Article

Maximum PV generation estimation method for residential low voltage feeders

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Abstract

Growing penetrations of distributed PV generation in electrical networks pose new challenges for electricity industry operation and planning. In particular, distribution network operators are now facing reduced and even reversed power flows at times of high PV generation and low load. This has a range of impacts of including, notably, voltage rise in the network. Existing planning tools are not necessarily appropriate in this changing context. This paper presents a novel method for simply and easily estimating the maximum PV generation that can be integrated into low voltage feeders while avoiding excessive voltage levels. This exercise would generally require the use of power flow analysis software. The proposed method, however, provides maximum PV generation estimates that are close to those calculated by such tools while being easily implemented in standard spreadsheet software. The method can therefore simplify the task of distribution network operators in planning and operating their networks when facing growing PV penetrations on their low voltage feeders.

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... Power quality studies referring to PV generation limits in low voltage (LV) have been a topic extensively covered in the scientific community, with some referring to voltage unbalance specifically as the main concern [5][6][7][8][9][10][11][12][13][14][15][16]. A study [16] considering a Canadian network used in suburban residential areas defined voltage variation limits and evaluated PV penetration limits. ...
... The results indicated that the PV penetration level should not adversely impact the voltage on the grid when the distributed PV resources do not exceed 2.5 kW per household on average on a typical distribution grid. It is important to bear in mind that the PV penetration has different effects when introduced in different points of the network [5][6][7], but also when either a single PV installation is considered or multiple PVs in the same phase are connected. Even though this effect exists, it does not seem to be as important as the PV size itself and the subjacent load applied [8]. ...
... There are methods dispensing the use of power flow analysis software for estimating the maximum PV generation that can be integrated into low-voltage feeders, while escaping excessive voltage levels. Heslop, MacGill and Fletcher (2016) [7] provide maximum PV generation estimates that are close to those calculated by such tools, while being easily implemented in a standard spreadsheet software. The example given for a low-voltage single-phase connection for a network based on Australian characteristics, estimated a 3.5 kW as maximum PV power for each PV system. ...
Article
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As photovoltaic (PV) penetration increases in low-voltage distribution networks, voltage variation may become a problem. This is particularly important in residential single-phase systems, due to voltage unbalances created by the inflow of points in the network. The existing literature frequently refers to three-phase systems focusing on losses and voltage variations. Many studies tend to use case studies whose conclusions are difficult to replicate and generalise. As levels of residential PV rise, single-phase PV power injection levels, before voltage unbalances reach standard limits, become important to be investigated. In this study, an urban European reference network is considered, and using a real-time digital simulator, different levels of PV penetration are simulated. PV systems are connected to the same phase (unbalanced case), and are also evenly phase-distributed (balanced case). Considering a 2-3% unbalance limit, approximately 3.5-4.6 kW could be injected in every bus in an unbalanced scenario. With a balanced PV distribution, the power injected could reach 10-13 kW per bus. Buses closer to the power transformer allow higher power connections, due to cable distances and inferior voltage drops. Feeder length, loads considered during simulation, and cable shunt capacitance reactance influence the results the most.
... In Australia, the assessment process of photovolatic (PV) installation varies from one DSO to another. Some DSOs allow PV integration only up to a certain limit [13], [14], while others use the transformer capacity as the determining factor [15]. For example, Ausgrid, a DSO in the state of New South Wales (NSW), which is experiencing a high PV penetration, examines all PV installations to determine their contribution to voltage rise and check if the network augmentation will be required [16]. ...
... For example, Ausgrid, a DSO in the state of New South Wales (NSW), which is experiencing a high PV penetration, examines all PV installations to determine their contribution to voltage rise and check if the network augmentation will be required [16]. Ergon Energy, another DSO in Australia, undertakes a complete assessment if the size of PV is greater than 3.5 kVA [14], [17]. Setting a hard limit on the total capacity that can be installed in the system or not assessing PV systems under a certain size can either result in an underutilization of the HC or in overvoltage problem. ...
