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Researching cluster partitioning and adjustment methods is essential for effectively implementing cluster control strategies and ensuring the safe operation of power grids amid challenges like reverse power flow and voltage violations resulting from large-scale distributed photovoltaic grid integration. The paper comprehensively evaluates factors including electrical distance, supply-demand balance, and power transmission. It introduces a method for partitioning and dynamically adjusting distributed photovoltaic clusters, based on an improved adaptive genetic algorithm (AGA). Firstly, a comprehensive performance index is introduced based on modularity, incorporating intra-cluster power supply rate and inter-cluster power transmission. Next, an unweighted adjacency matrix is employed to encode chromosomes, and an adaptive optimization parameter adjustment strategy is introduced to enhance the AGA, ensuring both direct node connectivity within clusters and improved global solution performance during optimization. By integrating these comprehensive indicators with AGA, a cluster partitioning optimization model is formulated based on the comprehensive indicator system. The IEEE 33-node system is utilized for cluster partitioning simulation analysis with this model. The outcomes demonstrate that, in contrast to the single modularity index-based cluster partitioning approach, the proposed comprehensive indicator method enhances the intra-cluster active and reactive power supply rates by approximately 20.34% and 28.61%, respectively, while decreasing inter-cluster power transmission by roughly 24.98%. Furthermore, in scenarios of insufficient photovoltaic power output, the cluster scheme, after dynamic strategy adjustment, notably mitigates system voltage fluctuations and network losses. [ABSTRACT FROM AUTHOR]

A method for assessing the maximum access capacity (MAC) of distributed photovoltaic (PV) in distribution networks (DNs) considering the dispatchable potential of 5G base stations is proposed. First, a 5G base station electricity load demand model is constructed, and the dispatchable potential of self-provided energy storage for 5G base stations is analyzed; then a distributed grid distributed PV MAC assessment model considering the dispatchable potential of 5G base stations is established; second, an auxiliary variable is introduced and the model is subjected to second-order conical relaxation, and a linearized model for distributed PV MAC assessment is constructed. Finally, the improved IEEE 33-node DN was applied to assess the MAC of distributed PV in DN under different scenarios. The results of the analyses of the algorithms show that considering the dispatchable potential of 5G base stations can significantly enhance the MAC of distributed PV in the DN. [ABSTRACT FROM AUTHOR]

Kinmen, the famous Cold War island also known as Quemoy, is a typical island with isolated power grids. It considers the promotion of renewable energy and electric charging vehicles to be two essential strategies to achieve the goal of a low-carbon island and smart grid. With this motivation in mind, the main objective of this study is to design and deploy an energy management system for hundreds of current PV sites distributed on the island, energy storage systems, and charging stations on the island. In addition, the real-time acquisition of the data for power generation, power storage, and power consumption systems will be used for future demand and response analysis. Moreover, the accumulated dataset will also be utilized for the forecast or prediction of renewable energy generated by the PV systems or power consumed by the battery units or charging stations. The results of this study are promising since a practical, robust, and workable system and database are developed and implemented with a variety of Internet of Things (IoT), data transmission technologies, and the hybrid of on-premises and cloud servers. Users of the proposed system can remotely access the visualized data through the user-friendly web-based and Line bot interfaces seamlessly. [ABSTRACT FROM AUTHOR]

• An innovative model for an electric bus system considering distributed photovoltaics is developed. • We simultaneously optimize the infrastructure planning and charging schedule. • We investigate not only the economic but also environmental benefits by considering PV into the electric bus system. • We conduct a sensitivity analysis to better understand the proposed model. The global focus on emissions reduction has grown significantly, leading to the emergence of Battery electric buses (BEBs) as a promising eco-friendly alternative to conventional buses. However, the high charging power induced by fast charging can burden the power grid and incur high demand charges. Distributed solar photovoltaics (PV) can play an important role in reducing peak load and charging costs. In this study, we address the problem of optimal planning and charging schedule for an electric bus system using fast-charging technology. We proposed a mathematical model to optimize the BEB charging schedule and PV planning such that the total cost of the system is minimized. A real bus network in Utah was adopted to validate the efficacy of the proposed models. The results demonstrated that integrating an energy storage system (ESS) and distributed PV can significantly reduce costs and increase the proportion of renewable energy used for BEB charging. [ABSTRACT FROM AUTHOR]

