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In Brazil, in the lasts five years there has been a significant growth of photovoltaic generation installed in the consumer side of me-ters, the so-called prosumers. However, most of these installations occur in an individual way, as self-consumption, with net-metering billing. The possibility of forming a community grouping several consumer units is little used. This paper analyzes the eco-nomic benefit obtained by prosumers acting individually and by prosumers grouped in a community when investing in photovolta-ic generation. A mixed integer linear programming model was used to select photovoltaic generation systems, considering the Brazilian net-metering billing, in order to minimize the annualized total cost to meet the demand of the prosumers. Tests were con-ducted for prosumers connected individually and in communities, for two tariff modalities, conventional and time of use. The results show that there is an increase in the economic benefit obtained by some of the individually connected prosumers when they install photovoltaic generation. However, when the option is to form a community the economic benefit can be 120% higher. [ABSTRACT FROM AUTHOR]

Summary: The fading characteristics of 60 Ah decommissioned electric vehicle battery modules were assessed employing capacity calibration, electrochemical impedance spectroscopy, and voltage measurement of parallel bricks inside modules. The correlation between capacity and internal resistance or voltage was analyzed. Then, 10 consistent retired modules were packed and configured in a photovoltaic (PV) power station to verify the practicability of their photovoltaic energy storage application. The results show that the capacity attenuation of most retired modules is not severe in a pack while minor modules with state of health (SOH) less than 80% bring about the retirement of the whole pack as a result of the buckets effect. There is no obvious correlation between capacities of retired battery modules and their lithium‐ion diffusion coefficients or charge transfer resistance or ohmic resistance, whose reliability is low as the consistency indexes of decommissioning battery modules. The maximum off load voltage difference ΔUmax at low state of charge (SOC) values has a good negative linear correlation with the capacity of retired modules, suggesting that the ΔUmax value at low SOC values can be considered as a characteristic index for fast classification of retired battery modules for large‐scale second‐life application. A PV power station equipped with retired battery energy storage system (RBESS) can maximize the photovoltaic self‐utilization rate. It is an important way to reutilization of retired battery that RBESSs are configured with distributed PV power stations. [ABSTRACT FROM AUTHOR]

In the last years, the manufacturing and installation costs of photovoltaic generators (PV) are gradually shrinking. This reduction in costs incentives the use of PV by the end user to satisfy its own demand and sell the surplus energy to the power distribution network. This paper evaluates the competitiveness to integrate small-scale PV in the city of Quito-Ecuador. These PV will be used to self-consumption for residential and commercial users affiliated to "Empresa Eléctrica Quito", which is the entity that manages the power requirements in Quito city. The levelized cost of electricity incurred by building and operating a PV is calculated and compared with the price used to purchase energy from the electrical distribution network. The concept of grid parity is analyzed by this comparison, including electricity tariffs and costs for the year 2018. OpenDSS software is used to estimate the energy supplied from PV in function of temperature and irradiation data gathered in Quito city. Finally, annual economic benefits obtained by the users are determined. Results show that there is not grid parity in 2018 yet, but the parity status could be reached by economic incentive schemes as Net Billing. [ABSTRACT FROM AUTHOR]

With the increasing penetration of distributed photovoltaic generation and energy storage systems in the demand side of the power system, new demand side model structures are necessary in order to better describe the dynamic performance of the power system. In this paper, a composite demand side model structure with load, distributed photovoltaic generation, and energy storage system together with a model parameter identification method are proposed to improve the traditional load model identification. The structure of the demand side model is proposed first and is further simplified so as to be identified at a high voltage level bus. The model parameter identifiability analysis is conducted based on the sensitivity method. The ambient signal data and disturbance data based model parameter identification method is proposed for the new demand side model structure using the differential evolution optimization method. The case study results for the WSCC 9 bus system show the effectiveness of the proposed model structure. Then, the case study results in a simplified 500-kV network of the Guangdong Power Grid show the effectiveness of the parameter identification method. [ABSTRACT FROM AUTHOR]

Recently, distributed generation using renewable energy sources such as photovoltaic (PV) generation has increased in power systems to solve environmental problems and resource exhaustion problems. However, conventional reliability evaluation methods of power systems cannot easily evaluate power systems with massive penetration of PV. The methods may not accurately evaluate overload exceeding system capacity, expansion of voltage phase difference between adjacent power systems, and voltage violation resulting from a sudden decrease in PV output due to weather conditions. Therefore, this paper proposes a new method to evaluate the supply reliability of power systems by three constraints, namely, capacity constraint, voltage phase difference constraint, and voltage magnitude difference constraint. [ABSTRACT FROM AUTHOR]

