scholarly journals Research on Renewable Energy Planning Considering the Flexible Region of the Microgrid

2020 ◽  
Vol 10 (21) ◽  
pp. 7544
Author(s):  
Dan Su ◽  
Kaicheng Li ◽  
Nian Shi
Keyword(s):  
Renewable Energy ◽  
System Reliability ◽  
Optimal Allocation ◽  
Test System ◽  
Energy Planning ◽  
Distributed Energy ◽  
Random Load ◽  
Allocation Model ◽  
Distributed Generations ◽  
Flexible Region

A microgrid can effectively improve the system reliability of a distribution network. When a fault occurs, the microgrid only has a determined division scheme under a fixed boundary method, and it is difficult to adapt to the random load and distributed power. In this paper, a novel renewable energy planning method considering the flexible region of the microgrid is proposed. Based on the randomness of the load and the output of distributed generations (DG) in the microgrid, the dynamic division method of the microgrid is proposed and the optimal allocation model of the distributed energy in the microgrid is established. Further, the model and method proposed are verified by the IEEE-33 bus test system. The simulation results show that the allocation of renewable energy in the microgrid considering the flexible region of the microgrid can effectively increase the utilization of renewable energy and improve the reliability of microgrid operation.

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 Optimal Allocation of Distributed Energy Supply System Under Uncertainty Based Improved Gray Wolf Algorithm

2021 ◽  
Author(s):  
Xiao Xue ◽  
Yangbing Zheng ◽  
Chao Lu
Keyword(s):  
Energy Supply ◽  
Optimal Allocation ◽  
Supply System ◽  
Research Progress ◽  
Maintenance Cost ◽  
Gray Wolf ◽  
Distributed Energy ◽  
Allocation Model ◽  
Penalty Cost ◽  
Energy Supply System

In order to improve the economical performance of distributed energy supply system under uncertainty, the improved gray wolf algorithm is constructed for optimal allocation of distributed energy supply system. The relating research progress is summarized firstly, and effect of improved gray wolf algorithm on optimal allocation of distributed energy supply system are studied. The optimal allocation model of distributed energy supply system is constructed considering fuel consumption, operation and maintenance cost, environment penalty cost, and power grid energy exchange function, and the uncertain factor is processed based on scienario method. And then the improved gray wolf algorithm is designed, and the initial strategy of population and the regulated method of main parameters are improved. Finally, simulation analysis is carried out, simulation results show that the proposed model can obtain best optimal allocation effect of system.

scholarly journals Short-Term Cooperative Operational Scheme of Distribution System with High Hosting Capacity of Renewable-Energy-Based Distributed Generations

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6340
Author(s):  
Chan-Hyeok Oh ◽  
Joon-Ho Choi ◽  
Sang-Yun Yun ◽  
Seon-Ju Ahn
Keyword(s):  
Renewable Energy ◽  
Power Output ◽  
Distribution System ◽  
Renewable Energy Sources ◽  
Test System ◽  
Network Reconfiguration ◽  
Short Term ◽  
Distributed Generations ◽  
Operation Method ◽  
Output Fluctuations

As the interconnection of renewable-energy-based distributed generations (DGs) to the distribution system increases, the local and temporary voltage and current problems, which are difficult to resolve with the existing operation method, are becoming serious. In this study, we propose a short-term operational method that can effectively resolve voltage and current violations caused by instantaneous output fluctuations of DGs in a system with a high hosting capacity of renewable energy sources. To achieve the objectives, a modified heuristic network reconfiguration method, and a method determining the maximum power output limit of individual DGs are proposed. We propose a cooperative method for controlling the power output fluctuations of renewable-energy-based DGs, which includes voltage control, network reconfiguration, and power curtailment. The proposed algorithm was verified through case studies by using a test system implemented in MATLAB environments. It can effectively resolve violations caused by DGs while minimizing the number of switching operations and power curtailment. The proposed method is an appropriate operation method to be applied to the real system as it can cope with the instantaneous output fluctuation of DGs, which was not dealt with in the existing operation method.

