The conventional adaptive full-order observer-based speed sensorless control method for induction motor is prone to instability at low-speed region as improper feedback gain matrix and imprecise speed adaptive law are often used. To address these problems, a new feedback gain matrix design approach as well as a new speed adaptive law design technique are proposed in this paper. Firstly, considering that the d-axis current estimation error in the traditional feedback gain matrix design method has a great influence on the stability of the speed estimation algorithm, especially at low speeds, a new feedback gain matrix design method is proposed to minimize the d-axis current estimation error. Secondly, a new speed adaptive law design technique is studied based on the conventional method, which only requires the d-axis and q-axis current estimation error with a weight coefficient to be designed, simplifying the conventional speed adaptive law. Thirdly, the transfer function from the speed observation error to the proposed adaptive error is analyzed by Routh stability criterion theory, and the weight coefficient suitable for full range stable operation is determined by MATLAB software. Fourthly, the stability of the proposed method in this paper is analyzed using the poles distribution maps. Finally, the proposed method is experimentally verified based on a 2.2 kW induction motor experimental platform. The experimental results show that the proposed method can make the induction motor operate steadily at low-speed and zero-speed region with rated load. In addition, the proposed method has better anti-disturbance performance than the existing method.
由于经常使用不恰当的反馈增益矩阵和不精确的速度自适应法则，传统的基于自适应全阶观测器的感应电机无速度传感器控制方法在低速区域容易出现不稳定。针对这些问题，本文提出了一种新的反馈增益矩阵设计方法和新的速度自适应律设计技术。首先，考虑到传统反馈增益矩阵设计方法中的 d 轴电流估计误差对速度估计算法的稳定性有很大影响，尤其是在低速情况下，因此提出了一种新的反馈增益矩阵设计方法，以最小化 d 轴电流估计误差。其次，在传统方法的基础上，研究了一种新的速度自适应律设计技术，该技术只需要设计带有权重系数的 d 轴和 q 轴电流估计误差，简化了传统的速度自适应律。第三，利用 Routh 稳定性准则理论分析了速度观测误差到拟议自适应误差的传递函数，并通过 MATLAB 软件确定了适合全范围稳定运行的权重系数。第四，利用极点分布图分析本文所提方法的稳定性。最后，基于 2.2 kW 异步电机实验平台对本文提出的方法进行了实验验证。实验结果表明，本文提出的方法能使感应电动机在额定负载下在低速和零速区域稳定运行。此外，与现有方法相比，所提出的方法具有更好的抗干扰性能。
{"title":"Sensorless control method of induction motors with new feedback gain matrix and speed adaptive law for low speed range","authors":"Leilei Guo, Shuai Wang, Yanyan Li, Xueyan Jin, Zhiyue Chu","doi":"10.1515/ijeeps-2024-0018","DOIUrl":"https://doi.org/10.1515/ijeeps-2024-0018","url":null,"abstract":"\u0000 The conventional adaptive full-order observer-based speed sensorless control method for induction motor is prone to instability at low-speed region as improper feedback gain matrix and imprecise speed adaptive law are often used. To address these problems, a new feedback gain matrix design approach as well as a new speed adaptive law design technique are proposed in this paper. Firstly, considering that the d-axis current estimation error in the traditional feedback gain matrix design method has a great influence on the stability of the speed estimation algorithm, especially at low speeds, a new feedback gain matrix design method is proposed to minimize the d-axis current estimation error. Secondly, a new speed adaptive law design technique is studied based on the conventional method, which only requires the d-axis and q-axis current estimation error with a weight coefficient to be designed, simplifying the conventional speed adaptive law. Thirdly, the transfer function from the speed observation error to the proposed adaptive error is analyzed by Routh stability criterion theory, and the weight coefficient suitable for full range stable operation is determined by MATLAB software. Fourthly, the stability of the proposed method in this paper is analyzed using the poles distribution maps. Finally, the proposed method is experimentally verified based on a 2.2 kW induction motor experimental platform. The experimental results show that the proposed method can make the induction motor operate steadily at low-speed and zero-speed region with rated load. In addition, the proposed method has better anti-disturbance performance than the existing method.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646959","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 : 2024-07-12DOI: 10.1515/ijeeps-2023-0485
Zhongpo Gao, Ao Yu
