
Marinko Barukčić ◽  
Toni Varga ◽  
Vedrana Jerković Jerković Štil ◽  
Tin Benšić
Keyword(s):  
Power System ◽  
Power Management ◽  
Computational Intelligence ◽  
Input Data ◽  
Optimization Problem ◽  
Optimal Allocation ◽  
Distribution Networks ◽  
Distributed Generations ◽  
Data Resolution ◽  
The Impact

The paper researches the impact of the input data resolution on the solution of optimal allocation and power management of controllable and non-controllable renewable energy sources distributed generation in the distribution power system. Computational intelligence techniques and co-simulation approach are used, aiming at more realistic system modeling and solving the complex optimization problem. The optimization problem considers the optimal allocation of all distributed generations and the optimal power control of controllable distributed generations. The co-simulation setup employs a tool for power system analysis and a metaheuristic optimizer to solve the optimization problem. Three different resolutions of input data (generation and load profiles) are used: hourly, daily, and monthly averages over one year. An artificial neural network is used to estimate the optimal output of controllable distributed generations and thus significantly decrease the dimensionality of the optimization problem. The proposed procedure is applied on a 13 node test feeder proposed by the Institute of Electrical and Electronics Engineers. The obtained results show a huge impact of the input data resolution on the optimal allocation of distributed generations. Applying the proposed approach, the energy losses are decreased by over 50–70% by the optimal allocation and control of distributed generations depending on the tested network.

scholarly journals Scenario-Based Network Reconfiguration and Renewable Energy Resources Integration in Large-Scale Distribution Systems Considering Parameters Uncertainty

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 26
Author(s):  
Ziad M. Ali ◽  
Ibrahim Mohamed Diaaeldin ◽  
Shady H. E. Abdel Aleem ◽  
Ahmed El-Rafei ◽  
Almoataz Y. Abdelaziz ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Distribution Systems ◽  
Optimization Problem ◽  
Optimal Allocation ◽  
Distribution Networks ◽  
Optimization Approach ◽  
Network Reconfiguration ◽  
Distributed Generations ◽  
Node Distribution ◽  
Power Loss Reduction

Renewable energy integration has been recently promoted by many countries as a cleaner alternative to fossil fuels. In many research works, the optimal allocation of distributed generations (DGs) has been modeled mathematically as a DG injecting power without considering its intermittent nature. In this work, a novel probabilistic bilevel multi-objective nonlinear programming optimization problem is formulated to maximize the penetration of renewable distributed generations via distribution network reconfiguration while ensuring the thermal line and voltage limits. Moreover, solar, wind, and load uncertainties are considered in this paper to provide a more realistic mathematical programming model for the optimization problem under study. Case studies are conducted on the 16-, 59-, 69-, 83-, 415-, and 880-node distribution networks, where the 59- and 83-node distribution networks are real distribution networks in Cairo and Taiwan, respectively. The obtained results validate the effectiveness of the proposed optimization approach in maximizing the hosting capacity of DGs and power loss reduction by greater than 17% and 74%, respectively, for the studied distribution networks.

scholarly journals Phase Synchronization Stability of Non-Homogeneous Low-Voltage Distribution Networks with Large-Scale Distributed Generations

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1257 ◽  
Author(s):  
Shi Chen ◽  
Hong Zhou ◽  
Jingang Lai ◽  
Yiwei Zhou ◽  
Chang Yu
Keyword(s):  
Power Law ◽  
Coupling Strength ◽  
Large Scale ◽  
Phase Synchronization ◽  
Distribution Networks ◽  
Critical Coupling ◽  
Power Law Distribution ◽  
Distributed Generations ◽  
Strength Formula ◽  
The Impact

The ideal distributed network composed of distributed generations (DGs) has unweighted and undirected interactions which omit the impact of the power grid structure and actual demand. Apparently, the coupling relationship between DGs, which is determined by line impedance, node voltage, and droop coefficient, is generally non-homogeneous. Motivated by this, this paper investigates the phase synchronization of an islanded network with large-scale DGs in a non-homogeneous condition. Furthermore, we explicitly deduce the critical coupling strength formula for different weighting cases via the synchronization condition. On this basis, three cases of Gaussian distribution, power-law distribution, and frequency-weighted distribution are analyzed. A synthetical analysis is also presented, which helps to identify the order parameter. Finally, this paper employs the numerical simulation methods to test the effectiveness of the critical coupling strength formula and the superiority over the power-law distribution.