The integration of a high proportion of distributed PV into distribution networks can cause power backfeeding and voltage limit violations. This paper introduces moment difference analysis theory for distribution networks, reframing PV consumption as the balancing moment difference equations. When maximum node voltage approaches the upper limit, the moment difference between PV and load stabilizes to an approximately constant, termed the standard moment difference. The standard moment difference represents the limit of the network's capacity to consume distributed PV. Essentially, the PV moment is the target for integration, while the load moment serves as the resource to consume the PV moment. Based on this theory, a method for energy storage configuration is proposed. Simplifying a complex multi-branch distribution network into single-branch lines and solving linear equations determines the optimal storage configuration. This method was tested on the Jibei Power Grid and the IEEE 33 and 69 bus systems, increasing computational efficiency by 1611.47–4973.82 times compared to the PSO algorithm, while maintaining an error margin of less than 2.6 %. Furthermore, the discharging strategy reduces the ESS capacity to between 12.39 % and 31.69 % of the original estimate, thereby enhancing both the economic and practical appeal of the approach. • Proposes moment difference theory, reframing PV consumption as balance equations. • PV and load moment difference is a constant termed the standard moment difference. • Load moment as the resource to absorb the PV moment targeted for integration. • Establishes energy storage configuration method based on moment difference theory. [ABSTRACT FROM AUTHOR]

This study analyses distributed photovoltaic (D-PV) system curtailment and impacts on consumers in response to high network voltages. Novel analytical techniques are applied to a unique real-world operational dataset of over 1300 D-PV systems in South Australia to identify 'tripping'. Data-driven methods are valuable due to the diverse range of D-PV conditions. South Australia is an insightful case study due to its D-PV rich network, where around one third of standalone housing now has a PV system. Findings suggest that overall curtailment is low, however some sites experience significant impacts of up to 46–95% curtailment per day, particularly during spring. The uneven distribution of impacts raises concerns regarding fairness, however network solutions to increase hosting capacity must be carefully balanced given the potential costs imposed on consumers without D-PV. Upscaling the estimated D-PV generation loss to all of South Australia indicates a total value of $1.2m-$4.5m per year in lost value to consumers with D-PV, considering clear sky days. Implications for policy makers and network operators are discussed in the context of strong projected D-PV uptake in Australia, and around the world. It is proposed that data-driven methods could inform future regulatory assessment processes to improve outcomes for all consumers. [ABSTRACT FROM AUTHOR]

This paper presents a 3 HP solar direct-drive photovoltaic air conditioning system which operates without batteries, ice thermal storage is used to store solar energy. The refrigeration compressor will suffer from loss of power even cannot startup or shut down if the PV power generation suddenly fluctuates. In the case of the solar radiation fluctuations to keep the system running continuously and steadily, that requires a proper system design to match the power consumption of solar air conditioning system with a proper PV capacity, matching an adaptive controller and a suited compressor simultaneously. Solar air conditioners with different capacity of PV panel, with and without MPPT controller and different types compressors were built and tested outdoors to experimentally investigate the matching characteristics of photovoltaic disturbance and refrigeration compressor. The experimental results of the system with a variable speed compressor and a MPPT controller have shown good ice-making performance and reliable operation as well as a great improvement in the available solar energy. Finally, the highest system COP reached 0.289 when the cumulative daily total radiation was 18.2 MJ/m2 in Kunming, China. The research work shows that the direct drive ice storage by solar photovoltaic system has a certain application prospect in the regions where the electricity is tight but requiring cooling. • Design of air conditioner directly driven by distributed solar PV was studied. • Ice thermal storage was used to completely replace batteries. • A MPPT controller was design to effectively utilize solar energy. • Variable speed compressor was suited for PV directly driven cooling. [ABSTRACT FROM AUTHOR]