scholarly journals Optimal Allocation of Renewable Energy Hybrid Distributed Generations for Small-Signal Stability Enhancement

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4777 ◽  
Author(s):  
Olusayo A. Ajeigbe ◽  
Josiah L. Munda ◽  
Yskandar Hamam
Keyword(s):  
Renewable Energy ◽  
Distribution Systems ◽  
Optimal Allocation ◽  
Mixed Integer ◽  
Small Signal ◽  
Small Signal Stability ◽  
Distributed Generations ◽  
Signal Stability ◽  
Dynamic Voltage ◽  
The Impact

This paper solves the allocation planning problem of integrating large scale renewable energy hybrid distributed generations and capacitor banks into the distribution systems. Extraordinarily, the integration of renewable energy hybrid distributed generations such as solar photovoltaic, wind, and biomass takes into consideration the impact assessment of variable generations from PV and wind on the distribution networks’ long term dynamic voltage and small-signal stabilities. Unlike other renewable distributed generations, the variability of power from solar PV and wind generations causes small-signal instabilities if they are sub-optimally allocated in the distribution network. Hence, the variables related to small-signal stability are included and constrained in the model, unlike what is obtainable in the current works on the planning of optimal allocation of renewable distributed generations. Thus, the model is motivated to maximize the penetration of renewable powers by minimizing the net present value of total cost, which includes investment, maintenance, energy, and emission costs. Consequently, the optimization problem is formulated as a stochastic mixed integer linear program, which ensures limited convergence to optimality. Numerical results of the proposed model demonstrate a significant reduction in electricity and emission costs, enhancement of system dynamic voltage and small-signal stabilities, as well as improvement in welfare costs and environmental goodness.

scholarly journals Methodology for Implementing the State Estimation in Renewable Energy Management Systems

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2301
Author(s):  
Yun-Sung Cho ◽  
Yun-Hyuk Choi
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
State Estimation ◽  
Measurement Errors ◽  
Large Scale ◽  
Test System ◽  
The State ◽  
Inner Function ◽  
Outer Function ◽  
Bad Data

This paper describes a methodology for implementing the state estimation and enhancing the accuracy in large-scale power systems that partially depend on variable renewable energy resources. To determine the actual states of electricity grids, including those of wind and solar power systems, the proposed state estimation method adopts a fast-decoupled weighted least square approach based on the architecture of application common database. Renewable energy modeling is considered on the basis of the point of data acquisition, the type of renewable energy, and the voltage level of the bus-connected renewable energy. Moreover, the proposed algorithm performs accurate bad data processing using inner and outer functions. The inner function is applied to the largest normalized residue method to process the bad data detection, identification and adjustment. While the outer function is analyzed whether the identified bad measurements exceed the condition of Kirchhoff’s current law. In addition, to decrease the topology and measurement errors associated with transformers, a connectivity model is proposed for transformers that use switching devices, and a transformer error processing technique is proposed using a simple heuristic method. To verify the performance of the proposed methodology, we performed comprehensive tests based on a modified IEEE 18-bus test system and a large-scale power system that utilizes renewable energy.

Optimal fault location for power distribution systems with distributed generations using synchronized measurements

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Wen Fan ◽  
Yuan Liao ◽  
Ning kang
Keyword(s):  
Power Distribution ◽  
Distribution Systems ◽  
Fault Location ◽  
Test System ◽  
Power Distribution Systems ◽  
Distributed Generations ◽  
High Penetration ◽  
Maintenance Time ◽  
Phasor Measurements ◽  
Synchronized Measurements

AbstractAccurate fault location in distribution systems greatly shortens maintenance time and improves reliability. This paper presents novel methods to pinpoint fault location and identify possible bad measurements for enhanced accuracy. It is assumed that network parameters and topology of the distribution network are available. The methods are applicable to a single fault as well as simultaneous faults and are applicable to both balanced and unbalanced networks. The methods utilize synchronized voltage and current phasor measurements to locate the fault. The methods are validated by simulation studies using the modified IEEE 34-Node Test System. Case studies have demonstrated that the methods are suitable for distribution systems with high penetration of distributed generations.

