Pub Date : 2023-08-29DOI: 10.13052/dgaej2156-3306.3863
Gou Yu
In the impartial factor ungrounded system, ferromagnetic resonance overvoltage is a frequent fault that lasts for a lengthy time and is hazardous to the grid. In this paper, the mechanism of grid ferromagnetic resonance overvoltage is first explored in depth. The precept of impartial voltage shift and ferromagnetic resonance brought about through PT saturation is analyzed with the aid of graphical and mathematical analysis. Then, the characteristics of fault current information are extracted by wavelet transform, and indicators such as wavelet fault degree, wavelet singularity and wavelet energy measurement are obtained respectively. D-S evidence theory is used to fuse multi-source information of electrical volume and switching quantity, so as to obtain comprehensive fault results of power grid more accurately. Finally, based on the time series risk assessment, the distribution network time series risk index is calculated, the risk level and risk area of each period are determined, and the early warning results are issued. Finally, an example is given to verify the effectiveness of the proposed method.
{"title":"Early Warning Analysis of Grid Ferromagnetic Resonance Overvoltage Risk Based on Multi-source Data","authors":"Gou Yu","doi":"10.13052/dgaej2156-3306.3863","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3863","url":null,"abstract":"In the impartial factor ungrounded system, ferromagnetic resonance overvoltage is a frequent fault that lasts for a lengthy time and is hazardous to the grid. In this paper, the mechanism of grid ferromagnetic resonance overvoltage is first explored in depth. The precept of impartial voltage shift and ferromagnetic resonance brought about through PT saturation is analyzed with the aid of graphical and mathematical analysis. Then, the characteristics of fault current information are extracted by wavelet transform, and indicators such as wavelet fault degree, wavelet singularity and wavelet energy measurement are obtained respectively. D-S evidence theory is used to fuse multi-source information of electrical volume and switching quantity, so as to obtain comprehensive fault results of power grid more accurately. Finally, based on the time series risk assessment, the distribution network time series risk index is calculated, the risk level and risk area of each period are determined, and the early warning results are issued. Finally, an example is given to verify the effectiveness of the proposed method.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82958064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-29DOI: 10.13052/dgaej2156-3306.3864
Hanumanthu Kesari, N. Kumaresan
A system comprising of a hydraulic turbine (HT) driven induction generator with excitation capacitor (IGEC) has been proposed for providing electricity to the residents living in remote areas and steep terrains, wherein the grid connection is unviable. The available water resource in such locations is effectively utilized and the load on the generator terminals is set, based on the requirement of the consumer demand. A method has been formulated for the estimation of excitation capacitor and rotor speed for ensuring nominal voltage and frequency at the generator terminals, regardless of variation in the consumer load. This design procedure is based on the analysis of IGEC employing the binary search algorithm (BSA). The logical way of arriving at the range of per unit (pu) speed to start the BSA has also been illustrated. A closed-loop control scheme has also been formulated, by taking generator voltage as the feedback variable and comparing the voltage set limits Vmin and Vmax. Accordingly, a controller action is initiated to add or disconnect the flexible loads. An available mathematical modeling of HT has been modified suitably and by using this model, the functioning of the proposed system with respect to the HT characteristics and generated frequency of IGEC has also been investigated. Using a MATLAB/Simulink software, the successful functioning of the proposed system has been demonstrated with typical operating conditions. The predetermined values and simulated observations are amply supported with the laboratory results conducted on a 3-phase, 3.7 kW IGEC.
