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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. ...

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. ...

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).

... 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. ...

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. ...

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). ...

... 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. ...

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. ...

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. ...

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]. ...

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. ...

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]. ...

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]. ...

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]. ...

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. ...

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.

Evaluation of the maximum connected solar photovoltaic (PV) capacity without violating stipulated network voltage limits is essential in managing the voltage rise in low-voltage (LV) networks under increasing solar penetration levels. In this regard, this paper reviews recent investigations completed in relation to solar PV hosting capacity (HC) assessment work in LV networks. A feeder based approach developed for evaluating solar PV HC constrained by over-voltage conditions in LV networks is summarised. Further, a novel nomographic tool developed for HC calculation based on the influential factors on HC as identified by solar PV location, feeder length/loading levels, conductor type and stipulated voltage limits, is reviewed. In addition, a three-stage solar PV connection criteria which was developed based on the rigorous outcomes of nomogram and the feeder based evaluation approach is presented in the paper. The HC assessment and solar PV connection criteria presented in this paper would be a contribution to further improvement of the available utility guidelines/standards on solar PV installations in LV networks.

The unregulated penetration of distributed generation (DG) on distribution networks can cause wide-ranging technical issues, such as voltage variation, thermal loading, and unbalance. To regulate penetration, a planner needs to determine the maximum penetration or hosting capacity (HC) of a network, which requires extensive studies assessing the technical impacts of DG on the most sensitive quality of supply variables. Several uncertainties complicate the HC computation, such as the stochasticity of customer loads, variable DG outputs, and unknown location and capacity of future DG installations. This uncertainty demands approaches with the capability of stochastic simulation of DG allocation and probabilistic assessment of the corresponding range of feeder performance. Existing uncertainty-based HC computation methods have inadequate probabilistic representation, high computational burden, and restricted scope of technical variables, reducing any confidence in the assessed HC. We use a stochastic analytic-probabilistic approach that embeds an analytic probabilistic load flow (PLF) transform in a Monte-Carlo simulation (MCS) of DG allocation, and applies a polynomial smoothing technique to further enhance computational efficiency. The acceptable variation of radial distribution feeder performance is identified by voltage limits, thermal capacity, and unbalance. The PLF has significant benefits in reducing the overall computational burden. The HC is quantified statistically using the beta probability density function, reflecting the composite risk from the multiple uncertainties. Compared with other formulations, this stochastic-analytic approach to HC improves feeder performance evaluation under a wide range of DG penetration scenarios and is appropriate for design and operational analysis.

Proliferation of solar photovoltaic (PV) generation in low voltage (LV) distribution networks has imposed a set of challenges in network operation and control. Voltage rise is currently the main constraint that limits solar PV capacity increase in LV networks. Together with this, there is a growing need for a generalised and versatile tool which utilities can use to deal with customer requests for new solar PV connections. This paper proposes a generalised approach to assess solar PV hosting capacity (HC) subjected to over-voltage curtailment based on a Nomogram representation, which facilitates reasonable modeling insights for HC assessment in LV networks. In addition, solar PV connection criteria are further developed using the Nomogram representation of HC evaluation. The proposed Nomogram based approach for HC assessment and connection criteria will contribute to further improvement of available guidelines on solar PV connections in LV networks.

This paper presents a review of the impact of rooftop photovoltaic (PV) panels on the distribution grid. This includes how rooftop PVs affect voltage quality, power losses, and the operation of other voltage-regulating devices in the system. A historical background and a classification of the most relevant publications are presented along with the review of the important lessons learned. It has been widely believed that high penetration levels of PVs in the distribution grid can potentially cause problems for node voltages or overhead line flows. However, it is shown in the literature that proper control of the PV resource using smart inverters can alleviate many of those issues, hence paving the way for higher PV penetration levels in the grid.

There is an ever-growing number of photovoltaic (PV) installations in the US and worldwide. Many utilities do not have complete or up-to-date information of the PVs present within their grids. This research presents a deep neural network approach for estimating PV size, tilt, and azimuth using only behind-the-meter data. It is found that the proposed deep neural network (DNN) method can estimate PV size with an error of 2.09% in a data set with fixed tilt and azimuth values and 3.98% in a data set with varying tilt and azimuths. This is a lower error than the benchmark linear regression approach. A net load data resolution of 1 min provides the lowest error when estimating the PV size. The proposed DNN is also reasonably robust to erroneous training data. When applied to estimate PV tilt and azimuth, the proposed method achieves a mean absolute percentage error of 10.1% and 2.8% respectively. These error metrics are 2.0× and 3.7× lower, respectively, than the benchmark linear regression achieves. It was observed that a higher data resolution (1 min) does not provide significant gains in accuracy. It is recommended that a data resolution of 60 min is used to reduce the effects of phenomena such as cloud enhancements. The proposed deep neural network approach is also highly robust, maintaining reasonable accuracy with high levels of mislabeled training data.