• DC bus transient voltage fluctuations are minimal with EO-BSMCC-based VSC control. • THDs in grid currents and voltages are reduced using EO-BSMCC based VSC control. • Outperforms other widely known advanced adaptive controls in multiple aspects. • Compensates local load's reactive power, unbalanced currents, and harmonics. • Performance confirmed from experimental results on developed prototype. This paper demonstrates the mitigation of current related power quality issues at the distribution end with a grid-tied PV system. The power quality problems at the distribution end result from the rapidly increasing non-linearity of the loads. The DC bus stability is ensured by an equilibrium optimized (EO) PI controller, which minimizes the DC bus voltage variations during dynamic conditions, i.e., irregular PV power generation due to insolation variation, grid voltage sag/swell, load, and grid voltage unbalancing. The EO-DC bus control delivers an accurate loss component of current that further enhances the operational capability of the controlled voltage source converter. The EO-DC bus stability is superior to various mete-heuristic optimization techniques, i.e., salp swarm optimization, particle swarm optimization, and genetic algorithm. The suggested block sparse maximum correntropy criteria (BSMCC) based estimation of load current component with l 1 , 0 norm regularized cost function offers improved filtering accuracy against nonlinear load current. The system control executes multiple functions, i.e., power factor correction, harmonics elimination, active and reactive power control, load balancing, and grid currents balancing at the point of common coupling. The BSMCC control outperforms its counterparts, i.e., least mean square, least mean fourth, maximum correntropy criteria, etc. The EO-BSMCC control offers better extraction of fundamental load current components and harmonics elimination during steady-state and dynamic conditions. The EO-BSMCC controlled grid integrated PV system performs satisfactorily as per IEEE 1547 standard. [ABSTRACT FROM AUTHOR]

The expansion of renewable energy generation in recent years has contributed to the decarbonization and diversification of energy grids worldwide. The use of hybrid power plants is a way to optimize renewable resources and energy storage systems can mitigate the intermittent availability of these energy sources. Thus, the current study aims to evaluate the feasibility of using solar photovoltaic energy to complement hydroelectric generation or even recover reservoir levels in hydroelectric power plants (HPP). To start, data from 62 HPPs in Brazil were used. The installed solar power potential was defined for each HPP in order to improve utilization of the electric substation. Economic analyses were conducted for all three of HPPs considering the energy reductions due to the excess energy loss because of the overloading of the substation's installed power. Then, one of the HPPs was chosen to install a PHS powered by the surplus solar energy. Feasibility calculations were conducted using parameters such as Net Present Value (NPV) and Levelized Cost of Storage (LCOS). The results demonstrated greater feasibility for hybrid powerplants in scenarios with low overloading of the substation and lower production rates of excess energy. The application of excess energy to recover dam levels proved to be unfeasible. [ABSTRACT FROM AUTHOR]

Three-phase electrical systems are subject to current imbalance, caused by the presence of single-phase loads with different powers. In addition, the use of photovoltaic solar energy from single-phase inverters increases this problem, because the inverters inject currents of different values, which depend on the generation capacity at a given location. To mitigate the problems caused by current imbalance, solutions that measure and compensate for the current in the neutral conductor are proposed. However, through an adequate control method, the current balance of the distribution network could be achieved by the photovoltaic inverters themselves. Thus, this work proposes to use positively the idle capacity of three-phase photovoltaic inverters to partially compensate for the current imbalances in the low voltage network but in a decentralized way. Therefore, a control method is developed, based on instantaneous symmetric components theory and on the estimation of orthogonal signals using a third-order generalized integrator (TOGI). In turn, through a laboratory prototype, experimental results are presented that demonstrate the feasibility of implementation and the effectiveness of the proposed control technique on current balancing. • Current balancing in distribution grids using photovoltaic inverters. • Control based on the decomposition of instantaneous power into symmetric components. • Feasibility of the control strategy demonstrated through experimental results. [ABSTRACT FROM AUTHOR]

Photovoltaic systems can strengthen the energy matrix aiming at energy sustainability, however, their intermittence, the availability time frame and seasonality effects are complicating aspects for the operation of these systems. To mitigate such problems, a possible measure is the operation of hybrid systems (HS) associated with storage systems to meet the energy demand. This study presents real operational scenarios for the management of a hybrid mini-grid installed in the Amazon region in Brazil, capable of managing energy supply and demand, changing the generation curve, reducing fossil fuel consumption and energy costs, in addition to providing flexibility and operational safety to the electrical operating under on-grid or off-grid conditions. Through technical and economic analyses, the objective of this study is to show that hybrid systems can be implemented in small and medium consumers, in addition to generating a new market option for utilities. This research evaluates the operation of HS concurrently with the electrical grid and the results show that the system meets the technical requirements, in addition to bringing financial and ecological benefits. This information can support the decisions of consumers, utilities and energy operators for the development of the national market for on-grid and off-grid HS.