{"title":"A Novel Control Scheme for Induction Generator Based Stand-alone Micro Hydro Power Plants","authors":"Hanumanthu Kesari, N. Kumaresan","doi":"10.13052/dgaej2156-3306.3864","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3864","url":null,"abstract":"A system comprising of a hydraulic turbine (HT) driven induction generator with excitation capacitor (IGEC) has been proposed for providing electricity to the residents living in remote areas and steep terrains, wherein the grid connection is unviable. The available water resource in such locations is effectively utilized and the load on the generator terminals is set, based on the requirement of the consumer demand. A method has been formulated for the estimation of excitation capacitor and rotor speed for ensuring nominal voltage and frequency at the generator terminals, regardless of variation in the consumer load. This design procedure is based on the analysis of IGEC employing the binary search algorithm (BSA). The logical way of arriving at the range of per unit (pu) speed to start the BSA has also been illustrated. A closed-loop control scheme has also been formulated, by taking generator voltage as the feedback variable and comparing the voltage set limits Vmin and Vmax. Accordingly, a controller action is initiated to add or disconnect the flexible loads. An available mathematical modeling of HT has been modified suitably and by using this model, the functioning of the proposed system with respect to the HT characteristics and generated frequency of IGEC has also been investigated. Using a MATLAB/Simulink software, the successful functioning of the proposed system has been demonstrated with typical operating conditions. The predetermined values and simulated observations are amply supported with the laboratory results conducted on a 3-phase, 3.7 kW IGEC.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"99 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78390400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The effective planning of active distribution networks is crucial for utility companies to make informed decisions regarding investments in distributed generation, reliability assessment, reactive power planning, substation revisions, and feeder repositioning. However, the dynamic nature of the solution space makes it challenging for model-based optimization methods to ensure computational performance in active distribution network planning. To address this issue, this study proposes a planning method that focuses on improving computational performance through the continuous updating of the planning model’s solution space during the reinforcement learning training process. Based on simulations conducted on the IEEE 33-bus test system, the proposed planning strategy successfully enhances computational performance while minimizing investment costs compared to other strategies. With the proposed method, the investment cost and the operation cost are reduced by 32.42% and 23.91%, respectively.
{"title":"A Multi-objective Optimization Planning Framework for Active Distribution System Via Reinforcement Learning","authors":"Hongtao Li, Cunping Wang, Hao Tian, Zhigang Ren, Ergang Zhao, Lina Xu","doi":"10.13052/dgaej2156-3306.3862","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3862","url":null,"abstract":"The effective planning of active distribution networks is crucial for utility companies to make informed decisions regarding investments in distributed generation, reliability assessment, reactive power planning, substation revisions, and feeder repositioning. However, the dynamic nature of the solution space makes it challenging for model-based optimization methods to ensure computational performance in active distribution network planning. To address this issue, this study proposes a planning method that focuses on improving computational performance through the continuous updating of the planning model’s solution space during the reinforcement learning training process. Based on simulations conducted on the IEEE 33-bus test system, the proposed planning strategy successfully enhances computational performance while minimizing investment costs compared to other strategies. With the proposed method, the investment cost and the operation cost are reduced by 32.42% and 23.91%, respectively.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87294086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-29DOI: 10.13052/dgaej2156-3306.3866
S. Sundarajoo, D. Soomro
Due to the growth of electric power demand and the intricacy of modern distribution system structure, the voltage stability issue is evolving as a critical problem in distribution grids. Therefore, it is imperative to investigate the corrective measures. In this paper, artificial neural network (ANN) based voltage stability online monitoring approach for distribution systems with distribution generators (DGs) is proposed. The proposed technique employs a local voltage stability index known as the stability index (SI) to identify the weak bus information, which is more effective compared to the conventional load margin techniques. Furthermore, the nonlinear relationship of the distribution grid control status and the resultant SI is mapped using ANN. From the installed distribution-level phasor measurement units (PMUs), the state parameters of buses can be obtained, and the resultant values of SI can be estimated. This approach can significantly enhance the computational speed of SI and evaluate the voltage stability measurement of distribution network in real-time, which assist the operator of the network in order to determine the operational condition and execute actions quickly. The proposed approach is applied on the modified IEEE 33 and IEEE 69-bus system with DGs. It is found that the computation time needed for assessment of voltage stability by CPF method is 16.2500 s and 21.8872 s whilst the computation time needed for the proposed method for the same assessment is 0.0677 s and 0.0749 s respectively for modified IEEE 33 and IEEE 69-bus system. This demonstrates that the proposed method has high accuracy and efficacy.