scholarly journals Optimal Allocation of Static Var Compensators in Electric Power Systems

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3219 ◽  
Author(s):  
Martin Ćalasan ◽  
Tatjana Konjić ◽  
Katarina Kecojević ◽  
Lazar Nikitović
Keyword(s):  
Power Systems ◽  
Power System ◽  
Optimal Power Flow ◽  
Optimal Allocation ◽  
Reactive Power ◽  
Dynamic Performance ◽  
Variable Load ◽  
Power Losses ◽  
Facts Devices ◽  
The Impact

In the current age, power systems contain many modern elements, one example being Flexible AC Transmission System (FACTS) devices, which play an important role in enhancing the static and dynamic performance of the systems. However, due to the high costs of FACTS devices, the location, type, and value of the reactive power of these devices must be optimized to maximize their resulting benefits. In this paper, the problem of optimal power flow for the minimization of power losses is considered for a power system with or without a FACTS controller, such as a Static Var Compensator (SVC) device The impact of location and SVC reactive power values on power system losses are considered in power systems with and without the presence of wind power. Furthermore, constant and variable load are considered. The mentioned investigation is realized on both IEEE 9 and IEEE 30 test bus systems. Optimal SVC allocation are performed in program GAMS using CONOPT solver. For constant load data, the obtained results of an optimal SVC allocation and the minimal value of power losses are compared with known solutions from the literature. It is shown that the CONOPT solver is useful for finding the optimal location of SVC devices in a power system with or without the presence of wind energy. The comparison of results obtained using CONOPT solver and four metaheuristic method for minimization of power system losses are also investigated and presented.

scholarly journals Distributionally Robust Distributed Generation Hosting Capacity Assessment in Distribution Systems

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2981 ◽  
Author(s):  
Mohammad Seydali Seyf Abad ◽  
Jin Ma ◽  
Ahmad Ahmadyar ◽  
Hesamoddin Marzooghi
Keyword(s):  
Robust Optimization ◽  
Distributed Generation ◽  
Optimization Model ◽  
Distribution Systems ◽  
Historical Data ◽  
Distribution Networks ◽  
Distributionally Robust Optimization ◽  
Distributed Generations ◽  
Distributionally Robust ◽  
The Impact

Uncertainties associated with the loads and the output power of distributed generations create challenges in quantifying the integration limits of distributed generations in distribution networks, i.e., hosting capacity. To address this, we propose a distributionally robust optimization-based method to determine the hosting capacity considering the voltage rise, thermal capacity of the feeders and short circuit level constraints. In the proposed method, the uncertain variables are modeled as stochastic variables following ambiguous distributions defined based on the historical data. The distributionally robust optimization model guarantees that the probability of the constraint violation does not exceed a given risk level, which can control robustness of the solution. To solve the distributionally robust optimization model of the hosting capacity, we reformulated it as a joint chance constrained problem, which is solved using the sample average approximation technique. To demonstrate the efficacy of the proposed method, a modified IEEE 33-bus distribution system is used as the test-bed. Simulation results demonstrate how the sample size of historical data affects the hosting capacity. Furthermore, using the proposed method, the impact of electric vehicles aggregated demand and charging stations are investigated on the hosting capacity of different distributed generation technologies.

scholarly journals Simultaneous optimal allocation and sizing of distributed generations and shunt capacitors in distribution networks using fuzzy GA methodology

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Srinivasa Rao Gampa ◽  
Debapriya Das
Keyword(s):  
Genetic Algorithm ◽  
Power Factor ◽  
Distribution Systems ◽  
Optimal Allocation ◽  
Reactive Power ◽  
Distribution Networks ◽  
Optimization Techniques ◽  
Distributed Generations ◽  
Shunt Capacitors ◽  
Fuzzy Genetic