scholarly journals Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework

2021 ◽  
Vol 11 (9) ◽  
pp. 3814
Author(s):  
Poushali Pal ◽  
Parvathy Ayalur Krishnamoorthy ◽  
Devabalaji Kaliaperumal Rukmani ◽  
S. Joseph Antony ◽  
Simon Ocheme ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Virtual Power ◽  
Distributed Energy ◽  
Distribution Method ◽  
Virtual Power Plant ◽  
Optimal Dispatch ◽  
Market Framework

Renewable energy sources prevail as a clean energy source and their penetration in the power sector is increasing day by day due to the growing concern for climate action. However, the intermittent nature of the renewable energy based-power generation questions the grid security, especially when the utilized source is solar radiation or wind flow. The intermittency of the renewable generation can be met by the integration of distributed energy resources. The virtual power plant (VPP) is a new concept which aggregates the capacities of various distributed energy resources, handles controllable and uncontrollable loads, integrates storage devices and empowers participation as an individual power plant in the electricity market. The VPP as an energy management system (EMS) should optimally dispatch the power to its consumers. This research work is proposed to analyze the optimal scheduling of generation in VPP for the day-ahead market framework using the beetle antenna search (BAS) algorithm under various scenarios. A case study is considered for this analysis in which the constituting energy resources include a photovoltaic solar panel (PV), micro-turbine (MT), wind turbine (WT), fuel cell (FC), battery energy storage system (BESS) and controllable loads. The real-time hourly load curves are considered in this work. Three different scenarios are considered for the optimal dispatch of generation in the VPP to analyze the performance of the proposed technique. The uncertainties of the solar irradiation and the wind speed are modeled using the beta distribution method and Weibull distribution method, respectively. The performance of the proposed method is compared with other evolutionary algorithms such as particle swarm optimization (PSO) and the genetic algorithm (GA). Among these above-mentioned algorithms, the proposed BAS algorithm shows the best scheduling with the minimum operating cost of generation.

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 Reliability Evaluation of Smart Microgrids Considering Cyber Failures and Disturbances under Various Cyber Network Topologies and Distributed Generation’s Scenarios

2021 ◽  
Vol 13 (10) ◽  
pp. 5695
Author(s):  
Mehrdad Aslani ◽  
Hamed Hashemi-Dezaki ◽  
Abbas Ketabi
Keyword(s):  
Smart Grids ◽  
Reliability Evaluation ◽  
Assessment Method ◽  
Test System ◽  
Efficient System ◽  
Control Center ◽  
Distributed Generations ◽  
Network Topologies ◽  
Physical Features ◽  
Microgrid Control

Smart microgrids (SMGs), as cyber–physical systems, are essential parts of smart grids. The SMGs’ cyber networks facilitate efficient system operation. However, cyber failures and interferences might adversely affect the SMGs. The available studies about SMGs have paid less attention to SMGs’ cyber–physical features compared to other subjects. Although a few current research works have studied the cyber impacts on SMGs’ reliability, there is a research gap about reliability evaluation simultaneously concerning all cyber failures and interferences under various cyber network topologies and renewable distributions scenarios. This article aims to fill such a gap by developing a new Monte Carlo simulation-based reliability assessment method considering cyber elements’ failures, data/information transmission errors, and routing errors under various cyber network topologies. Considering the microgrid control center (MGCC) faults in comparion to other failures and interferences is one of the major contributions of this study. The reliability evaluation of SMGs under various cyber network topologies, particularly based on an MGCC’s redundancy, highlights this research’s advantages. Moreover, studying the interactions of uncertainties for cyber systems and distributed generations (DGs) under various DG scenarios is another contribution. The proposed method is applied to a test system using actual historical data. The comparative test results illustrate the advantages of the proposed method.

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