{"title":"Artificial Neural Network-Based Voltage Stability Online Monitoring Approach for Distributed Generation Integrated Distribution System","authors":"S. Sundarajoo, D. Soomro","doi":"10.13052/dgaej2156-3306.3866","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3866","url":null,"abstract":"Due to the growth of electric power demand and the intricacy of modern distribution system structure, the voltage stability issue is evolving as a critical problem in distribution grids. Therefore, it is imperative to investigate the corrective measures. In this paper, artificial neural network (ANN) based voltage stability online monitoring approach for distribution systems with distribution generators (DGs) is proposed. The proposed technique employs a local voltage stability index known as the stability index (SI) to identify the weak bus information, which is more effective compared to the conventional load margin techniques. Furthermore, the nonlinear relationship of the distribution grid control status and the resultant SI is mapped using ANN. From the installed distribution-level phasor measurement units (PMUs), the state parameters of buses can be obtained, and the resultant values of SI can be estimated. This approach can significantly enhance the computational speed of SI and evaluate the voltage stability measurement of distribution network in real-time, which assist the operator of the network in order to determine the operational condition and execute actions quickly. The proposed approach is applied on the modified IEEE 33 and IEEE 69-bus system with DGs. It is found that the computation time needed for assessment of voltage stability by CPF method is 16.2500 s and 21.8872 s whilst the computation time needed for the proposed method for the same assessment is 0.0677 s and 0.0749 s respectively for modified IEEE 33 and IEEE 69-bus system. This demonstrates that the proposed method has high accuracy and efficacy.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"108 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79186742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.13052/dgaej2156-3306.38511
Gong Mengting
Economic Environmental Dispatching (EED) in power systems is a multi-variable, strongly constrained, non-convex, multi-objective optimization problem that is difficult to properly handle using traditional methods. However, the application of particle swarm optimization algorithms may result in insufficient population diversity and easy to fall into local optimization problems. Therefore, this paper proposes an adaptive backbone multi-objective particle swarm optimization (ABBMOPSO) method to solve the economic and environmental scheduling problems of power systems. This paper first analyzes the topology and computational flow of particle swarm optimization algorithms, and then constructs a multi-objective optimization research framework that integrates Pareto optimization principles for the scheduling of power generation units. The execution algorithm is the improved multi-objective particle swarm optimization algorithm (MOPSO). This paper establishes a mathematical model for the economic and environmental scheduling of power systems, which optimizes conflicting fuel cost functions and pollutant emission functions simultaneously, taking into account nonlinear constraints such as load balance constraints and unit operation constraints. The improved ABBMOPSO algorithm is used to optimize the solution to improve the global search ability of the EED model. The simulation data of seven units show that the ABBMOPSO algorithm has a minimum power generation cost of 588.1 $/h and a minimum pollutant emission of 0.192 t/h, which is significantly superior to other algorithms and reduces the number of iterations, with good feasibility.
{"title":"Multi-objective Optimal Scheduling Analysis of Power System Based on Improved Particle Swarm Algorithm","authors":"Gong Mengting","doi":"10.13052/dgaej2156-3306.38511","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.38511","url":null,"abstract":"Economic Environmental Dispatching (EED) in power systems is a multi-variable, strongly constrained, non-convex, multi-objective optimization problem that is difficult to properly handle using traditional methods. However, the application of particle swarm optimization algorithms may result in insufficient population diversity and easy to fall into local optimization problems. Therefore, this paper proposes an adaptive backbone multi-objective particle swarm optimization (ABBMOPSO) method to solve the economic and environmental scheduling problems of power systems. This paper first analyzes the topology and computational flow of particle swarm optimization algorithms, and then constructs a multi-objective optimization research framework that integrates Pareto optimization principles for the scheduling of power generation units. The execution algorithm is the improved multi-objective particle swarm optimization algorithm (MOPSO). This paper establishes a mathematical model for the economic and environmental scheduling of power systems, which optimizes conflicting fuel cost functions and pollutant emission functions simultaneously, taking into account nonlinear constraints such as load balance constraints and unit operation constraints. The improved ABBMOPSO algorithm is used to optimize the solution to improve the global search ability of the EED model. The simulation data of seven units show that the ABBMOPSO algorithm has a minimum power generation cost of 588.1 $/h and a minimum pollutant emission of 0.192 t/h, which is significantly superior to other algorithms and reduces the number of iterations, with good feasibility.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76561446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.13052/dgaej2156-3306.3853