... Most HC studies have been based on the sequential power flow [7], [9], [24], [25]. In order to reduce the HC assessment dependency on power flow calculation, authors in [14] presented an analytical method to estimate the HC of PVs without using power flow calculation, but the voltage drop along the feeder was not modeled, so the aforementioned method might not be accurate for long low voltage (LV) feeders. ...
Article
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High penetration of distributed generation (DG) is mainly constrained by voltage related issues. Due to the uncertainties associated with type, size and location of DGs, it is difficult to quantify their integration limits in distribution networks, i.e., hosting capacity (HC). To address this issue, this paper proposes a probabilistic based framework to determine the maximum integration limits of DGs considering the voltage rise and voltage deviation constraints. Such framework requires use of the HC model, which can be formulated as a nonlinear optimization problem. Adding the voltage deviation constraint in the HC problem makes the model unsolvable. We address this issue by proposing a two-step algorithm to linearize the HC model. Then, using the linearized model, a probabilistic framework is proposed for considering the load variability and DGs uncertainties. To validate the efficacy and accuracy of the proposed framework, we identify the HC of a balanced and an unbalanced distribution networks and compare our results with those obtained from comprehensive power flow method and the traditional conservative planning. Finally, using the proposed framework, the impact of voltage deviation constraint, load growth, DG type and network structure on the HC are comprehensively studied using different DG technologies (i.e., Photovoltaics and wind).
... There is an obvious need for an effective method that simplifies the process of evaluating the voltage rise and its mitigation techniques [20]. Techniques such as the one developed in [21] give close results to the values calculated using commercial power analysis tools, but the application is limited to simple residential low voltage feeders. ...
... By plugging in the right numbers for the loads and coupling impedances, (21) and (22) determine the values of I pv ,P and δ L . There are two solutions for (1), one of them satisfies (V Lm − Z r I pv ,P ) > 0 which is the one to be considered while the other one leads to (V Lm − Z r I pv ,P ) < 0. The PV production limit can then be obtained directly as V Lm I pv ,P . ...
... There are two solutions for (1), one of them satisfies (V Lm − Z r I pv ,P ) > 0 which is the one to be considered while the other one leads to (V Lm − Z r I pv ,P ) < 0. The PV production limit can then be obtained directly as V Lm I pv ,P . The values determined in (21) and (22) specifies the PV power production that leads to an unacceptable voltage rise. This value for the PV power can also determine how much curtailment is needed to keep the voltage below the upper limit. ...
Article
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As the photovoltaic (PV) sources capacities in distribution networks continue to grow, more operational challenges are expected to be encountered. One of these challenges is the voltage rise within distribution networks due to reverse power flow from the PV sources toward the grid. In this paper, a simplified analytical approach is presented which allows the voltage rise possibility to be tested and the performance of its mitigation techniques to be evaluated. Equivalent transformations are used to represent complicated power systems using simplified circuits. Then, formulas are derived to determine the PV power limits beyond which a voltage rise will be encountered considering the PV sources capability of absorbing reactive power. Moreover, the system losses in each case are estimated using the proposed formulas. Consequently, the proposed analysis method could be used for a number of applications related to PV sizing and losses minimization. The validity of the proposed method is verified through a number of case studies where its findings are compared with results obtained from DIgSILENT software tools.
... HC quantification methods are classified into three groups in [7]: deterministic methods, probabilistic load flow methods, and quasi-static time series (QSTS) methods. Deterministic methods do not require high computational capabilities and offer a quick rough estimate for HC, utilizing fixed-input data models such as customer power consumption and PV generation [8][9][10][11][12]. Probabilistic load flow methods use the probability density functions of stochastic input variables to model the uncertainties of the distribution network and estimate the HC [13][14][15][16][17]. ...
