Stochastic Assessment of Voltage Unbalance Mitigation by Battery System in case of Single-Phase Solar Generation

The political decisions and environmental problems apply a pressure on the research to utilize environmentally friendly energy sources and bring them to masses. However, the vast spread of renewable energy generation, such as solar power, adds an additional strain to electric power grid and damage the quality of the supplied electrical energy. In this thesis, stochastic assessment of the voltage unbalance mitigation by home battery system in low voltage grid with single-phase solar generation is analysed. The stochastic voltage unbalance assessment method based on Monte Carlo Simulation technique was utilised for two algorithms: time independent and time dependent. Both models were presented and results of each were compared. Three different battery phase connection strategies were modelled and voltage unbalance mitigation efficacy of each was evaluated. Three low voltage distribution grids are considered - rural, intermediate and urban - each grid representing different regions in Finland. The voltage unbalance at different solar and battery penetration levels was assessed and the most efficient battery connection strategy was revealed. Lastly, various aspects of the topic were discussed in the end

Data-Driven Modelling for Harmonic Current Emission in Low-Voltage Grid Using MCReSANet with Interpretability Analysis

Even though the use of power electronics PE loads offers enhanced electrical energy conversion efficiency and control, they remain the primary sources of harmonics in grids. When diverse loads are connected in the distribution system, their interactions complicate establishing analytical models for the relationship between harmonic voltages and currents. To solve this, our paper presents a data-driven model using MCReSANet to construct the highly nonlinear between harmonic voltage and current. Two datasets from PCCs in Finland and Germany are utilized, which demonstrates that MCReSANet is capable of establishing accurate nonlinear mappings, even in the presence of various network characteristics for selected Finland and Germany datasets. The model built by MCReSANet can improve the MAE by 10% and 14% compared to the CNN, and by 8% and 17% compared to the MLP for both Finnish and German datasets, also showing much lower model uncertainty than others. This is a crucial prerequisite for more precise SHAP value-based feature importance analysis, which is a method for the model interpretability analysis in this paper. The results by feature importance analysis show the detailed relationships between each order of harmonic voltage and current in the distribution system. There is an interactive impact on each order of harmonic current, but some orders of harmonic voltages have a dominant influence on harmonic current emissions: positive sequence and zero sequence harmonics have the dominant importance in the Finnish and German networks, respectively, which conforms to the pattern of connected load types in two selected Finnish and German datasets. This paper enhances the potential for understanding and predicting harmonic current emissions by diverse PE loads in distribution systems, which is beneficial to more effective management for optimizing power quality in diverse grid environments

Convex Model for Estimation of Single-Phase Photovoltaic Impact on Existing Voltage Unbalance in Distribution Networks

Due to the increasing adoption of solar power generation, voltage unbalance estimation gets more attention in sparsely populated rural networks. This paper presents a Monte Carlo simulation augmented with convex mixed-integer quadratic programming to estimate voltage unbalance and maximum photovoltaic penetration. Additionally, voltage unbalance attenuation by proper phase allocation of photovoltaic plants is analysed. Single-phase plants are simulated in low-voltage distribution networks and voltage unbalance is evaluated as a contribution of measured background and photovoltaic-caused unbalance. Voltage unbalance is calculated in accordance with EN 50160 and takes into account 10-minute average values with 5% tolerance condition. Results of the optimization revealed substantial unbalance attenuation with optimal phase selection and increased potential of local generation hosting capacity in case of higher background unbalance

Evaluating distribution network optimal structure with respect to solar hosting capacity

Funding Information: This work was supported by Aalto University of Finland as a part of “SolarX” project 211763 funded by Business Finland . Publisher Copyright: © 2022 The Author(s)Optimal design of distribution networks has become an important topic for analysis due to the growing share of photovoltaics (PV). Low and medium voltage networks should undergo structural changes to accommodate widespread PV generation and optimal operation. In this paper, the impact of the network structure on the solar hosting capacity (HC) is analyzed with respect to the role of low and medium voltage networks in power delivery. A given set of load nodes is simulated with multiple feeding substations and varying peak power and number of PV plants. The slime mold algorithm is utilized for numerous topology generations and measured load time series represent regions ranging from rural to urban. The results reveal that networks should go through significant structural changes to cope with larger PV generation and even more so to increase the HC. On the other hand, voltage control measures, such as on-load tap changers, PV reactive power control and curtailment, provide a competitive solution to varying size of distribution networks in hosting solar power. Finally, the analysis in this study provides evidence to a possible need in the change of residential PV policies in order to sustain the current pace of adopting PV plants in Finland.Peer reviewe

Convex Model for Estimation of Single-Phase Photovoltaic Impact on Existing Voltage Unbalance in Distribution Networks

Due to the increasing adoption of solar power generation, voltage unbalance estimation gets more attention in sparsely populated rural networks. This paper presents a Monte Carlo simulation augmented with convex mixed-integer quadratic programming to estimate voltage unbalance and maximum photovoltaic penetration. Additionally, voltage unbalance attenuation by proper phase allocation of photovoltaic plants is analysed. Single-phase plants are simulated in low-voltage distribution networks and voltage unbalance is evaluated as a contribution of measured background and photovoltaic-caused unbalance. Voltage unbalance is calculated in accordance with EN 50160 and takes into account 10-minute average values with 5% tolerance condition. Results of the optimization revealed substantial unbalance attenuation with optimal phase selection and increased potential of local generation hosting capacity in case of higher background unbalance.Peer reviewe