R. Tiwari, Rahul Kumar, O. Gupta, V. Sood
VSC-HVDC systems are widely used to integrate wind farms, asynchronous generations and networks operating at different frequencies. The Multi-terminal (MT) and multi-fed (MF) HVDC’s are the system mainly constituted of VSC’s, to integrate renewable sources and transmitting bulk power to conventional AC grids. A sudden change in the steady state even in adjacent networks may create severe disturbances in the operation of such HVDC systems. The disturbances in AC or DC networks directly influence the performance of systems, particularly in MT-HVDC and MF-HVDC systems. However, the HVDC systems are known for their intelligent control in modulating operational states as and when required. This paper presents the dynamic analysis of MF-HVDC system due to load changes, faults and other disturbances in the adjacent AC networks. The result indicates that VSC-HVDC provides decoupled control of active and reactive power with capability in adjusting operational mode during various minor and major disturbances. Based on the results obtained, the paper proposed a novel sensitivity factor indicating percentage coupling among various line parameters during disturbances. Furthermore, the VSC’s injects harmonic signals on both AC and DC sides of HVDC system. These harmonics voltage or currents signals may get amplified to a dangerously high magnitude at resonance frequencies. Thus, the frequency characteristics of different subsystems are also analyzed using FFT. A ±100 kV, 200 MW bipolar MF VSC-HVDC test systems is used to simulated the results in MATLAB/Simulink software.
{"title":"Dynamic Analysis of VSC-HVDC System with Disturbances in the Adjacent AC Networks","authors":"R. Tiwari, Rahul Kumar, O. Gupta, V. Sood","doi":"10.13052/dgaej2156-3306.3853","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3853","url":null,"abstract":"VSC-HVDC systems are widely used to integrate wind farms, asynchronous generations and networks operating at different frequencies. The Multi-terminal (MT) and multi-fed (MF) HVDC’s are the system mainly constituted of VSC’s, to integrate renewable sources and transmitting bulk power to conventional AC grids. A sudden change in the steady state even in adjacent networks may create severe disturbances in the operation of such HVDC systems. The disturbances in AC or DC networks directly influence the performance of systems, particularly in MT-HVDC and MF-HVDC systems. However, the HVDC systems are known for their intelligent control in modulating operational states as and when required. This paper presents the dynamic analysis of MF-HVDC system due to load changes, faults and other disturbances in the adjacent AC networks. The result indicates that VSC-HVDC provides decoupled control of active and reactive power with capability in adjusting operational mode during various minor and major disturbances. Based on the results obtained, the paper proposed a novel sensitivity factor indicating percentage coupling among various line parameters during disturbances. Furthermore, the VSC’s injects harmonic signals on both AC and DC sides of HVDC system. These harmonics voltage or currents signals may get amplified to a dangerously high magnitude at resonance frequencies. Thus, the frequency characteristics of different subsystems are also analyzed using FFT. A ±100 kV, 200 MW bipolar MF VSC-HVDC test systems is used to simulated the results in MATLAB/Simulink software.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73029562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.13052/dgaej2156-3306.3857
Md Irfan Ahmed, Ramesh Kumar
The prediction of nodal electricity price (NEP) is a primary step to be done before the bidding process starts in the actual market environment. NEP plays a significant role for the efficient working of the electrical system. NEP follows a common trend as during peak hours when the load is high the price will also be high similarly during off-peak-load times the price will be lower and common to all the node. Thus, accurate forecasting of the NEP can help electricity generation companies to be more proactive in the wholesale electricity market to maximize its overall benefits. In this paper, exponential smoothing (ES), and holt’s exponential smoothing (HES) have been utilized for forecasting the NEP. Furthermore, a comparative analysis between ES and HES has been done considering several alpha values and several trends. The model evaluation and the forecasting performance have been tested using different parameters of ES, and HES techniques such as Akaike Information Criterion (AIC), Akaike Information Criterion Corrected (AICc), Bayesian Information Criteria (BIC). The performance of the proposed technique has been authenticated efficaciously on average nodal real-time price data collected from ISO New England (BOSTON Zone).