... The parameters of the two critic functions are optimized by using gradient descent to minimize their respective loss functions as given in Equations (12) and (13), where D is a batch of experiences sampled from the replay buffer B. To address the overestimation bias that generally persists in all DRL algorithms, TD3 employs the clipped double-Q learning trick that uses a single target y(r, s ′ ) to calculate the loss functions of both critic functions. The target y(r, s ′ ) is calculated using the minimum of two target critics Q θ ′ 1 and Q θ ′ 2 as given in Equation (14). ...
Article
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Coordinated voltage control enables the active management of voltage levels throughout electricity distribution networks by leveraging the voltage support capabilities of existing grid-connected PV inverters. The efficient management of power flows and precise voltage regulation through coordinated voltage control schemes facilitate the increased adoption of rooftop PV systems and enhance the hosting capacity of electricity distribution networks. The research work presented in this paper proposes a coordinated voltage control scheme and evaluates the enhanced hosting capacity utilizing a deep reinforcement learning-based approach. A comparative analysis of the proposed algorithm is presented, and the performance is benchmarked against existing local voltage control schemes. The proposed coordinated voltage control scheme in this paper is evaluated using simulations on a real-world low-voltage electricity distribution network. The evaluation involves quasi-static time series power flow simulations for assessing performance. Furthermore, a discussion is presented that reflects on the strengths and limitations of the proposed scheme based on the results observed from the case study.
... Previous studies have developed methods for determining the hosting capacity to improve the accuracy of the natural characteristics of PV penetration (Bollen and Hassan 2011;Breker, Claudi, and Sick 2015;Dubey and Santoso 2017;Electric Power Research Institute 2012;Kolenc, Papič, and Blažič 2015). The main challenge in improving accuracy is the modelling of distributed penetration, which includes the characteristics of uncertainty and natural variability of PV penetration (Bollen and Hassan 2011;Breker, Claudi, and Sick 2015;Dubey and Santoso 2017;Electric Power Research Institute 2012;Emmanuel and Rayudu 2017;Heslop, MacGill, and Fletcher 2016;Kolenc, Papič, and Blažič 2015;Luthander, Lingfors, and Widén 2017). ...
... To model the PV penetration and obtain expected hosting capacity results, the two most widely used approaches are the deterministic approach and the stochastic approach. A deterministic approach for obtaining the hosting capacity has been implemented by several authors (Abdelkader, Osman, and Elshahed 2020;Conti and Raiti 2007;Emmanuel and Rayudu 2017;Heslop, MacGill, and Fletcher 2016;Kabir, Mishra, and Bansal 2016;Luthander, Lingfors, and Widén 2017;Shayani and De Oliveira 2011). This approach predicts the hosting capacity by setting specific values as simulation variables. ...
Article
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The previous stochastic hosting capacity prediction method using the Monte Carlo method for high photovoltaic (PV) penetration with a battery energy storage system (BESS) required a large number of computations to achieve the expected accuracy. The problem of high computational load must be addressed so that the electrical distribution planner can practically use the PV hosting capacity prediction in actual situations. Therefore, this study developed a Markov-chain-based PV hosting capacity prediction method for high PV penetration using BESS. The proposed method is described in detail, followed by case and validation studies. The obtained hosting capacity was 123.58 kW, which increased to 3676.4 kW after the utility-scale BESS implementation. The results demonstrate that the proposed Markov-chain-based PV hosting capacity prediction method outperforms the Monte Carlo method, which is the most popular stochastic hosting capacity method, in terms of accuracy and computational cost.
... Because the fixed assignment of specific values to the model does not properly deal with the uncertainties in practice, the results of this method are not really accurate. The Deterministic constant generation method determines the HC value by increasing or decreasing solar photovoltaic system (PV) roof area utilization factor [13][14][15], or establishing the relationship between consumption, feeder impedance and solar PV generation [16]. In addition, the time-series method is employed in several HC computational models [17]. ...