• NYSolarCast is an open-source solar forecasting system configurable for any region. • NYSolarCast predicts gridded GHI and both utility-scale and distributed PV power. • NYSolarCast integrates NWP models, machine learning, and real-time weather data. • NYSolarCast was validated for 1 year of 0–6-h GHI and power forecasts in New York. • NYSolarCast GHI forecasts performed comparably to a commercial reference forecast. Solar energy generation capacity will need to be greatly increased to meet aggressive clean energy targets by New York State (NYS), which are 70% renewable energy (RE) generation by 2030, and 100% by 2040. Because solar energy is a variable, weather-driven resource, accurate forecasts of solar energy generation both in nowcast (intra-day) and day-ahead time horizons are necessary for electric utilities and independent system operators, as they maintain grid stability and maximize RE use. Meeting this need for NYS, a gridded, open-source solar power forecasting system called NYSolarCast was developed (https://github.com/ncar/NYSolarCast%5fdelivery). NYSolarCast makes 15-min resolution predictions of global horizontal irradiance (GHI) on a 3-km grid covering all of NYS, which are then used to estimate solar power generation both for select utility-scale PV plants (15-min resolution) and for zone-aggregated distributed PV (1-h resolution). The statewide GHI forecasts are made by applying the StatCast statistical forecasting model, which is trained on over two years of GHI observations from pyranometers at all 126 NYS Mesonet stations and gridded numerical weather prediction forecasts from both the Weather Research and Forecasting model tuned for solar applications (WRF-Solar®) and NOAA's operational High-Resolution Rapid Refresh (HRRR) model. Forecasts are made at each NYS Mesonet site and then blended outward into the rest of the grid. This paper gives an overview of NYSolarCast performance for intra-day (0–6-h) GHI and power forecasts during a one-year period. [ABSTRACT FROM AUTHOR]

In this paper, a novel topology of modular dc–dc converter has been proposed for medium voltage dc (MVdc) integration of high-penetration distributed PV. The proposed topology is featured with input-independent and output-series connected configuration and intermodule power balancing units (PBUs). A high voltage gain could be achieved with series-connected submodules (SMs), while each SM's input port is connected with PV array to realize the independent maximum power point tracking (MPPT) control function. PBUs with bidirectional power conversion ability are installed between adjacent SMs for the elimination of intermodule power mismatch. The operation principles of the proposed converter have been explained in detail along with the corresponding control strategies. The design principles of major passive components have been investigated on the basis of boundary operation conditions, while a quantitative analysis of steady-state power losses has been performed. Moreover, a comparative study is conducted from the aspects of operation range, topology complexity, component stress, and power efficiency. The theoretical results have been validated by both simulations and down-scaled experiments. [ABSTRACT FROM AUTHOR]

As subsidies continue to fall, the technology and cost performance of distributed photovoltaic (PV) determines the progress of its grid parity. Based on the discussion of technology and cost, this paper analyzed the economic performance of China's distributed PV industry by utilizing the two indicators of levelized cost of energy (LCOE) and internal rate of return (IRR). The results show that: firstly, the current external environment is generally conducive to the development of distributed PV, but there are still some constraints. Secondly, with the decrease of unit investment cost, distributed PV can achieve the goal of parity before 2025. Thirdly, distributed PV projects in the three types of solar energy resources all have high IRR, and the economic performance is better for the projects with high proportion of spontaneous self-use. At the end of the paper, policy recommendations are offered as references for the government. • We comprehensively analyzed the technology and cost performance of China's distributed PV. • We focused on the trend and decline path of China's distributed PV costs. • The LCOE of distributed PV in China is expected to achieve full parity in 2025. • Except 100% grid-connected mode, the IRR of distributed PV power plants in three areas is higher than 8% which has shown good economic benefits. [ABSTRACT FROM AUTHOR]