Review on the PV hosting capacity in distribution networks

The increasing penetration of Photovoltaic (PV) generation results in challenges regarding network operation, management and planning. Correspondingly, Distribution Network Operators (DNOs) are in the need of totally new understanding. The establishment of comprehensive standards for maximum PV integration into the network, without adversely impacting the normal operating conditions, is also needed. This review article provides an extensive review of the Hosting Capacity (HC) definitions based on different references and estimated HC with actual figures in different geographical areas and network conditions. Moreover, a comprehensive review of limiting factors and improvement methods for HC is presented along with voltage rise limits of different countries under PV integration. Peak load is the major reference used for HC definition and the prime limiting constraint for PV HC is the voltage violations. However, the varying definitions in different references lead to the conclusion that, neither the reference values nor the limiting factors are unique values and HC can alter depending on the reference, network conditions, topology, location, and PV deployment scenario.Peer reviewe

Comparison of Different References When Assessing PV HC in Distribution Networks

The burgeoning photovoltaics’ (PVs) penetration in the low voltage distribution networks can cause operational bottlenecks if the PV integration exceeds the threshold known as hosting capacity (HC). There has been no common consensus on defining HC, and its numerical value varies depending on the reference used. Therefore, this article compared the HC values of three types of networks in rural, suburban, and urban regions for different HC reference definitions. The comparison was made under balanced and unbalanced PV deployment scenarios and also for two different network loading conditions. A Monte Carlo (MC) simulation approach was utilized to consider the intermittency of PV power and varying loading conditions. The stochastic analysis of the networks was implemented by carrying out a large number of simulation scenarios, which led towards the determination of the maximum amount of PV generation in each network case.Peer reviewe

Monte carlo-based comprehensive assessment of PV hosting capacity and energy storage impact in realistic finnish low-voltage networks

The direction taken towards sustainable power system and renewable energy generation is now irreversible. The power grid needs to host more renewable energy sources, such as solar power, and tackle power quality problems that come along with it. In this paper, firstly, the Hosting Capacities (HCs), of Photo-Voltaic (PV), were found for various regions and their limiting constraints were defined. Afterwards, comparison was made with the HC values obtained for different voltage value standards defined by various countries. Next, single-phase PV connection percentages in the network were defined that makes the voltage unbalance the limiting factor for HC. Lastly, the HC of the solar generation coupled with a Battery Energy Storage System (BESS) was assessed for the Finnish Low-Voltage (LV) grids. Different BESS-based scenarios were employed and their impact on voltage unbalance and HCs were observed. Finally, also the load voltage unbalance was incorporated to make the approach realistic and its impact on HC wasanalyzed. Results reveal that, depending on the connection strategy, the BESS can increase as well as decrease the HC based on voltage unbalance criteria. However, the load voltage unbalance has little effect on the solar HC values.Peer reviewe

Survey of a power quality measurement campaign in low-voltage grids

With an increasing share of renewable energy generation becoming connected to distribution grids, power quality has attracted the attention of grid operators and academia. However, to obtain a realistic picture, power quality distortions caused by renewables should be superimposed on already existing emissions in grids. Measured household load data is tedious to acquire and is not publicly available. This paper presents the data from a low-voltage feeder measurement campaign and it is divided into voltage and feeder current analyses. The voltage parameters are validated as per EN 50160. The measured data includes measurements from feeders supplying single-family homes as well as one apartment building. A total of 24 weeks of 10-second mean values were recorded in the Helsinki region of Finland. Results indicate that the voltage quality is within the acceptable limits. The feeder currents show load unbalance in single-family homes and high utilisation rate of feeders supplying multiple customers.Peer reviewe

Analyzing the Impact of EV and BESS Deployment on PV Hosting Capacity of Distribution Networks

Funding Information: This work was supported by Aalto University of Finland as a part of “SolarX” project 211763 funded by Business Finland, and by the Ministry of Education, Youth and Sports of the Czech Republic under BUT specific research programme (project No. FEKT-S-20-6449) in the Centre for Research and Utilization of Renewable Energy (CVVOZE). Funding Information: This research work has been carried out in the Centre for Research and Utilization of Renewable Energy (CVVOZE). Authors gratefully acknowledge financial support from the Ministry of Education, Youth and Sports of the Czech Republic under BUT specific research programme (project No. FEKT-S-20-6449). The work was conducted during the Erasmus+ exchange program. Publisher Copyright: © 2022 by the authors.The current article analyzes the impact of charging electric vehicles and battery energy storage systems on the photovoltaic hosting capacity of low-voltage distribution networks. A Monte Carlo-based simulation is used to analyze predominantly rural, intermediate and predominantly urban residential regions facing different penetrations of electric vehicles utilizing uncontrolled and controlled charging, and evaluate their impact on photovoltaic hosting capacity. Subsequently, electric vehicles are replaced or supplemented by residential battery energy storage systems, and their combined impact on the hosting capacity is studied. The results revealed that electric vehicles solely do not improve the hosting capacity unless they are connected to the network during sunshine hours. However, controlled storage provides a remarkable increase to the hosting capacity and exceptional contribution in combination with electric vehicles and customers with high loads. Finally, a feasibility analysis showed that controlled charging of the storage has a lower marginal cost of increasing hosting capacity as compared to network reinforcement.Peer reviewe