{"title":"Nodal Electricity Price Forecasting using Exponential Smoothing and Holt’s Exponential Smoothing","authors":"Md Irfan Ahmed, Ramesh Kumar","doi":"10.13052/dgaej2156-3306.3857","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3857","url":null,"abstract":"The prediction of nodal electricity price (NEP) is a primary step to be done before the bidding process starts in the actual market environment. NEP plays a significant role for the efficient working of the electrical system. NEP follows a common trend as during peak hours when the load is high the price will also be high similarly during off-peak-load times the price will be lower and common to all the node. Thus, accurate forecasting of the NEP can help electricity generation companies to be more proactive in the wholesale electricity market to maximize its overall benefits. In this paper, exponential smoothing (ES), and holt’s exponential smoothing (HES) have been utilized for forecasting the NEP. Furthermore, a comparative analysis between ES and HES has been done considering several alpha values and several trends. The model evaluation and the forecasting performance have been tested using different parameters of ES, and HES techniques such as Akaike Information Criterion (AIC), Akaike Information Criterion Corrected (AICc), Bayesian Information Criteria (BIC). The performance of the proposed technique has been authenticated efficaciously on average nodal real-time price data collected from ISO New England (BOSTON Zone).","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88674675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.13052/dgaej2156-3306.3855
Achintya Sharma, A. Shukla, O. Singh, M. Sharma
The energy consumption has gradually increased in the current context. Fossil fuels are the primary source of energy for the world’s population. Furthermore, energy derived from fossil fuels has significant disadvantages, including increased pollution and global warming. Solar energy is the fastest-growing alternative to fossil fuels among the various energy options. As a result, the focus of the present work is on the thermo-economic analysis of a hybrid solar-assisted intercooled gas turbine (GT) and organic Rankine cycle (ORC) for waste heat recovery and power production at near-zero-emissions. The work outcome and maximum efficiency of the hybrid arrangement are 1342.12 kW and 71.12% respectively at the cycle pressure ratio of 8, and 443 K entry point turbine temperature. The economic model of the integrated system depicts that the unit power production cost for the combined system has been evaluated as 1932 e per kW.
{"title":"Parametric Analysis of the Solar-assisted Intercooled Gas Turbine and Organic Rankine Cycle for Waste Heat Recovery and Power Production","authors":"Achintya Sharma, A. Shukla, O. Singh, M. Sharma","doi":"10.13052/dgaej2156-3306.3855","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3855","url":null,"abstract":"The energy consumption has gradually increased in the current context. Fossil fuels are the primary source of energy for the world’s population. Furthermore, energy derived from fossil fuels has significant disadvantages, including increased pollution and global warming. Solar energy is the fastest-growing alternative to fossil fuels among the various energy options. As a result, the focus of the present work is on the thermo-economic analysis of a hybrid solar-assisted intercooled gas turbine (GT) and organic Rankine cycle (ORC) for waste heat recovery and power production at near-zero-emissions. The work outcome and maximum efficiency of the hybrid arrangement are 1342.12 kW and 71.12% respectively at the cycle pressure ratio of 8, and 443 K entry point turbine temperature. The economic model of the integrated system depicts that the unit power production cost for the combined system has been evaluated as 1932 e per kW.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76182634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.13052/dgaej2156-3306.38510
Bikash Kumar Saw, Aashish Kumar Bohre, Jalpa Thakkar, M. Kolhe
A Multi Objective based Fitness Function (MOFF) is proposed for the optimum planning of multiple Solar Distributed Generation (SDG) and DSTATCOM with radial distribution network (RDN) reconfiguration impact for techno-economic and environmental benefit improvement. The Adaptive-Particle Swarm Optimization (APSO) and Teaching-Learning Based Optimization techniques (TLBO) are employed to accomplish this work. In the proposed MOFF, the Active Power Loss (APLoss), Reactive Power Loss (RPLoss), System Voltage Deviation (SVD), Fault-Current Level-of-Line (FCLLine), and System Service Reliability (SSR) are considered. The economic-benefit measures along with Environmental Emissions Components (EEC) impact have also been considered in light of various system costs such as Fixed Capital Recovery Cost (FCRCost), Energy Loss Cost (ELCost) and Energy Not Supplied Cost (ENSCost). The novelty in the MOFF is the simultaneous consideration of FCLLine with APLoss, RPLoss, SVD, and SSR along with EEC impact calculation. The IEEE 69 and 118 bus RDN is considered with three case studies to demonstrate the proposed methodology's usefulness. The result analysis reveals that better performances can be obtained based on the considered MOFF in terms of environment-friendly techno-economic perspective, consistency, convergence, and computation time using TLBO rather than APSO.