... This power exchange is free variable that might be positive (importing electricity from the upstream grid), negative (exporting power to the upstream grid) or zero (no power exchange). Besides, inequality constraints (15) and (16) show load fluctuations in bus m that are constrained by a lower and upper limitation. This value can be determined from historical load data. ...
Article
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The large penetration of distributed energy resource (DER) into low voltage distribution network (LVDN), especially the rooftop solar photovoltaic system, is a matter of concern today. The number of DER in the LVDN increases quickly as a result of the government’s push to adopt renewable energy sources, causing many technical issues. Therefore, estimating the maximum capacity of DER that LVDN can absorb according to its limit is essential. This topic is called Hosting Capacity. Many methods to determine Hosting Capacity have been proposed in recent years, including Deterministic, Stochastic and Optimization. However, with the resolution of uncertain factors about load, location and size of (DGs), Stochastic and Optimization are more prestigious. This article focuses on comparing and evaluating the accuracy and effectiveness of these two methods when testing on an actual LVDN. Finally, by analyzing and comparing the effectiveness, advantage and disadvantage of the two proposed methods, this article helps distribution network operator (DNO) to determine the appropriate method to apply to an actual network. This not only assists DNO in planning long-term distribution network development but also supports the approval of DER connectivity.
... The border between (A) and (B) is referred as the minimum HC and the border between (B) and (C) is referred as the maximum HC in this paper. Generally, all the existing HC estimation methods can be divided into two In terms of HC assessment, studies in [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] can be categorized as region-B approach. The HC in region-B methods is usually modelled as the objective of an optimization problem [4,6,9,[12][13][14][15][16][17][18]. ...
... The HC in region-B methods is usually modelled as the objective of an optimization problem [4,6,9,[12][13][14][15][16][17][18]. However, there are some other approaches such as analytical [3,7,8,10] and Monte Carlo-based [5,11] methods that belong to the region-B category. In analytical methods, an equation is derived based on technical constraints such as over-voltage [8], overloading [7] and harmonic distortion [10] to estimate the maximum DER that could be connected to a certain location of the system. ...
Article
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This paper outlines a methodology to determine the amount of renewable energy that can be accommodated in a power system before adverse impacts such as over-voltage, over-loading and system instability occur. This value is commonly known as hosting capacity. This paper identifies when the transmission network local hosting capacity might be limited because of static and dynamic network limits. Thus, the proposed methodology can effectively be used in assessing new interconnection requests and provides an estimation of how much and where the new renewable generation can be located such that network upgrades are minimized. The proposed approach was developed as one of the components of the AUSTEn project, which was a three-year project to map Australia’s tidal energy resource in detail and to assess its economic feasibility and ability to contribute to the country’s energy needs. In order to demonstrate the effectiveness of the proposed approach, two wide area networks were developed in DIgSILENT PowerFactory based on actual Australian network data near two promising tidal resource sites. Then, the proposed approach was used to assess the local tidal hosting capacity. In addition, a complementary local hosting capacity analysis is provided to show the importance of future network upgrades on the locational hosting capaity.
... In Australia, the assessment process of PV installation varies. Some distribution system operators (DSOs) allow PV installations only up to a certain limit [9], while others set a limit based on transformer capacity [10], [11]. For instance, Ausgrid, a DSO in NSW, experiencing high PV penetration level, assesses each PV installation to determine its contribution to the steady state voltage rise and check whether augmentation will be required [12]. ...
... Most researchers have used sequential power flow to find the HC. In order to simplify the HC calculation and to reduce its dependency on a particular power flow routine, authors in [10] presented an analytical approach to estimate the maximum PV penetration without using power flow calculation. Since the effect of voltage drop along the feeder was not considered, the proposed method would work for short low voltage feeder, but could lead to a big error for long feeders. ...