This paper presents the implementation of a custom-made virtual power plant model in OpenDSS. The goal is to develop a model adequate for time-driven power flow calculations in distribution systems. The virtual power plant is modeled as the aggregation of renewable generation and energy storage connected to the distribution system through an inverter. The implemented operation mode allows the virtual power plant to act as a single dispatchable generation unit. The case studies presented in the paper demonstrate that the model behaves according to the specified control algorithm and show how it can be incorporated into the solution scheme of a general parallel genetic algorithm in order to obtain the optimal day-ahead dispatch. Simulation results exhibit a clear benefit from the deployment of a virtual power plant when compared to distributed generation based only on renewable intermittent generation.

DC microgrids (DC-MGs) are capable of integrating and coordinating distributed energy resources into power systems, along with providing services to the wider system, e.g. balancing, frequency support, demand response and so on. This study investigates the capability of DC-MGs providing grid frequency support, for the GB enhanced frequency response service. In this study, photovoltaic generation, energy storage, and load form the DC-MGs. The control strategy is a decentralised scheme, based on conventional droop control for active power sharing and grid frequency support. Droop control is also used within the DC-MG for power-sharing amongst generation and load. Scenarios are conducted to evaluate the effectiveness of the control strategy and verified by MATLAB/Simulink simulations.

with the onboard diesel generators and energy storage system to meet the propulsion and service load, the all-electric ship (AES) can be viewed as a ‘mobile microgrid’. Nowadays, photovoltaic (PV) generation is gradually integrated into the AES for a ‘greener’ voyage. To fully utilise the PV energy, this paper proposes a joint generation and voyage scheduling method for the PV integrated AES. The overall model is formulated as a bi-level programming problem and solved by column-and-constraint generation method. The simulation results manifest that, the integration of PV into AES leads to reductions on both the fuel consumption and CO2 emission.

This work analyses the impact of photovoltaic generation on voltage stability margin in an islanded microgrid. An indicator of voltage collapse proximity, based on the maximum deliverable power, is used to study the contribution of photovoltaic generation to the voltage stability margin. In this context, the well-known power–voltage curves, also known as ‘nose’ curves, are developed, taking into account different levels of photovoltaic penetration. Furthermore, the effect of the power factor at the photovoltaic generators as well as the influence of the adopted model for such generators are also investigated. The results have shown that the photovoltaic generation can significantly affect the voltage stability margin.

In the background of the energy Internet, the number of data centres is increasing, aiming at the shortcomings of power supply and reliability in power supply system of traditional data centre and the development trend of green data centres. This article proposes an AC & DC hybrid power supply system with high-proportion renewable energy. The system includes photovoltaic generation, wind power generation, photothermal power generation, thermal utilisation system, power storage system, and different types of loads. Therein, a multi-port power electronic transformer is used to realise AC & DC multi-level mixing system with high proportion of variety of distributed renewable energy. Thereafter, the power supply, power grid, and the load can efficiently complement each other by using the integrated energy storage system such as electricity storage and heat storage. In detail, the rationality and functionality of the AC & DC hybrid power system are analysed through the system simulation and power supply reliability calculation. Moreover, the results show that the proposed hybrid power supply can effectively improve the impact of high-proportion renewable energy access to the grid and provide a new design scheme for the green data centre.

This paper deals with the optimal siting and sizing problem of photovoltaic (PV) generators in electrical distribution networks considering daily load and generation profiles. It proposes the discrete-continuous version of the vortex search algorithm (DCVSA) to locate and size the PV sources where the discrete part of the codification defines the nodes. Renewable generators are installed in these nodes, and the continuous section determines their optimal sizes. In addition, through the successive approximation power flow method, the objective function of the optimization model is obtained. This objective function is related to the minimization of the daily energy losses. This method allows determining the power losses in each period for each renewable generation input provided by the DCVSA (i.e., location and sizing of the PV sources). Numerical validations in the IEEE 33- and IEEE 69-bus systems demonstrate that: (i) the proposed DCVSA finds the optimal global solution for both test feeders when the location and size of the PV generators are explored, considering the peak load scenario. (ii) In the case of the daily operative scenario, the total reduction of energy losses for both test feeders are 23.3643% and 24.3863%, respectively; and (iii) the DCVSA presents a better numerical performance regarding the objective function value when compared with the BONMIN solver in the GAMS software, which demonstrates the effectiveness and robustness of the proposed master-slave optimization algorithm.