In order to achieve maximum carbon reduction during the operation of pure electric buses, the author proposes a re estimation of carbon emissions in international trade based on evolutionary algorithm analysis of electric vehicle green energy regeneration systems. On the basis of analyzing single line scheduling, the author focuses on studying the regional scheduling mode of pure electric buses, and establishes a multi-objective optimization model for pure electric bus regional scheduling considering carbon benefits with the goals of minimizing the number of operating vehicles, minimizing the empty distance, and maximizing carbon benefits. Based on the actual operation data of pure electric buses 146 and 149 in a certain city, the author used an improved particle swarm optimization algorithm to solve the regional scheduling problem of pure electric buses according to the characteristics of the model. The results indicate that assuming other conditions remain unchanged, when the price of diesel rises to around 7.9 yuan, its operating costs will exceed those of pure electric buses, and the cost advantage of diesel vehicles will gradually decrease. Other conditions remain unchanged, and when the battery price per vehicle drops to around 300,000 yuan, the operating cost of pure electric buses will be lower than that of diesel vehicles. Conclusion: Under the premise of considering carbon benefits, adopting regional dispatch mode for pure electric buses has better economic efficiency and is more conducive to the promotion of pure electric buses.
{"title":"Analysis of green energy regeneration system for Electric Vehicles and Re estimation of carbon emissions in international trade based on evolutionary algorithms","authors":"Zhongpo Gao, Ao Yu","doi":"10.1515/ijeeps-2023-0485","DOIUrl":"https://doi.org/10.1515/ijeeps-2023-0485","url":null,"abstract":"\u0000 In order to achieve maximum carbon reduction during the operation of pure electric buses, the author proposes a re estimation of carbon emissions in international trade based on evolutionary algorithm analysis of electric vehicle green energy regeneration systems. On the basis of analyzing single line scheduling, the author focuses on studying the regional scheduling mode of pure electric buses, and establishes a multi-objective optimization model for pure electric bus regional scheduling considering carbon benefits with the goals of minimizing the number of operating vehicles, minimizing the empty distance, and maximizing carbon benefits. Based on the actual operation data of pure electric buses 146 and 149 in a certain city, the author used an improved particle swarm optimization algorithm to solve the regional scheduling problem of pure electric buses according to the characteristics of the model. The results indicate that assuming other conditions remain unchanged, when the price of diesel rises to around 7.9 yuan, its operating costs will exceed those of pure electric buses, and the cost advantage of diesel vehicles will gradually decrease. Other conditions remain unchanged, and when the battery price per vehicle drops to around 300,000 yuan, the operating cost of pure electric buses will be lower than that of diesel vehicles. Conclusion: Under the premise of considering carbon benefits, adopting regional dispatch mode for pure electric buses has better economic efficiency and is more conducive to the promotion of pure electric buses.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141653525","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 : 2024-07-02DOI: 10.1515/ijeeps-2024-0147
Akash Abhisek, Chinmayee Biswal, P. Rout, G. Panda
Abstract In the era of smart grids and microgrids, the transformation of the traditional grid system brings many operational, technical, and economic benefits. However, the complexity of the network due to the integration of various distributed generations (DGs), continuous change of topology, and non-linear load make fault detection a major issue that forces power engineers to focus on. In this paper, a novel fault detection scheme is suggested based on the multivariate variational mode decomposition mode (MVMD) and differential cumulative sum (DCUSUM). As a generalized extension of the original variational mode decomposition (VMD) algorithm for multivariate data residing in multidimensional spaces, the main goal of MVMD is to decompose the input signal into different band-limited intrinsic mode functions (IMFs). Due to the inherent characteristics of being insensitive to noise and very effective in decomposing the local features even with similar frequencies, it is very effective for fault detection in microgrid distribution systems. The proposed DCUSUM algorithm computes the differential cumulative energy for the remaining significant modes. A fault detection index is considered in this approach and applied for fault detection by adaptively through the threshold setting to accurately result in fault detection. To justify the proposed approach, a standard AC microgrid test system is considered and the approach is verified for fault detection under various fault conditions and resistances. The obtained results and the comparative analysis with other methods reflect the better accuracy, robustness, and reliability of the proposed approach.