AbstractThis paper presents a combination of fuzzy and genetic algorithm (GA)-based methodology for simultaneous optimum allocation and sizing of distributed generations (DGs) and shunt capacitors (SCs) together in distribution systems. The objectives of reduction of active power and reactive power supply, reduction of real power loss and improvement of branch current capacity, voltage profile and voltage stability are considered. The combination of shunt capacitors with both unity power factor DGs and lagging power factor DGs also considered for analyzing the performance of the distribution systems. Simulation results are demonstrated to show the advantage of proposed fuzzy genetic algorithm-based technique over conventional multiobjective approach and loss sensitivity-based optimization techniques reported in the literature.

scholarly journals Photovoltaic Generation Integration with Radial Feeders Using GA and GIS

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Elias Mandefro Getie ◽  
Belachew Bantyirga Gessesse ◽  
Tewodros Gera Workneh
Keyword(s):  
Power System ◽  
Power Loss ◽  
Optimal Allocation ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Generation System ◽  
Photovoltaic Generation ◽  
Gis Methods ◽  
Pv Generation ◽  
Transmission And Distribution

The electric power generated from different electricity sources are not used efficiently by end users in the world. This is due to the loss of power supplied in the case of electricity transmission and distribution to residential, commercial, and industrial loads. Even if the loss of power in the power system cannot be avoided 100%, it should be reduced to the minimum optimal value. The loss of power in the radial feeders can be minimized using an optimally allocated photovoltaic (PV) generation system by considering the information of geography, solar irradiance of the site, and space availability, which should not have shadow from large buildings and trees. The PV generation system eliminates the problem of power demand by enhancing the capacity of the power network as well as by reducing the depletion and consumption of fossil fuel resources. To reduce power loss and improve system loading capacity for demand response, the integration and finding the optimal place of photovoltaic generation take high concern from power system operators and technicians. The optimal allocation of PV has been done using the Genetic Algorithm (GA) for optimization of a multiobjective function with different constraints. The main objective of this paper is to minimize the power loss of the radial distribution networks by maintaining the phase voltage of the load in balance and improving the drop in voltage along the phase. So, GA is used to determine the best location and capacity of PV generation that can reduce the loss of power in the system. The IEEE-33 bus system is used to test the proposed method. Generally, using the GA and GIS methods results in a high accuracy for optimal placement of PV generation in the IEEE-33 bus radial feeder and enables to reduce the loss of power during transmission and distribution by maintaining the power quality for consumers.

scholarly journals A Review of methodologies for Fault Location Techniques in Distribution Power System

2021 ◽  
Vol 17 (2) ◽  
pp. 27-37
Author(s):  
Ahmed Abbas ◽  
Mazyed Al-Tak
Keyword(s):  
Power Systems ◽  
Power System ◽  
Distribution Systems ◽  
Fault Location ◽  
Comprehensive Evaluation ◽  
Distribution Networks ◽  
Test System ◽  
Lightning Strike ◽  
Location Methods ◽  
The Impact

Since recent societies become more hooked into electricity, a higher level of power supply continuity is required from power systems. The expansion of those systems makes them liable to electrical faults and several failures are raised due to totally different causes, like the lightning strike, power system element failure caused by mechanical aging as well as human mistakes. These conditions impact the stability of the power as well as lead to costly maintenance and loss of output. This article examines the latest technologies and strategies to determine the location of faults in medium voltage distribution systems. The aim is to classify and assess different strategies in order to determine the best recommended models in practice or for further improvement. Several ways to locate failures in distribution networks have therefore been established. Because faults are unpredictable, quick fault location as well as isolating are necessary to reduce the impact of faults in distribution networks as well as removing the emergency condition from the entire system. This study also includes a comprehensive evaluation of several defect location methods depending on the algorithm employed, the input, the test system, the characteristics retrieved, and the degree of complexity. In order to gain further insight into the strengths and limitations of each method and also comparative analysis is carried out. Then the main problems of the fault location methods in distribution network are briefly expounded

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