The problem of the optimal placement and sizing of photovoltaic power plants in electrical power systems from high- to medium-voltage levels is addressed in this research from the point of view of the exact mathematical optimization. To represent this problem, a mixed-integer nonlinear programming model considering the daily demand and solar radiation curves was developed. The main advantage of the proposed optimization model corresponds to the usage of the reactive power capabilities of the power electronic converter that interfaces the photovoltaic sources with the power systems, which can work with lagging or leading power factors. To model the dynamic reactive power compensation, the η-coefficient was used as a function of the nominal apparent power converter transference rate. The General Algebraic Modeling System software with the BONMIN optimization package was used as a computational tool to solve the proposed optimization model. Two simulation cases composed of 14 and 27 nodes in transmission and distribution levels were considered to validate the proposed optimization model, taking into account the possibility of installing from one to four photovoltaic sources in each system. The results show that energy losses are reduced between 13% and 56% as photovoltaic generators are added with direct effects on the voltage profile improvement.

The proliferation of renewable energy resources (RES), especially solar photovoltaic (PV) generation resources, causes overvoltage and line overloading in distribution networks. This study proposes a two-level volt–var control method based on multiple timescales. The on-load tap changer (OLTC) operates on an hourly timescale, to regulate the voltage on the secondary winding. In the 15-minutes timescale, PV-connected smart inverters and static var compensators (SVCs) are obliged to compensate the reactive power for the voltage control at the point of common coupling. In the multi-timescale voltage control framework, this study proposes a new multi-sectional volt–var curve (MSVVC) of a PV inverter. The objective of the MSVVC is to minimize the energy loss in the network, improve the voltage profile, and obtain the operational margin of other reactive power compensation devices. In the process of determining the optimal parameters of the MSVVC, stochastic modeling-based load flow analysis is utilized to consider the intermittency and uncertainty of RES generation. The effectiveness of the proposed method is verified on the IEEE 33-bus system in comparison with the conventional volt–var curve cases.

The efficient integration of photovoltaic (PV) production in energy systems is conditioned by the capacity to anticipate its variability, that is, the capacity to provide accurate forecasts. From the classical forecasting methods in the state of the art dealing with a single power plant, the focus has moved in recent years to spatio-temporal approaches, where geographically dispersed data are used as input to improve forecasts of a site for the horizons up to 6 h ahead. These spatio-temporal approaches provide different performances according to the data sources available but the question of the impact of each source on the actual forecasting performance is still not evaluated. In this paper, we propose a flexible spatio-temporal model to generate PV production forecasts for horizons up to 6 h ahead and we use this model to evaluate the effect of different spatial and temporal data sources on the accuracy of the forecasts. The sources considered are measurements from neighboring PV plants, local meteorological stations, Numerical Weather Predictions, and satellite images. The evaluation of the performance is carried out using a real-world test case featuring a high number of 136 PV plants. The forecasting error has been evaluated for each data source using the Mean Absolute Error and Root Mean Square Error. The results show that neighboring PV plants help to achieve around 10% reduction in forecasting error for the first three hours, followed by satellite images which help to gain an additional 3% all over the horizons up to 6 h ahead. The NWP data show no improvement for horizons up to 6 h but is essential for greater horizons.

The optimum sizing of photovoltaic technologies depends on certain variables such as the daily energy consumption of buildings and available solar potential of the location. The purpose of this paper is to define the optimum photovoltaic panel area with no battery system to supply the daytime electricity usage of a Vocational School in Sanlıurfa, Turkey. First, the maximum photovoltaic panel areas are found at the 100% self-consumption for the Mono-Si, Multi-Si, and CdTe photovoltaic technologies. Besides, for defining optimum installation powers, an economic analysis has been carried out. The seasonal performances of economical optimum capacities are investigated under the feed-in tariff scenario. At 100% self-consumption, the maximum photovoltaic panel areas are found 130 m², 160 m², and 170 m² for Mono-Si, Multi-Si and CdTe respectively. The results show that the installation of Mono-Si (115 m²), Multi-Si (150 m²), and CdTe (210 m²) photovoltaic systems at 1.65, 1.75, and 2.3 times as the daily peak electricity consumption, is the most optimal selection according to economic indicators. [ABSTRACT FROM AUTHOR]