{"title":"Protection strategy for fault detection in AC microgrid based on MVMD & differential CUSUM","authors":"Akash Abhisek, Chinmayee Biswal, P. Rout, G. Panda","doi":"10.1515/ijeeps-2024-0147","DOIUrl":"https://doi.org/10.1515/ijeeps-2024-0147","url":null,"abstract":"Abstract In the era of smart grids and microgrids, the transformation of the traditional grid system brings many operational, technical, and economic benefits. However, the complexity of the network due to the integration of various distributed generations (DGs), continuous change of topology, and non-linear load make fault detection a major issue that forces power engineers to focus on. In this paper, a novel fault detection scheme is suggested based on the multivariate variational mode decomposition mode (MVMD) and differential cumulative sum (DCUSUM). As a generalized extension of the original variational mode decomposition (VMD) algorithm for multivariate data residing in multidimensional spaces, the main goal of MVMD is to decompose the input signal into different band-limited intrinsic mode functions (IMFs). Due to the inherent characteristics of being insensitive to noise and very effective in decomposing the local features even with similar frequencies, it is very effective for fault detection in microgrid distribution systems. The proposed DCUSUM algorithm computes the differential cumulative energy for the remaining significant modes. A fault detection index is considered in this approach and applied for fault detection by adaptively through the threshold setting to accurately result in fault detection. To justify the proposed approach, a standard AC microgrid test system is considered and the approach is verified for fault detection under various fault conditions and resistances. The obtained results and the comparative analysis with other methods reflect the better accuracy, robustness, and reliability of the proposed approach.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141688565","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 : 2024-07-01DOI: 10.1515/ijeeps-2024-0062
Sanaullah Kaka, Mingchao Xia, Arif Hussain, Kashif Zulfiqar
Abstract Distributed generators (DGs) have the potential to act as alternative power sources for balancing and restoring service in distribution system breakdowns. Nevertheless, DGs variety of characteristics and uncertain behavior pose difficulties in optimizing their operation while restoring the system. In this paper, a hierarchical structure is introduced to manage the unbalanced and islanded distribution networks with the optimal coordination strategy of DGs. The proposed approach encompasses multiple control tiers that manage DGs coordination process into three specific levels, each accountable for distinct functions involving voltage and frequency regulation, power distribution within individual islands, and overseeing power exchange between these units for minimizing imbalance and maximizing the load restoration. This research delivers a comprehensive solution for optimally coordinating DGs in unbalanced and isolated networks during restoration, thus elevating system reliability and resilience. The proposed model for distributed control restoration is validated using a modified IEEE 123-bus test setup.
{"title":"Optimal DGs coordination strategy for managing unbalanced and islanded distribution networks","authors":"Sanaullah Kaka, Mingchao Xia, Arif Hussain, Kashif Zulfiqar","doi":"10.1515/ijeeps-2024-0062","DOIUrl":"https://doi.org/10.1515/ijeeps-2024-0062","url":null,"abstract":"Abstract Distributed generators (DGs) have the potential to act as alternative power sources for balancing and restoring service in distribution system breakdowns. Nevertheless, DGs variety of characteristics and uncertain behavior pose difficulties in optimizing their operation while restoring the system. In this paper, a hierarchical structure is introduced to manage the unbalanced and islanded distribution networks with the optimal coordination strategy of DGs. The proposed approach encompasses multiple control tiers that manage DGs coordination process into three specific levels, each accountable for distinct functions involving voltage and frequency regulation, power distribution within individual islands, and overseeing power exchange between these units for minimizing imbalance and maximizing the load restoration. This research delivers a comprehensive solution for optimally coordinating DGs in unbalanced and isolated networks during restoration, thus elevating system reliability and resilience. The proposed model for distributed control restoration is validated using a modified IEEE 123-bus test setup.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141695892","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 : 2024-06-18DOI: 10.1515/ijeeps-2024-0138
Sankalpa Bohidar, R. Mallick, P. Nayak, Sairam Mishra, Narayan Nahak, G. Panda, P. Gouda