... Deployment of distributed PV systems into electricity networks can have a range of positive and negative impacts including technical and non-technical factors (Passey et al., 2011). The technical impacts have been widely investigated in the literature from various points of view and include voltage fluctuations, voltage rise and reverse power flow, power fluctuations, power factor changes, frequency regulation and harmonics, unintentional islanding, fault currents and grounding issues (Passey et al., 2011, Eltawil et al., 2010, Eftekharnejad et al., 2013, Alam et al., 2013, Hoke et al., 2013, Western Power, 2012, AEMO, 2012, Tonkoski et al., 2012a, Heslop et al., 2016. Non-technical issues such as the economics and commercial implications of PV, and frameworks and policies to facilitate effective deployment of PV systems are also receiving attention in the literature. ...
... PV can, of course also contribute to such disturbances. Various studies have tried to evaluate and formulate the impact of high penetration of PV systems on the voltage profile in distribution networks (Tonkoski et al., 2012a, Heslop et al., 2016. Some mitigation strategies have been also introduced to alleviate this adverse impact of high PV penetrations using approaches including the use of distributed storage systems to manage power injection (Alam et al., 2013), active power curtailment (Tonkoski et al., 2011), and reactive power control (Demirok et al., 2011). ...
... Load estimation has been performed across a variety of use cases within power grid operation and study. Heslop et al. (2016) have estimated maximum photovoltaic generation for residential low voltage feeders. Mendes et al. (2023) estimate the variability of the load, using graph signal processing, on data with a high level of distributed generation, similar to the situation in the Netherlands. ...
Preprint
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In this paper we present novel methodology for automatic anomaly and switch event filtering to improve load estimation in power grid systems. By leveraging unsupervised methods with supervised optimization, our approach prioritizes interpretability while ensuring robust and generalizable performance on unseen data. Through experimentation, a combination of binary segmentation for change point detection and statistical process control for anomaly detection emerges as the most effective strategy, specifically when ensembled in a novel sequential manner. Results indicate the clear wasted potential when filtering is not applied. The automatic load estimation is also fairly accurate, with approximately 90% of estimates falling within a 10% error margin, with only a single significant failure in both the minimum and maximum load estimates across 60 measurements in the test set. Our methodology's interpretability makes it particularly suitable for critical infrastructure planning, thereby enhancing decision-making processes.
... Through [5], identifying of voltage variations on uniform and non-uniform feeder without violating upper voltage limit is presented. ...
Article
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Voltage unbalance is common issue encountered in low voltage distribution networks, caused by uneven allocation of single-phase customers among phases. This paper analyses part of real low voltage distribution network in Bosnia and Herzegovina. The impact of single-phase customers and single-phase connected micro photovoltaic power plants (MPPP-s) were analysed. To reduce unbalance and improve voltage profiles, Phase Balance Optimization toolbox in DIgSILENT PowerFactory software was performed in six scenarios with different distribution of customers and different percentage of penetration of MPPS-s. The aim was to find method with least number of changes in customer and photovoltaic phase connection that fits within defined limits of voltage variations and voltage unbalance of European standard for power quality (EN 50160). Conclusion is that MPPP-s cause voltage increases in the network, as well as an increase in voltage unbalance, but these effects can be mitigated by proper distribution of customer loads and MPPS-s among phases.
... This is because the reactive power injected by the shunt capacitor lowers the bus voltages in the distribution network. In [65], the HC for a residential LV feeder is estimated using an analytical approach to the deterministic methods. The authors studied the impact of solar PV with unity or non-unity power factor and compared the result to that obtained using a power system software. ...
Article
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The increasing demand for electricity and the need for environmentally friendly transportation systems has resulted in the proliferation of solar photovoltaic (PV) generators and electric vehicle (EV) charging within the low voltage (LV) distribution network. This high penetration of PV and EV charging can cause power quality challenges, hence the need for hosting capacity (HC) studies to estimate the maximum allowable connections. Although studies and reviews are abundant on the HC of PV and EV charging available in the literature, there is a lack of reviews on HC studies that cover both PV and EVs together. This paper fills this research gap by providing a detailed review of five commonly used methods for quantifying HC including deterministic, time series, stochastic, optimization, and streamlined methods. This paper comprehensively reviews the HC concept, methods, and tools, covering both PV and EV charging based on a survey of state-of-the-art literature published within the last five years (2017-2022). Voltage magnitude, thermal limit, and loading of lines, cables, and transformers are the main performance indices considered in most HC studies.