Abstract Household distributed photovoltaic (PV) can supply clean power directly to the end users. With the rapid growth of the distributed PV installed capacity, the problems of PV grid connection and PV consumption are becoming more and more serious in China. It is an effective means to improve the efficiency of PV system by promoting the home self-consumption of PV generation. In this study, a residential demand response model considering distributed PV consumption based on dynamic electricity price is proposed. The household users are classified into several types with different power consumption preferences in this model. Both the comfort and economy of power consumption are quantified to describe the users' satisfaction. The model is established with two goals, maximizing the users' satisfaction meanwhile minimizing PV power into the grid. Then a solution algorithm based on NSGA-II is proposed to solve the model. Finally, an example study based on China's PV policy is presented, and the results show that the model has certain advantages in improving the users' satisfaction and increasing the rate of self-consumption of PV generation. In addition, sensitivity analysis of the provincial government's PV subsidies in China is also carried out and the relevant policy recommendations are presented. Highlights • Household users are classified into several types with different preferences. • The UEV with users' power consumption comfort and economy is designed. • Exploiting the interaction between users and the power grid for PV consumption. • Sensitivity analysis of the provincial government's PV subsidies in China. [ABSTRACT FROM AUTHOR]

Abstract In this paper, an integrated control strategy for a solar cooling system directly driven by distributed photovoltaics (PVs) without a battery is proposed; this strategy matches the optimal operating impedance of the PV array by periodically perturbing the running frequency of the compressor. The theoretical working principle of the control strategy is explained, and two experimental processes are analysed under different solar irradiance levels. Furthermore, comparative tests of the control system with and without a controller were conducted to evaluate the performance of the solar cooling system. The results of the experiment under the impedance matching control strategy reveal that the average photoelectric conversion efficiency reached approximately 0.129 and improved by 83.7% relative to the control system without a controller. The coefficient of performance (COP solar) reached 0.263 using an ice thermal storage model, which was an improvement of 60.4%. The compressor ran continually when the instantaneous irradiance exceeded 143 W/m2. The average efficiency of the control system reached 0.96, and the average three-phase power factor was approximately 0.71. The COP of the refrigeration unit was 2.10, and the total cooling capacity was 103.5 MJ, which was sufficient for cooling a 25.5-m2 air-conditioned room for 8.5 h. Highlights • An impedance matching control strategy for solar cooling system was proposed. • The impedance matching relationship was verified with theory and experiments. • Comparative tests with and without controller were conducted for proposed system. • The compressor ran stably when the instantaneous irradiance exceeded 143 W/m2. • The COP solar reached 0.263 in ice-making thermal storage model. [ABSTRACT FROM AUTHOR]

Storage energy is an effective means and key technology for overcoming the intermittency and instability of photovoltaic (PV) power. In the early stages of the PV and energy storage (ES) industries, economic efficiency is highly dependent on industrial policies. This study analyzes the key points of policies on technical support, management drive, and financial support. Focusing on the efficiency of PV power and the power load of users, including households and enterprises, in Shanghai City over 24 h in 2016, this study analyzes the costs, benefits, internal rates of return, and investment recovery periods of distributed PV (DPV) and ES systems in the current policy context. This study also discusses the influences of various policy variables, including the ES battery capacity, the peak-valley price ratio, feed-in tariffs for DPV, and the ratio of grid-connected surplus PV power, on economic efficiency. The results show that in China's current policy context, both household and enterprise users of PV power would gain some economic benefits if PV systems were fitted with aqueous sodium-ion batteries of an appropriate capacity. Finally, this study offers some additional government policy suggestions. [ABSTRACT FROM AUTHOR]

Summary: Access to energy has increasingly been provided by the Chinese Government via new alternative energy sources known as renewables in recent years. Meanwhile, the development and use of environmentally friendly renewables gradually become the basic requirements for the sustainable development in the future society. The integration of blockchain technology with distributed photovoltaic (PV) energy may break the existing pattern where the production, transportation, distribution, and sales of energy are centralized. This paper first reviews the current overall situation of China's distributed PV and further analyzes the policy environment with respect to the development of distributed PV. On the basis of the analysis of the status quo, the paper then discusses the internalities (strengths and weaknesses) and the externalities (opportunities and threats) that have driven the development of China's distributed PV by illustrating the SWOT analysis. The data structure and characteristics of blockchain are analyzed to identify the application mode of blockchain technology in the distributed PV industry for the first time. Through our research, some conclusions and policy proposals are finally put forward to provide support to the formulation of related policy in the Chinese Government and industry association. [ABSTRACT FROM AUTHOR]