Abstract Integrating renewable energy sources like solar power into traditional power systems poses challenges. One such challenge is the effect of renewable power plants, which use power electronics, on the grid’s stability. Specifically, these plants can impact small-signal stability by either damping or exacerbating low-frequency oscillations. This paper introduces a novel Unified Power Flow Controller (UPFC) based damping controller specifically designed for Solar Photovoltaic (PV) integrated power systems. It employs an Arithmetic Optimization Algorithm (AOA) to optimize the UPFC damping controller parameters and mitigate low-frequency oscillations in the power system. The objective function minimizes the Integral Time Absolute Error (ITAE) of speed deviations under varying loading conditions. The proposed technique is utilized simultaneously to control the modulation index of series and phase angle of shunt converters of UPFC. The MATLAB/simulation results obtained effectively from the proposed technique which is actualized and identify both detrimental and beneficial impacts of increased PV penetration for small signal stability performance. The study reveals both the small-signal stability of the system and its response to large disturbances that alter the active power balance and frequency stability. The results of the analysis demonstrated with single and multimachine environment by comparing with the other optimizations like PSO, DE, DE-PSO and GWO, the proposed one is effective for damping out the oscillations. The effectiveness of the proposed damping controller is further confirmed through real-time validation using the OPAL-RT setup.
{"title":"Design of novel UPFC based damping controller for solar PV integrated power system using arithmetic optimization algorithm","authors":"Sankalpa Bohidar, R. Mallick, P. Nayak, Sairam Mishra, Narayan Nahak, G. Panda, P. Gouda","doi":"10.1515/ijeeps-2024-0138","DOIUrl":"https://doi.org/10.1515/ijeeps-2024-0138","url":null,"abstract":"Abstract Integrating renewable energy sources like solar power into traditional power systems poses challenges. One such challenge is the effect of renewable power plants, which use power electronics, on the grid’s stability. Specifically, these plants can impact small-signal stability by either damping or exacerbating low-frequency oscillations. This paper introduces a novel Unified Power Flow Controller (UPFC) based damping controller specifically designed for Solar Photovoltaic (PV) integrated power systems. It employs an Arithmetic Optimization Algorithm (AOA) to optimize the UPFC damping controller parameters and mitigate low-frequency oscillations in the power system. The objective function minimizes the Integral Time Absolute Error (ITAE) of speed deviations under varying loading conditions. The proposed technique is utilized simultaneously to control the modulation index of series and phase angle of shunt converters of UPFC. The MATLAB/simulation results obtained effectively from the proposed technique which is actualized and identify both detrimental and beneficial impacts of increased PV penetration for small signal stability performance. The study reveals both the small-signal stability of the system and its response to large disturbances that alter the active power balance and frequency stability. The results of the analysis demonstrated with single and multimachine environment by comparing with the other optimizations like PSO, DE, DE-PSO and GWO, the proposed one is effective for damping out the oscillations. The effectiveness of the proposed damping controller is further confirmed through real-time validation using the OPAL-RT setup.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334736","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 : 2024-06-17DOI: 10.1515/ijeeps-2024-0148
Santanu Borgohain, Sumant K. Dalai, Rangababu Peesapati, G. Panda
Abstract The optimizing of renewable energy use and grid integration relies on accurate solar power predictions. In order to predict the amount of power that solar photovoltaic (PV) systems would produce inside an IoT framework, this study suggests a new method that integrates Singular Spectrum Analysis (SSA) with Extreme Learning Machine technology. The SSA algorithm makes sense of solar power data by separating it into its component parts, such as trend, seasonality, and noise. The ELM model, a quick and effective feedforward neural network with a single hidden layer, takes these broken-down parts as input characteristics. In order to enhance the accuracy of solar power forecasts, the suggested strategy combines the decomposition skills of SSA with the predictive capability of ELM. Data acquired by solar PV sensors is input into the IoT-based forecasting model, which then undergoes preprocessing with SSA, feature extraction, model training with ELM, and performance evaluation. The SSA-ELM methodology has been successfully tested on real solar power data and has shown promising results in terms of accuracy measures such as low mean absolute error and mean absolute percentage error. By implementing the suggested method, accurate projections of solar output can be made, leading to better energy management, lower costs, and the smooth incorporation of renewables into smart grids. A dependable and computationally efficient method for solar forecasting in Internet of Things applications is provided by the combination of SSA and ELM.