... This is because the reactive power injected by the shunt capacitor lowers the bus voltages in the distribution network. In [65], the HC for a residential LV feeder is estimated using an analytical approach to the deterministic methods. The authors studied the impact of solar PV with unity or non-unity power factor and compared the result to that obtained using a power system software. ...
Article
Full-text available
The increasing demand for electricity and the need for environmentally friendly transportation systems has resulted in the proliferation of solar photovoltaic (PV) generators and electric vehicle (EV) charging within the low voltage (LV) distribution network. This high penetration of PV and EV charging can cause power quality challenges, hence the need for hosting capacity (HC) studies to estimate the maximum allowable connections. Although studies and reviews are abundant on the HC of PV and EV charging available in the literature, there is a lack of reviews on HC studies that cover both PV and EVs together. This paper fills this research gap by providing a detailed review of five commonly used methods for quantifying HC including deterministic, time series, sto-chastic, optimization, and streamlined methods. This paper comprehensively reviews the HC concept , methods, and tools, covering both PV and EV charging based on a survey of state-of-the-art literature published within the last five years (2017-2022). Voltage magnitude, thermal limit, and loading of lines, cables, and transformers are the main performance indices considered in most HC studies.
... Analytical approaches to deterministic methods are widely used in many works of literature, since they offer a quick determination of HC with less computational burden. Power flow analysis software is not required for such analytic methods, and they can easily be implemented in spreadsheet environments [24]. Another example of an analytical approach for HC quantification is presented in [25] for three different scenarios of distributed generation (DG) placement in the network. ...
Article
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Increasing connection rates of rooftop photovoltaic (PV) systems to electricity distribution networks has become a major concern for the distribution network service providers (DNSPs) due to the inability of existing network infrastructure to accommodate high levels of PV penetration while maintaining voltage regulation and other operational requirements. The solution to this dilemma is to undertake a hosting capacity (HC) study to identify the maximum penetration limit of rooftop PV generation and take necessary actions to enhance the HC of the network. This paper presents a comprehensive review of two topics: HC assessment strategies and reinforcement learning (RL)-based coordinated voltage control schemes. In this paper, the RL-based coordinated voltage control schemes are identified as a means to enhance the HC of electricity distribution networks. RL-based algorithms have been widely used in many power system applications in recent years due to their precise, efficient and model-free decision-making capabilities. A large portion of this paper is dedicated to reviewing RL concepts and recently published literature on RL-based coordinated voltage control schemes. A non-exhaustive classification of RL algorithms for voltage control is presented and key RL parameters for the voltage control problem are identified. Furthermore, critical challenges and risk factors of adopting RL-based methods for coordinated voltage control are discussed.
... Section 4.1 presents the effects of DERs on the RMS voltage performance and frequency, especially sub-voltage (sags) [29], overvoltage (swells) [165,166], frequency deviation, and control [1,167]. Section 4.2 presents the impact on HC, such as bidirectional behaviour of current, active power, nonactive power, apparent power [26,27,168], and electric protection [13]. Section 4.3 indicates that the impact on quality power begins with distortion of voltage signals [169] and current [31], which lead to indicators such as total harmonic distortion voltage (THD v ) [169] and current (THD i ) [170], total rated-current distortion (TRD) [1], short-and long-duration flicker [1,171,172], and voltage imbalance [19,79,173]. ...