A literature review is presented in this paper of the methods for quantifying the solar PV hosting capacity of low-voltage distribution grids. Three fundamentally different methods are considered: i) deterministic ii) stochastic iii) time series. The methods’ outline of applications, merits and shortfalls are summarized. The methods differ in the input data, accuracy, accuracy, computation time, consideration of uncertainties, consideration of the time-related influence and the models used. Two types of uncertainties need to be considered: certain (aleatory) uncertainties and uncertain (epistemic) uncertainties. The latter ones are only included in some of the stochastic methods.
In most of the reviewed publications, the voltage magnitude rise and increased loading with increased risk of overvoltage and overloading (for lines, cables and transformers) were the main phenomena considered in the hosting capacity study.
This review offers guidelines for distribution system planners on which hosting-capacity method to be used and to researchers on research gaps.

Australia has one of the highest penetrations of residential PV in the world and is projected to see substantially more deployment in coming years, with a growing proportion of this being coupled with battery energy storage (BES). Previous analysis of the implications of these residential distributed energy resources (DERs) has tended to focus on the individual private benefits to households that deploy them, their direct technical and revenue impacts on network businesses, or broader electricity industry implications. This paper seeks to quantify the economic impacts of residential PV and BES on electricity network businesses, from residential to wholesale market region level. One key impact is reductions in network business revenues as households purchase less electricity from the grid. However, we also consider the potential savings for network businesses as these PV and BES deployments reduce peak network demand from residential to wholesale market level, a key driver of network investment and hence network business costs. Our findings for the Sydney region suggest that potential network investment cost reductions could even outweigh the loss of revenue. Tariff design will have a key role in ensuring that residential PV and BES deployment offers value both to households as well as network businesses.

This paper presents the smart public transportation network expansion and its interaction with the grid. Electric buses have been used to perform the mass transportation in the Guwahati city, Assam, India. Electric buses receive energy from the electric bus stops that are present through the ring road of the Guwahati city. A high capacity energy storage device and the solar plant have been connected to every bus stop, to achieve the smooth performance of the smart public transportation network. In this work, the capa-buses (supercapacitor based buses) and the electric vehicles have been used along with the electric buses to expand the electrified transportation network in the Guwahati city. Algorithm based controllers are responsible to control the energy flow between the high capacity energy storage device, the capa-buses and the electric vehicles. Fuzzy logic controller is present at every bus stop to control the energy flow between the grid, the energy storage device and the solar plant. The complete system response has been verified through Simulations: for different situations in all the seasons of a year and for the uncertain situations that exist in the system. This system is helpful to improve the air quality in city region and also improves the voltage profile of the grid.

The increasing presence of Distributed Generation (DG) at distribution level is worsening the network power quality with higher waveform distortion and voltage variations, and growing the cable and transformer loading level. Otherwise, DG can positively impact the network by increasing the voltage profile in those networks affected by voltage drops, reducing losses, helping Distribution Network Operators (DNO) fulfil regulator’s requirements and avoiding penalty by reducing the numbers of voltage drops and interruptions.
In Medium Voltage (MV) network planning studies, LV networks are generally represented as aggregated loads at MV level but, in order to correctly evaluate the effectiveness of possible no network solutions as valuable alternatives to the traditional network reinforcements (identifying voltage constraints on LV networks and so defining the possible improvements), a more realistic model is needed.
To this end, a simplified LV network model, that could be easily integrated in a probabilistic electrical simulation tool that simulates all the nodes of the MV network level (whilst having an aggregated view of maximum possible voltage rises and drops at the LV level), has been developed. The model is based on a matrix containing the main information of the LV network: number of feeders, lines parameters (resistance and reactance), load demand (active and reactive power), nominal power of the generators installed and their location in the network.