摘要 可再生能源的优化利用和并网依赖于准确的太阳能功率预测。为了预测太阳能光伏（PV）系统在物联网框架内的发电量，本研究提出了一种将奇异谱分析（SSA）与极限学习机技术相结合的新方法。单频谱分析算法通过将太阳能数据分离为趋势、季节性和噪声等组成部分，使其具有意义。ELM 模型是一种具有单隐层的快速有效的前馈神经网络，它将这些分解部分作为输入特征。为了提高太阳能预测的准确性，建议的策略结合了 SSA 的分解技能和 ELM 的预测能力。太阳能光伏传感器获取的数据被输入到基于物联网的预测模型中，然后经过 SSA 预处理、特征提取、ELM 模型训练和性能评估。SSA-ELM 方法已成功在真实太阳能数据上进行了测试，并在平均绝对误差和平均绝对百分比误差等准确度指标方面显示出良好的效果。通过实施所建议的方法，可以对太阳能输出进行精确预测，从而改善能源管理，降低成本，并将可再生能源顺利纳入智能电网。SSA 和 ELM 的结合为物联网应用中的太阳能预测提供了一种可靠且计算效率高的方法。
{"title":"IoT based solar power forecasting using SSA-ELM technique","authors":"Santanu Borgohain, Sumant K. Dalai, Rangababu Peesapati, G. Panda","doi":"10.1515/ijeeps-2024-0148","DOIUrl":"https://doi.org/10.1515/ijeeps-2024-0148","url":null,"abstract":"Abstract The optimizing of renewable energy use and grid integration relies on accurate solar power predictions. In order to predict the amount of power that solar photovoltaic (PV) systems would produce inside an IoT framework, this study suggests a new method that integrates Singular Spectrum Analysis (SSA) with Extreme Learning Machine technology. The SSA algorithm makes sense of solar power data by separating it into its component parts, such as trend, seasonality, and noise. The ELM model, a quick and effective feedforward neural network with a single hidden layer, takes these broken-down parts as input characteristics. In order to enhance the accuracy of solar power forecasts, the suggested strategy combines the decomposition skills of SSA with the predictive capability of ELM. Data acquired by solar PV sensors is input into the IoT-based forecasting model, which then undergoes preprocessing with SSA, feature extraction, model training with ELM, and performance evaluation. The SSA-ELM methodology has been successfully tested on real solar power data and has shown promising results in terms of accuracy measures such as low mean absolute error and mean absolute percentage error. By implementing the suggested method, accurate projections of solar output can be made, leading to better energy management, lower costs, and the smooth incorporation of renewables into smart grids. A dependable and computationally efficient method for solar forecasting in Internet of Things applications is provided by the combination of SSA and ELM.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141335074","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 : 2024-06-17DOI: 10.1515/ijeeps-2024-0011
Yiqi Zhang, Yuan Liao, Gaurav Yadav
Abstract To reduce greenhouse emission and achieve sustainability in the electric power industry, improved efficiency and energy conservation are key to finding a sound solution. Energy conservation through voltage reduction (CVR) is one such program. To implement effective CVR programs, load models are of utmost importance in determining proper feeders and methods to implement the CVR programs. Exponential and polynomial load models stand out as the most widely adopted models. The polynomial load model, often referred to as the ZIP (constant impedance, current and power) model, is especially notable for its ability to represent the relationship between the applied voltage and power consumption. This paper sheds light on the limitations of commonly used ZIP load model estimation methods and highlights the significance of using ap-propriate measurement samples and understanding the true nature of the load. Two distinct ZIP load models, i.e., the regular ZIP (RegZIP) and the Non-traditional ZIP (NTZIP) models, have been used for ZIP parameter estimation. The RegZIP load model consumes equal or more power when voltage increases, while the NTZIP model consumes equal or less power when voltage increases. It is emphasized that the RegZIP is an existing load model and the NTZIP is an artificial load model this research created for comparison purposes. The intention of this paper is not to propose any new load model, but to investigate the implications of choosing the wrong model and the impacts of measurement errors of voltage and power data. The research has shown that the two different models can fit the same measurement data equally well for some measured data. The results have demonstrated that simply using certain methods such as the optimization method for estimating load model parameters using unfiltered real time measurements may yield misleading and unreliable results. Wrong load models will inevitably lead to wrong CVR assessment. Identifying the correct measurement samples, obtained during natural or staged events causing substantial voltage variations, is critically important in calculating load parameters and ensure the soundness of the obtained results. The accurate load parameters will be important in the assessment of CVR program effectiveness and will ensure that power system analysis applications that utilize the load models will provide reliable results.