Summary: Access to energy has increasingly been provided by the Chinese Government via new alternative energy sources known as renewables in recent years. Meanwhile, the development and use of environmentally friendly renewables gradually become the basic requirements for the sustainable development in the future society. The integration of blockchain technology with distributed photovoltaic (PV) energy may break the existing pattern where the production, transportation, distribution, and sales of energy are centralized. This paper first reviews the current overall situation of China's distributed PV and further analyzes the policy environment with respect to the development of distributed PV. On the basis of the analysis of the status quo, the paper then discusses the internalities (strengths and weaknesses) and the externalities (opportunities and threats) that have driven the development of China's distributed PV by illustrating the SWOT analysis. The data structure and characteristics of blockchain are analyzed to identify the application mode of blockchain technology in the distributed PV industry for the first time. Through our research, some conclusions and policy proposals are finally put forward to provide support to the formulation of related policy in the Chinese Government and industry association. [ABSTRACT FROM AUTHOR]

Energy storage can help integrate local renewable generation, however the best deployment level for storage remains an open question. Using a data-driven approach, this paper simulates 15-min electricity consumption for households and groups them into local communities of neighbors using real locations and the road network in Cambridge, MA. We then simulate PV for these households and use this framework to study battery economics in a high PV adoption, high electricity cost scenario, in order to demonstrate significant storage adoption. We compare the results of storage adoption at the level of individual households to storage adoption on the community level using the aggregated community demands. Under the simulated conditions, we find that the optimum storage at the community level was 65% of that at the level of individual households and each kWh of community battery installed was 64–94% more effective at reducing exports from the community to the wider network. Therefore, given the current increasing rates of residential battery deployment, our research highlights the need for energy policy to develop market mechanisms which facilitate the deployment of community storage. [ABSTRACT FROM AUTHOR]

A recent upsurge of investment in photovoltaic (PV) industry in China has made outstanding contributions to the adjustment of energy structure. In order to further promote the investment and construction of PV projects, the state has published many fiscal subsidy policies. In addition to unified national subsidy standard, local standards have been developed according to local fiscal revenue. They either have greatly improved return on investment (ROI) or have no significant effect as a result of too many impact factors. This paper utilizes multi dimensional big dates of distributed PV projects to obtain the weight of factors influencing the ROI from the calculation equation of ROI, which is fitted with innovative big data mining method of LSSVM-PSO. Results show that construction cost, sunshine duration, retail electricity tariff and subsidy have the greatest impacts. This study provides decision makers with quantitative basis for more comprehensive understanding on economic aspect of the distributed PV projects. [ABSTRACT FROM AUTHOR]

Promoting the penetration of distributed photovoltaic systems (PV) at the end-user side is an important and urgent task. This study aims to evaluate the promotion impact of the response capability of smart home consumers on the distributed PV penetration using non-cooperative game theoretical analysis. In the analysis, the Nash equilibrium can be found for consumers with different levels of demand response capability in an electricity market with real-time pricing (RTP) mechanism under different PV installed capacities and battery capacities. As a case study, 5 levels of consumers’ response capability, 32 combinations of PV installed capacities and battery capacities were analyzed and inter-compared using the developed model. The results show that: (i) the consumers with higher response capability are able to accept larger PV capacity because the marginal revenue of new installed PV for smart consumers decreases much more slowly compared to that of a common consumer; (ii) the consumers with higher response capability need less batteries to promote PV economic acceptability; (iii) the consumers with higher response capability can meet the electricity demand in real-time with least expenditure, so they get more ultimate benefit from the games. [ABSTRACT FROM AUTHOR]

The PV Industry is a strategic emerging industry in China. With extensive application, easy local accommodation and little impact on the power grid, distributed PV power generation is viewed as a major way of PV power generation in the future. In recent two years, the Chinese government has rolled out policies concerning distributed PV power generation, in the hope to quickly expand the domestic market, ease the impact on the PV industry from global market fluctuations and reduce the excess capacity of the PV industry. However, distributed PV power generation faces complex financing problems at home with the unclear definition of rooftop property rights, risks in PV power generation policies, risks in the access to power grids and uncertainties in profitability. The paper summarizes that China must improve laws, polices and management institution to dissolve the financing risks related to distributed PV power generation. [ABSTRACT FROM AUTHOR]