Article
Distributed energy resources (DERs) have gained particular attention in the last few years owing to their rapid deployment in power capacity installation and expansion into distribution systems. DERs mainly involve distributed generation and energy storage systems; however, some definitions also include electric vehicles, demand response strategies, and power electronic devices used for their coupling with power grids. DERs challenge the entire operating system owing to their heterogeneous energy generation from renewable energy sources, the probabilistic nature of electric vehicle charging, and end-user exponential integration of power electronic devices. Research on DER integration has been conducted in the academic and industrial sectors. This study proposes a schematic literature review of DERs, including its modelling, description of deterministic and probabilistic power flow methods, power grid topologies for studies, and impacts of DERs on power grid operation. DERs are primarily modelled using probabilistic approaches. The most frequently optimized DER variables are sizing and location. Meanwhile, the most critical variables to analyse during their integration process to the power grid are voltage profile, frequency response, and charging of both lines and transformers, followed by less-proportional power quality indicators. Overall, DERs can improve the resilience of energy systems because they provide voltage and frequency support, reduce energy losses, enhance power quality indicators, and enhance energy recovery in extreme scenarios such as high-impact low-probability events.
... Nguyen et al. [14] applied a sensorless Maximum Power Point Tracking (MPPT) method for a hybrid Photovoltaic-Wind system. Heslop at al [15]. Presented a new approach to estimate the maximum PV generation that can be integrated into low voltage feeders. ...
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Energy is the basis for development of material civilization. Since fossil energy can cause environmental problems, clean energy has become the trend of energy development. Solar energy is a kind of resource-rich and clean energy. Therefore, it exists great prospects of development. In addition, the cost of photovoltaic power generation is relatively high, and governmental subsidies are required. In this paper, we propose a spatial econometric model to analyze performance of government subsidies for the photovoltaic industry. When spatial dependence is obvious, classical econometrics begins to fail. At this time, spatial econometrics came into being. This paper evaluates the support policies of photovoltaic industry based on the premise that there is spatial dependence among regions. The results show that the installed capacity of photovoltaics in various regions has begun to show a significant positive correlation since 2012.What's more, the feed-in tariff and R&D subsidy policies have played a positive role in photovoltaic installed capacity from 2012 to 2018. It significantly contributes to the transformation of photovoltaic industry policy. At the same time, this paper expands the application scope of spatial econometric model.
... For example, in [31,32], PV hosting capacity assessments of Swedish distribution grids were investigated with the voltage deviation level as the performance index. In [33,34], different PV hosting capacity assessment methodologies were proposed and discussed. The enhancement of PV hosting capacity using EMS schemes was simulated in [24,35]. ...
Article
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Photovoltaic (PV) systems and electric vehicles (EVs) integrated in local distribution systems are considered to be two of the keys to a sustainable future built environment. However, large-scale integration of PV generation and EV charging loads poses technical challenges for the distribution grid. Each grid has a specific hosting capacity limiting the allowable PV and EV share. This paper presents a combined PV-EV grid integration and hosting capacity assessment for a residential LV distribution grid with four different energy management system (EMS) scenarios: (1) without EMS, (2) with EV smart charging only, (3) with PV curtailment only, and (4) with both EV smart charging and PV curtailment. The combined PV-EV hosting capacity is presented using a novel graphical approach so that both PV and EV hosting capacity can be analyzed within the same framework. Results show that the EV smart charging can improve the hosting capacity for EVs significantly and for PV slightly. While the PV curtailment can improve the hosting capacity for PV significantly, it cannot improve the hosting capacity for EVs at all. From the graphical analysis, it can be concluded that there is a slight positive correlation between PV and EV hosting capacity in the case of residential areas.
... Moreover, voltage limits by investigating a typical UK LV distribution network [23] complied with the BS EN-50160 standard. The voltage limits as per Australian standard (−6/+10% Un) are taken into account in ( [51,84,91]) in which HC has been investigated considering voltage limits as the limiting factor complying with voltage band of 216 V-253 V. Similarly, the voltage violations as the limiting factor are defined as 0.89 p.u.-1.1 p.u. (205 V-253 V) in [92]. ...
Article
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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.