摘要 为减少温室气体排放，实现电力行业的可持续发展，提高效率和节约能源是找到合理解决方案的关键。通过降低电压（CVR）来节约能源就是这样一种方案。要实施有效的 CVR 计划，负荷模型对于确定合适的馈线和实施 CVR 计划的方法至关重要。指数负荷模型和多项式负荷模型是最广泛采用的模型。多项式负载模型通常被称为 ZIP（恒定阻抗、电流和功率）模型，因其能够表示应用电压和功耗之间的关系而尤为突出。本文揭示了常用 ZIP 负载模型估计方法的局限性，并强调了使用适当测量样本和了解负载真实性质的重要性。两种不同的 ZIP 负载模型，即常规 ZIP (RegZIP) 模型和非传统 ZIP (NTZIP) 模型，已被用于 ZIP 参数估计。RegZIP 负载模型在电压升高时消耗相同或更多的功率，而 NTZIP 模型在电压升高时消耗相同或更少的功率。需要强调的是，RegZIP 是现有的负载模型，而 NTZIP 是本研究为比较目的而创建的人工负载模型。本文的目的不是提出任何新的负载模型，而是研究选择错误模型的影响以及电压和功率数据测量误差的影响。研究结果表明，对于某些测量数据，两种不同的模型可以很好地拟合相同的测量数据。研究结果表明，简单地使用某些方法，如使用未过滤的实时测量数据估算负载模型参数的优化方法，可能会产生误导性和不可靠的结果。错误的负荷模型必然导致错误的 CVR 评估。确定正确的测量样本（在导致电压大幅变化的自然或阶段性事件中获得）对于计算负荷参数和确保所得结果的合理性至关重要。准确的负荷参数对于评估 CVR 程序的有效性非常重要，并将确保使用负荷模型的电力系统分析应用程序能够提供可靠的结果。
{"title":"Experiences about calculating ZIP and exponential load model parameters","authors":"Yiqi Zhang, Yuan Liao, Gaurav Yadav","doi":"10.1515/ijeeps-2024-0011","DOIUrl":"https://doi.org/10.1515/ijeeps-2024-0011","url":null,"abstract":"Abstract To reduce greenhouse emission and achieve sustainability in the electric power industry, improved efficiency and energy conservation are key to finding a sound solution. Energy conservation through voltage reduction (CVR) is one such program. To implement effective CVR programs, load models are of utmost importance in determining proper feeders and methods to implement the CVR programs. Exponential and polynomial load models stand out as the most widely adopted models. The polynomial load model, often referred to as the ZIP (constant impedance, current and power) model, is especially notable for its ability to represent the relationship between the applied voltage and power consumption. This paper sheds light on the limitations of commonly used ZIP load model estimation methods and highlights the significance of using ap-propriate measurement samples and understanding the true nature of the load. Two distinct ZIP load models, i.e., the regular ZIP (RegZIP) and the Non-traditional ZIP (NTZIP) models, have been used for ZIP parameter estimation. The RegZIP load model consumes equal or more power when voltage increases, while the NTZIP model consumes equal or less power when voltage increases. It is emphasized that the RegZIP is an existing load model and the NTZIP is an artificial load model this research created for comparison purposes. The intention of this paper is not to propose any new load model, but to investigate the implications of choosing the wrong model and the impacts of measurement errors of voltage and power data. The research has shown that the two different models can fit the same measurement data equally well for some measured data. The results have demonstrated that simply using certain methods such as the optimization method for estimating load model parameters using unfiltered real time measurements may yield misleading and unreliable results. Wrong load models will inevitably lead to wrong CVR assessment. Identifying the correct measurement samples, obtained during natural or staged events causing substantial voltage variations, is critically important in calculating load parameters and ensure the soundness of the obtained results. The accurate load parameters will be important in the assessment of CVR program effectiveness and will ensure that power system analysis applications that utilize the load models will provide reliable results.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141335259","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 : 2024-06-12DOI: 10.1515/ijeeps-2024-0145
A. Bhoi, P. Nayak, R. Mallick, Sairam Mishra, G. Panda