Unbalance of the three-phase currents in photovoltaic (PV) systems may depend on structural aspects of the installation, the effect of partial shading, or both. In this paper, a number of unbalance indicators are calculated starting from data that are measured during experimental analyses on a real building-integrated PV system that represents different types of unbalance. Detailed information is obtained from indices that identify the balance and unbalance components that are also in the presence of waveform distortion. These indices extend the current definitions of unbalance given in the power quality standards. The results show that the unbalance cannot be considered negligible, even with no single-phase inverters and is more significant if nonlinear loads add a contribution to both harmonic distortion and unbalance seen from the distribution transformer.

The penetration of residential photovoltaic (PV) panels is increasing particularly in those countries with special incentives. The total PV installed capacity in the UK has increased from negligible to 1.2 GW since the Feed-In Tariff scheme was created in 2010. As a result, Distribution Network Operators (DNOs) are already experiencing voltage issues in low voltage (LV) feeders were clusters have appeared. This work proposes a Monte Carlo-based technique to assess the impacts of different PV penetrations on LV networks in order to estimate their corresponding hosting capabilities. Three-phase models of two real LV networks in the North West of England are studied considering 5-min resolution synthetic data for domestic load and PV generation. Voltage-related impacts are measured using the European Standard EN50160. Additionally, the importance of data granularity on the impact assessment is analyzed. Results for the studied LV networks indicate that feeders with greater lengths and larger number of customers tend to experience voltage issues with lower PV penetration levels. In terms of the granularity, it was found that hourly resolution analyses underestimate the voltage impacts of residential PV.

This paper presents simulation results for a taxonomy of typical distribution feeders with various levels of photovoltaic (PV) penetration. For each of the 16 feeders simulated, the maximum PV penetration that did not result in a steady-state voltage or current violation is presented for several PV location scenarios: clustered near the feeder source, clustered near the midpoint of the feeder, clustered near the end of the feeder, randomly located, and evenly distributed. In addition, the maximum level of PV is presented for single, large PV systems at each location. Maximum PV penetration was determined by requiring that feeder voltages stay within ANSI Range A and that feeder currents stay within the ranges determined by overcurrent protection devices. Generation ramp rates, protection and coordination, and other factors that may impact maximum PV penetrations are not considered here. Simulations were run in GridLAB-D using hourly time steps over a year with randomized load profiles based on utility data and typical meteorological year weather data. For 86% of the 336 cases simulated, maximum PV penetration was at least 30% of peak load.

In a geographically small distribution area, fast moving clouds may cover the whole area within a short period causing photovoltaic (PV) power to drop. When a feeder loses PV power support, bus voltages will decrease. In an unbalanced network, asymmetrical spacing and non-transposition of line configurations can result in different voltage drops for each phase. This may potentially cause some voltage problems after a decline in PV generation, such as an extremely low voltage magnitude of a certain phase and an unacceptable voltage imbalance level at a remote bus. This paper proposes a method of analyzing voltage variation sensitivity due to PV power fluctuations in an unbalanced network (unbalanced line configuration and phase loading levels). Based on this method, a network reconfiguration solution is developed to solve the voltage problems. This solution utilizes unbalanced line characteristics and realizes the potential of the network, so no extra compensation devices are needed for network support.

With increasing level of rooftop solar photovoltaic (PV) penetration into low voltage (LV) distribution networks, analysis with realistic network models is necessary for adequate capturing of network behavior. Traditional three-phase 3-wire power flow approach lacks the capability of exact analysis of 4-wire multigrounded LV networks due to the approximation of merging the neutral wire admittance into the phase wire admittances. Such an approximation may not be desirable when neutral wire and grounding effects need to be assessed, especially in the presence of single-phase solar power injection that may cause a significant level of network unbalance. This paper proposes a three-phase power flow approach for distribution networks while preserving the original 3-wire and 4-wire configurations for more accurate estimation of rooftop PV impacts on different phases and neutrals. A three-phase transformer model is developed to interface between the 3-wire medium voltage (MV) and the 4-wire LV networks. Also an integrated network model is developed for an explicit representation of different phases, neutral wires and groundings of a distribution system. A series of power flow calculations have been performed using the proposed approach to investigate the impacts of single-phase variable PV generation on an Australian distribution system and results are presented.

The objective of this paper is to provide an assessment on voltage profiles in residential neighborhoods in the presence of photovoltaic (PV) systems. The network was modeled in PSCAD using common feeder characteristics that Canadian system planners use in suburban residential regions. A simulation study was performed to investigate potential voltage rise issues in the network up to 11.25% total PV penetration in the feeder and LV transformer capacity penetration up to 75%. Results indicate 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. Moreover, the role of feeder impedance, feeder length, and the transformer short circuit resistance in the determination of the voltage rise is quantified.