The recent rapid development of distributed PV (photovoltaic) industry in China closely ties to the relevant policies support. This paper reviews some main points of relevant policies including financial support, technology innovation and management improvement. Scenario analysis both in residential sectors and industrial and commercial sectors are taken into account. We calculate IRR (internal rate of return) and static payback period of a specific distributed PV system in China's five cities located in different resource areas. In order to provide a realistic reference for investors, the historical data from real projects are used to calculate the generating capacity. The impacts of relevant policy variables such as subsidies, benchmark price, electricity price and tax on economic performance of distributed PV system are discussed. The results show that distributed PV system with high generation efficiency has produced good economic benefit in both two scenarios under China's current policies. The current policy instruments on distributed PV industry are efficient. At the end of the paper, policy recommendations are offered as references for the government. [ABSTRACT FROM AUTHOR]

• Optimal charging control for solar-powered electric bus networks was proposed. • MILP was adopted to tackle the complex and high-dimensional charging problem. • It can improve solar energy on-site consumption and reduce grid dependence. • It can satisfy the complex and various constraints. • It can assist in developing effective solar-powered electric bus networks. Developing solar-powered electric bus networks in high-density cities can greatly mitigate their increasing energy and environmental challenges such as carbon emission, street-level air pollution, and renewable penetration to the power grid. However, such solar-powered electric bus networks face a charging control issue that is caused by the severe and frequent mismatch between PV power generation and bus charging demand. Without proper consideration of this mismatch, renewable energy generation cannot be effectively utilized, and heavy grid dependence (i.e., energy exports/imports to/from power grids as solar power surplus/insufficient) will still exist. Meanwhile, the electric bus network charging issue is a complex constraint-based and high-dimensional control problem that requires holistically coordinating charging operations of a large number of electric buses (i.e., when and at which terminus to charge) while satisfying various constraints (e.g., bus schedule, bus battery capacity and charging power limits, limited charging stations in a terminus). Existing charging control methods of solar-powered electric vehicles may not be applicable for this problem. To address this knowledge gap, this study proposed a mixed-integer-linear-programming-based control strategy for solar-powered electric bus networks with improved renewable energy on-site consumption and reduced grid dependence. A case study of a bus network with reference to 10 real bus terminuses in Hong Kong was used to validate the performance of the proposed control in comparison to a rule-based one (i.e., first-come-first-served [FCFS]). The results showed that the proposed control can significantly improve the renewable energy on-site consumption ratio from 0.457 to 0.813, while the grid dependence indicator was reduced from 0.809 to 0.451. The in-depth analysis showed that the proposed control can realize both temporal and spatial demand shifting which mainly contributes to the performance improvements. The results also revealed to achieve the same performance of the proposed control, the FCFS control requires installing a large-sized battery storage system, i.e., 45-MWh. The proposed control can be used to facilitate the development of solar-powered electric bus networks in high-density cities, thereby alleviating associated carbon emissions and air pollution. [ABSTRACT FROM AUTHOR]

Distributed PV (DPV) has become the policy priority of renewable energy development in China since 2012 and ambitious planning for it has been formulated and updated. In 2013 a national unified subsidy policy was put into implementation. However, the actual progress is far below expectation. In this paper, the analytical framework of levelized cost of electricity (LCOE) is employed to estimate the generation cost of DPV in China. We find that under existing tariff and subsidy policies, with ideal conditions of most favorable financial arrangement and maximum annual operation hours, DPV projects located in regions with best solar resource or high commercial/industrial retail electricity prices are able to break even; but with practical conditions DPV projects are economically unfeasible at most cases. We further find that, difficulty in obtaining roof space, complicated grid integration procedure, barriers in obtaining bank loan, and unattractive and rigid subsidy policy, lead to high investment risks, which largely explains why DPV can't take off in China. A series of policy packages are proposed to address these issues. [ABSTRACT FROM AUTHOR]