Abstract Accurate harmonic estimation is essential for effective power quality assessment, designing appropriate harmonic filters, and ensuring the reliable operation of electrical equipment. This article proposes a novel hybrid harmonic estimation technique combining recursive least square (RLS) and arithmetic optimization algorithm (AOA) for accurate estimation of harmonics, inter-harmonics and sub-harmonics. AOA is a new meta-heuristic method based on distribution behaviour of main arithmetic operators such as addition, subtraction, multiplication and division. RLS is used for estimation of amplitude of harmonics, whereas phase is estimated by AOA. The performance of AOA–RLS is investigated in detail for estimation of power system signals using two set of test signals buried with noise. The proposed AOA–RLS is proved to be efficient for estimating both phase and amplitude parameters under different signal to noise ratio (SNR) conditions with an estimation of error of E−3. The efficacy of AOA–RLS technique is demonstrated by comparing with competitive existing techniques. The performance of AOA–RLS also verified in experimental studies.
{"title":"Novel hybrid arithmetic optimization algorithm-recursive least square approach for power system harmonic estimation","authors":"A. Bhoi, P. Nayak, R. Mallick, Sairam Mishra, G. Panda","doi":"10.1515/ijeeps-2024-0145","DOIUrl":"https://doi.org/10.1515/ijeeps-2024-0145","url":null,"abstract":"Abstract Accurate harmonic estimation is essential for effective power quality assessment, designing appropriate harmonic filters, and ensuring the reliable operation of electrical equipment. This article proposes a novel hybrid harmonic estimation technique combining recursive least square (RLS) and arithmetic optimization algorithm (AOA) for accurate estimation of harmonics, inter-harmonics and sub-harmonics. AOA is a new meta-heuristic method based on distribution behaviour of main arithmetic operators such as addition, subtraction, multiplication and division. RLS is used for estimation of amplitude of harmonics, whereas phase is estimated by AOA. The performance of AOA–RLS is investigated in detail for estimation of power system signals using two set of test signals buried with noise. The proposed AOA–RLS is proved to be efficient for estimating both phase and amplitude parameters under different signal to noise ratio (SNR) conditions with an estimation of error of E−3. The efficacy of AOA–RLS technique is demonstrated by comparing with competitive existing techniques. The performance of AOA–RLS also verified in experimental studies.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141354170","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 : 2024-05-24DOI: 10.1515/ijeeps-2023-0372
Ian McClenny, Emily Tynes, G. Xydis
Developing nations are facing market, regulatory, and monetary issues that often prevent them from being on the cutting edge of the energy industry. Climate commitments set forth by international cooperation like the Paris Agreement are calling for countries to decarbonize their energy infrastructure. The International Finance Corporation (IFC) predicts that much of the development in the renewable energy sector is poised to come from developing nations; this is where the greatest opportunities lie for systemic change. This study will highlight the shifting trend towards wind-plus-storage, the development cycle of disruptive technologies, key characteristics of wind-plus-storage projects, and a discussion on best practices to stimulate market demand, technological innovation, and associated regulations. A case study in Oceania, in Papua New Guinea was constructed using ArcGIS as a proof of concept to highlight data that can be leveraged to preliminarily identify high potential sites for wind-plus-storage project development. A detailed map was revealed and the different wind-plus-storage options for future project development were found. It has not been studied so far how a wind-plus-storage project can contribute to more holistic energy systems in emerging markets, such as in the case of Papua New Guinea.