... DSOs in Australia use different method for estimating the HC. Some of them use the capacity of the feeder's transformer as the determining factor [9], [10], while some others limit the DG integration to a certain capacity [11]. For instance, Ergon Energy only assesses the DG installations that are greater than 3.5 kVA [12]. ...
Conference Paper
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Integration limits of distributed generations (DGs) in distribution networks, i.e. the hosting capacity (HC), are highly dependent on uncertainties associated with the size, location and output power of DGs. Addressing these uncertainties to a great extent is reliant on the availability and resolution of the historical data. This paper investigates the effects of data resolution and uncertainty modeling on the HC calculation. To do so, a mathematical model of the HC problem is used in a Monte Carlo-based framework. Our analysis is carried out on an agricultural distribution network in Australia. It is shown that decreasing the resolution of historical data shifts the probability distribution function of the HC towards right implying an increase in the estimated HC. Further, it is illustrated that assuming a fixed capacity for DGs instead of proper modeling of the uncertainty associated with their size results in underestimation of the HC in the network.
... Despite these obvious benefits, the integration of RESs represents a major challenge: renewable generation is variable and uncertain [14]. Therefore, the wider and wider presence of RESs is making the management of the LV network more and more difficult [15]. Thus, monitoring the real operating conditions of the LV networks in terms of power flows, phase unbalances, voltage levels and other power quality indicators becomes essential to efficiently operate these kinds of networks. ...
Article
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Up to now, the evolution of the distribution network toward the smart grid model has been essentially focused on two non-intersecting areas: medium voltage network automation and smart metering. The former one is mainly focused on improving the quality of service, studying and deploying fault location, isolation and service restoration systems, while the latter has been addressed to improve the customer relationship management, promote the customer awareness and enable new smart home services. In most cases a deep investigation of the low voltage network has been left disregarded, even if it represents the asset bridging the medium voltage level up to final customers. This network segment is probably the most affected by regulatory actions promoting intermittent renewable generations, distributed storage, heat pumps and the growing diffusion of electric vehicles utilization. The paper describes a field demonstrator of the FP7 European project IDE4L, where an extensive analysis of the low voltage network has been performed by means of an innovative use of smart meters and the installation of sensors on the medium-to-low voltage substation.
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The installed capacity of photovoltaic systems has recently increased at a much faster rate than the development of grid codes to effectively and efficiently manage high penetrations of PV within the distribution system. In a number of countries, PV penetrations in some regions are now raising growing concerns regarding integration. Management strategies vary considerably by country - some still have an approach that photovoltaic systems should behave as passive as possible while others demand an active participation in grid control. This variety of grid codes also causes challenges in learning from 'best practice'. This paper provides a review of current grid codes in some countries with high PV penetrations. In addition, the paper presents a number of country-specific case studies on different approaches for improved integration of photovoltaic systems in the distribution grid. In particular, we consider integration approaches using active and reactive power control that can reduce or defer expensive grid reinforcement while supporting higher PV penetrations.
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One of the main factors that may limit the penetration level of distributed generation (DG) in typical distribution systems is the steady-state voltage rise. The maximum amount of active power supplied by distributed generators into each system bus without causing voltage violations can be determined by using repetitive power flow studies. However, this task is laborious and usually time-consuming, since different loading level and generation operation modes have to be evaluated. Therefore this article presents a method that, based on only one power flow solution and one matrix operation, can directly determine the maximum power that can be injected by distributed generators into each system bus without leading to steady-state voltage violations. This method is based on the determination of voltage sensitivities from a linearised power system model. In addition, this article proposes a numerical index to quantify the responsibility of each generator for the voltage level rise in a multi-DG system. Based on this index, utility managers can decide which generators, and in which degree, should be penalised by the voltage rise or rewarded by not depreciating the voltage profile. The method is applied to a 70-bus distribution network. The results are compared with those obtained by repetitive power flow solutions in order to validate the proposed method.