This paper presents an innovative management strategy for distributed battery storages that greatly increases the capability of distribution networks to absorb and utilize photovoltaic (PV) generation. Optimal daily energy profiles for each storage unit are calculated using a Fourier series description based on one day ahead energy forecasts. Each battery charge/discharge profile is optimized to minimize a cost function that includes network and battery losses, battery cyclic costs and the network voltage profile. The optimization method combined an interior-point algorithm and pattern search algorithm. Simulations are carried out on a three-phase distribution system over a period of 24 h at 15 min interval with time varying loads. The adopted technique in this paper shows significant control abilities in peak shaving and load leveling. Results also indicate that proposed approach can enhance the performance of the grid by improving the voltage stability and reducing distribution losses thus providing the required security for consumers. Results also illustrate capacity and charging/discharging rates of batteries highly depend on the location of the controlled consumer battery and amount of controlled batteries. [ABSTRACT FROM AUTHOR]

Highlights: [•] Uncertainty in PV generation forecast is a drawback for grid integration. [•] Self-consumption of distributed PV reduces the effect of forecast uncertainty. [•] Active Demand Side Management and local storage increases self-consumption. [•] Experimental results and simulations are presented. [•] Error on electricity exchanged with the grid is reduced to 2%. [ABSTRACT FROM AUTHOR]

• This study proposes a voltage profile perception (VPP) method where the maximum/minimum voltage of each feeder in a DN can be perceived by utilising the information of certain nodes. • A cluster partition method which considers the voltage regulation capability of distributed PVs as well as the voltage amplitude sensitivity of both active and reactive power. • A hierarchical decentralised voltage control with a comprehensive distributed PV and traditional device control strategy based on the optimal network partition is proposed. The integration of large-scale distributed photovoltaics (PVs) in distribution networks (DNs) causes reverse power flow and the voltage violation problem. However, in some rural area, DNs do not have sufficient measuring information and communication ability to meet the challenge. In order to solve the voltage violation problem, this study proposes a voltage profile perception method and a voltage regulation analysis model as an alternative method to power flow calculations to guide the partition and voltage control of DNs. We then propose a novel hierarchical decentralised voltage control method strategy that combines cluster autonomous optimisation and cluster coordination optimisation in different time scales based on the DN partition. The optimal control is conducted for voltage regulation to minimise the amount of reactive power compensation and the active power curtailment under the DN operation constraints. The effectiveness and feasibility of the proposed method are demonstrated via simulation tests on a real 10.5 kV 34-node feeder in China. [ABSTRACT FROM AUTHOR]

• Aggregate PV power reduction of ~30–40% during voltage disturbance is observed. • Depth and duration of response is shown to be diverse across individual PV systems. • Data from 376 distributed PV systems during major voltage disturbances is analyzed. • Four data analysis techniques are demonstrated including geographical analysis. • Findings indicate that distributed PV may contribute to frequency management needs. As distributed photovoltaics (PV) levels increase around the world, it is becoming apparent that the aggregate behavior of many small-scale PV systems during major power system disturbances may pose a significant system security threat if unmanaged. Alternatively, appropriate coordination of these systems might greatly assist in managing such disturbances. A key issue is PV behavior under extreme voltage events. PV connection standards typically specify aspects of inverter voltage behavior. However unresolved questions remain regarding compliance, ambiguity and transition between versions of these standards. In addition, how major voltage disturbances manifest in the low voltage network is complex, and analysis of operational system data could be particularly useful for establishing the behavior of distributed PV in the field. Our study utilizes 30 s operational PV generation data from 376 sites during two major voltage disturbances in Australia. Australia has one of the highest penetrations of distributed PV worldwide, and as such provides a useful case study. Results show that an aggregate ~30–40% reduction in distributed PV generation occurred during these events, but individual inverter behavior varied markedly. To the authors' knowledge, this is the first time the aggregate response of distributed small-scale PV to voltage disturbances originating in the transmission system has been demonstrated. Four novel techniques for analyzing events are proposed. Results show a potential increase in system security service requirements as distributed PV penetrations grow. Our findings would seem to have major implications for development of composite load models used by power system operators and for contingency management. [ABSTRACT FROM AUTHOR]