{"title":"Wind-plus-storage integration in emerging markets – a GIS-driven proof-of-concept for Papua New Guinea","authors":"Ian McClenny, Emily Tynes, G. Xydis","doi":"10.1515/ijeeps-2023-0372","DOIUrl":"https://doi.org/10.1515/ijeeps-2023-0372","url":null,"abstract":"\u0000 Developing nations are facing market, regulatory, and monetary issues that often prevent them from being on the cutting edge of the energy industry. Climate commitments set forth by international cooperation like the Paris Agreement are calling for countries to decarbonize their energy infrastructure. The International Finance Corporation (IFC) predicts that much of the development in the renewable energy sector is poised to come from developing nations; this is where the greatest opportunities lie for systemic change. This study will highlight the shifting trend towards wind-plus-storage, the development cycle of disruptive technologies, key characteristics of wind-plus-storage projects, and a discussion on best practices to stimulate market demand, technological innovation, and associated regulations. A case study in Oceania, in Papua New Guinea was constructed using ArcGIS as a proof of concept to highlight data that can be leveraged to preliminarily identify high potential sites for wind-plus-storage project development. A detailed map was revealed and the different wind-plus-storage options for future project development were found. It has not been studied so far how a wind-plus-storage project can contribute to more holistic energy systems in emerging markets, such as in the case of Papua New Guinea.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141098672","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 : 2024-04-01DOI: 10.1515/ijeeps-2023-0420
Silin He, Jiran Zhu, Di Zhang, Shengpeng Liu, Luxin Zhan, Chun Chen
In distribution networks, single-phase grounding occurrences in non-effectively grounded systems do not result in short-circuits, thus leading to low fault currents. Particularly in high-resistance grounding scenarios, fault currents become extremely low, increasing the risk of protection misjudgments. To enhance the speed and accuracy of self-healing during such faults, a distributed self-healing control method based on flexible grounding and zero-sequence current analysis for non-effectively grounded systems is proposed. This method employs peer-to-peer distributed self-healing and flexible grounding techniques to convert isolated or arc-suppressed neutral systems to low-resistance grounded systems. Additionally, a localization criterion unaffected by neutral grounding modes is introduced, utilizing deviations in zero-sequence current upstream and downstream of the fault as distinguishing characteristics. The proposed method is straightforward in principle and leverages existing terminal equipment for accurate and swift fault processing. Simulation results validate the method’s resilience to transition resistance and neutral grounding conditions, demonstrating its suitability for single-phase grounding fault localization across all system types. The research findings effectively ensure the accuracy and swiftness of self-healing during single-phase grounding faults in non-effectively grounded systems.
{"title":"Distributed self-healing control of single-phase grounding fault in neutral point non-effective grounding system","authors":"Silin He, Jiran Zhu, Di Zhang, Shengpeng Liu, Luxin Zhan, Chun Chen","doi":"10.1515/ijeeps-2023-0420","DOIUrl":"https://doi.org/10.1515/ijeeps-2023-0420","url":null,"abstract":"\u0000 In distribution networks, single-phase grounding occurrences in non-effectively grounded systems do not result in short-circuits, thus leading to low fault currents. Particularly in high-resistance grounding scenarios, fault currents become extremely low, increasing the risk of protection misjudgments. To enhance the speed and accuracy of self-healing during such faults, a distributed self-healing control method based on flexible grounding and zero-sequence current analysis for non-effectively grounded systems is proposed. This method employs peer-to-peer distributed self-healing and flexible grounding techniques to convert isolated or arc-suppressed neutral systems to low-resistance grounded systems. Additionally, a localization criterion unaffected by neutral grounding modes is introduced, utilizing deviations in zero-sequence current upstream and downstream of the fault as distinguishing characteristics. The proposed method is straightforward in principle and leverages existing terminal equipment for accurate and swift fault processing. Simulation results validate the method’s resilience to transition resistance and neutral grounding conditions, demonstrating its suitability for single-phase grounding fault localization across all system types. The research findings effectively ensure the accuracy and swiftness of self-healing during single-phase grounding faults in non-effectively grounded systems.","PeriodicalId":45651,"journal":{"name":"International Journal of Emerging Electric Power Systems","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140354535","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}
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