{"title":"Techno-Economic and Environmental Based Approach for Planning of SDG and DSTATCOM with Impact of Network Reconfiguration using APSO and TLBO","authors":"Bikash Kumar Saw, Aashish Kumar Bohre, Jalpa Thakkar, M. Kolhe","doi":"10.13052/dgaej2156-3306.38510","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.38510","url":null,"abstract":"A Multi Objective based Fitness Function (MOFF) is proposed for the optimum planning of multiple Solar Distributed Generation (SDG) and DSTATCOM with radial distribution network (RDN) reconfiguration impact for techno-economic and environmental benefit improvement. The Adaptive-Particle Swarm Optimization (APSO) and Teaching-Learning Based Optimization techniques (TLBO) are employed to accomplish this work. In the proposed MOFF, the Active Power Loss (APLoss), Reactive Power Loss (RPLoss), System Voltage Deviation (SVD), Fault-Current Level-of-Line (FCLLine), and System Service Reliability (SSR) are considered. The economic-benefit measures along with Environmental Emissions Components (EEC) impact have also been considered in light of various system costs such as Fixed Capital Recovery Cost (FCRCost), Energy Loss Cost (ELCost) and Energy Not Supplied Cost (ENSCost). The novelty in the MOFF is the simultaneous consideration of FCLLine with APLoss, RPLoss, SVD, and SSR along with EEC impact calculation. The IEEE 69 and 118 bus RDN is considered with three case studies to demonstrate the proposed methodology's usefulness. The result analysis reveals that better performances can be obtained based on the considered MOFF in terms of environment-friendly techno-economic perspective, consistency, convergence, and computation time using TLBO rather than APSO. ","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82288150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.13052/dgaej2156-3306.3859
Krishna Kumba, S. P. Simon, K. Sundareswaran, P. S. R. Nayak
This article presented the comparative study of the second-class lever principle single-axis solar tracking system (SCLPSAST) with the fixed solar axis (FSA) system. The SCLPSAST system continuously tracks the sun regardless of atmospheric conditions from sunrise to sunset. This SCLPSAST system is a cost effective and straightforward solar tracking system built with negligible operational costs. The Photovoltaic (PV) panel are directed towards the sun throughout the year without using any additional power. The main advantage is that an external motor is not required to control the solar panel. A detailed performance evaluation of the SCLPSAST system is carried out for 90 days (from Jan 2022 to Mar 2022) with the FSA system. Finally, the working functionality, efficiency improvement, and experimental consequences of the SCLPSAST system are detailed. SCLPSAST and the fixed solar system generated 8.92 kWh and 7.03 kWh, respectively, which is around 26.87% more energy than the FSA system.
{"title":"Comparative Evaluation of Second-Class Lever Principle Based Single-Axis Solar Tracking System and Conventional System","authors":"Krishna Kumba, S. P. Simon, K. Sundareswaran, P. S. R. Nayak","doi":"10.13052/dgaej2156-3306.3859","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3859","url":null,"abstract":"This article presented the comparative study of the second-class lever principle single-axis solar tracking system (SCLPSAST) with the fixed solar axis (FSA) system. The SCLPSAST system continuously tracks the sun regardless of atmospheric conditions from sunrise to sunset. This SCLPSAST system is a cost effective and straightforward solar tracking system built with negligible operational costs. The Photovoltaic (PV) panel are directed towards the sun throughout the year without using any additional power. The main advantage is that an external motor is not required to control the solar panel. A detailed performance evaluation of the SCLPSAST system is carried out for 90 days (from Jan 2022 to Mar 2022) with the FSA system. Finally, the working functionality, efficiency improvement, and experimental consequences of the SCLPSAST system are detailed. SCLPSAST and the fixed solar system generated 8.92 kWh and 7.03 kWh, respectively, which is around 26.87% more energy than the FSA system.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"105 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76222860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：