The present paper aims at assessing the effects produced on the
distribution system by dispersed generators directly connected to LV
networks. In particular, the introduction of photovoltaic (PV)
generation systems has been studied, since such systems are the only
ones having a natural inclination to be easily integrated into high
density urban LV distribution networks. In the proposed study some
aspects of the quality of power supplied to the customers will be dealt
with taking into consideration slow voltage variations. In this regard
the effect of dispersed generation (DG) on the voltage profile of a LV
distribution feeder has been examined. With reference to a different
kind of load distribution along the line, analytical expressions have
been derived to determine the limit value of the power that can be
injected into the distribution network without causing overvoltages.
These expressions have been developed under some simplifying hypothesis
related both to the DG unit and to the distribution network

A new concept of Photovoltaic (PV) grid-parity is presented for three typical case studies in Europe by including the distribution-network limits and the fixed costs of the electricity bills. Real cases are described for residential/tertiary sector loads: the PV penetration results, achieved without investments in the distribution upgrading, are presented through the ratio of the admissible PV energy ratio which can be close to 30% of the total consumption for residential users and 45% for tertiary-users. The future approach of distribution limits certainly will increase the electricity bills which have been analysed here in the current situation: in Germany the fixed costs are negligible, whereas in Italy the common loads of apartment-blocks are charged by the cost of the available power. The grid-parity problem is analysed by the net present value which provides the cost effectiveness or not of the PV installation. The results are obtained by the interest rates of 3–6% in Germany and 4–10% in Italy. The grid-parity for dwelling houses and tertiary-sector users is reached in Germany and Central/Southern Italy; it is achieved in Germany for the users in apartment-blocks, while it is unrealistic to be reached in Italy with the current tariff situation.

Photovoltaic generating units connected to distribution systems represent a type of distributed generation (DG) that has been experiencing increased growth in recent years. Higher DG penetration levels may be interesting from many different points of view, but raise important issues about distribution system operation. Therefore, new techniques are needed to determine the maximum amount of DG that may be installed without requiring major changes in the existing electric power system. According to the literature, voltage rises at load bus bars are a serious limiting factor when installing DG. This paper presents and discusses studies proving that conductor ampacity and voltage rises are limiting factors that manifest themselves under different conditions. The present study highlights situations in which line overloads are more restrictive than voltage rises. Variation in substation voltage, load, and its power factor were simulated in a simplified radial distribution system model, and the amount of distributed generation that may be installed was obtained. Mathematic formulae were developed to determine the amount of distributed generation for existing utility systems.

Present renewable portfolio standards are changing power systems by replacing conventional generation with alternate energy resources such as photovoltaic (PV) systems. With the increase in penetration of PV resources, power systems are expected to experience a change in dynamic and operational characteristics. This paper studies the impact of increased penetration of PV systems on static performance as well as transient stability of a large power system, in particular the transmission system. Utility scale and residential rooftop PVs are added to the aforementioned system to replace a portion of conventional generation resources. While steady state voltages are observed under various PV penetration levels, the impact of reduced inertia on transient stability performance is also examined. The studied system is a large test system representing a portion of the Western U.S. interconnection. The simulation results obtained effectively identify both detrimental and beneficial impacts of increased PV penetration both for steady state stability and transient stability performance.

This paper investigates the operation and protection issues on distribution systems with high penetration of residential PV systems. Residential PV systems represent small scale resources and therefore they have different impacts on a distribution circuit than larger scale resources. The paper considers a typical residential distribution system and shows that determining the fault current profile and voltage variations on such systems becomes more challenging. However, the impacts on system protection and voltage variation are not severe on such systems, and thus, high level penetration can be accommodated provided that proper revisions are made to the protection and voltage control schemes.

We assess the effects that size and locations of photovoltaic (PV) arrays in a low-voltage (LV) electric power grid have on the maximum installable capacity. The objective is to place and control PVs without violating voltage limits and not require interventions by utilities. Multi-modal control is suggested whereby the PVs deviate from unity power factor and begin to supply reactive power if the voltage limits are approached; the installed capacity need not ever be disconnected. Given such multi-modal control, it is shown that the best location of a large PV farm is at the load located furthest away from the medium voltage step-down transformer. Furthermore, we show that the maximum installable capacity increases if the capacity is distributed as many smaller "rooftop" PVs.

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.

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.