• New methodology to address PV distributed generation impacts on LV networks. • PV technical assessment based on economic and stochastic approach. • A comprehensive distribution system modeling, including real data measurement. • Comparison between the proposed methodology and the so-called traditional one. • Identification of the most critical nodes regarding technical impacts. This work investigates the influence of the local photovoltaic (PV) market in the analysis of the photovoltaic distributed generation (PVDG) impacts on LV networks. The new methodology proposed by this work indicates: the PV penetration based on different scenarios and technology diffusion evaluation; the probability of technical violation occurrence due to PVDG connection; and the location of the critical points over the distribution system, aiding in the efficient management of investment in network reinforcements. The novelty of this methodology refers to the inclusion of an economic analysis within the stochastic approach, considering the influence of local market in the technical assessment. Furthermore, this methodology is applied to a real distribution feeder in Brazil. Firstly, an economic analysis of the consumers of the studied circuit is carried out to estimate the PVDG penetration. Next, Monte Carlo Simulations are performed through OpenDSS considering network parameters, real local irradiance and load curves measured by advanced metering infrastructure. Therefore, it is possible to consider the uncertainties associated with the connection of PV systems and the variation of consumer load. One of the main results of this study is that the proposed methodology notices less technical violations than the methodology that is traditionally used in the literature and does not consider the influence of the local market. In addition, technical violations tend to occur in different transformers for each methodology. This happens because the traditional methodology considers that every consumer has the same probability of installing PVDG, including those classified as not economically able according to the analysis proposed in this article. [ABSTRACT FROM AUTHOR]

Global warming, increase in environmental pollution, and high cost of electrical power generation using fossil fuels are considered the most important reasons for the application of renewable energy power plants (REPPs) around the world. In recent years, a new generation of REPPs called hybrid renewable energy power plants (HREPPs) has been implemented in order to have higher efficiency and reliability than conventional REPPs such as wind power plants and photovoltaic power plants. The HREPPs include two or more renewable energy generation units such as wind turbine generation units, and PV generation units. In case of high penetration of these types of power plants, the most common tasks of synchronous generators should be supported by them. One of these tasks is the ability to reduce the low-frequency oscillation (LFO) risk through power oscillation damper such as the power system stabilizers of synchronous generators. In this paper, a novel method is proposed for LFO damping by HREPPs, which is based on the design of an optimal power oscillation damper (OPOD) implemented in the generic HREPP controller model. The structure of the proposed OPOD is a 2nd-order single-input lead-lag controller, and its performance is investigated in a modified two-area test system. The simulation results show the proper performance of the HREPP for LFO damping using the proposed OPOD in the various loading levels and different short circuit ratio values. [ABSTRACT FROM AUTHOR]

Renewable energies (REs) such as photovoltaic generation (PV) have been gaining attention in distribution systems. Recently, houses with PV and battery systems, as well as electric vehicles (EV) are expected to contribute to not only the suppression of global warming but also reducing electricity bill on the consumer side. However, there are numerous challenges with the introduction of REs at the demand side such as the actual output of REs often deviating from the forecasted output, which causes fluctuation of the power flow and this is challenging for the distribution or transmission system operator. For this challenge, it is expected that smart grid technology using controllable loads such as a fixed battery or EV battery, can suppress fluctuation of power flow. This paper presents a decision method of optimal scheduling of controllable loads to suppress the fluctuation of power flow by PV output in the smart home. An optimization method to cope with uncertainties such as variability of PV power and effective forecasting methods are considered in the proposed scheme. In order to decrease the expected operational cost and to validate the robustness for the uncertainty's optimization approach, statistical analysis is executed for the optimal scheduling scheme. From the optimization results, the proposed methodology suppressed the fluctuation of power flow in the smart home and also minimized the consumer operational cost. [ABSTRACT FROM AUTHOR]

Because of the significant changes in environmental policies and electric power deregulation in the last decade, a lot of photovoltaic generations (PV) have been and will be installed into the power system in Japan and the ratio of PVs to other synchronous generators will be increased. As a countermeasure against the decrease in the rotational inertia in the whole power system, a virtual synchronous generator (VSG) model control of the PV has so far been proposed. However, the system stabilization effect of the VSG in large‐scale power systems has been unclear. In this paper, a virtual step‐out blocking method of VSG for improving the transient stability is proposed. In addition, the necessity of governor control of VSG in a large‐scale power system is discussed. Finally, the rated kw and kwh capacities of the battery required for realizing the VSG‐model control are evaluated. [ABSTRACT FROM AUTHOR]

Owing to the depletion of oil reserves and the low efficiency of traditional deep-water semi-submersible drilling platforms, the application of photovoltaic generation and energy storage systems in marine power systems has been increasingly attracting attention. However, the intermittent and uncertain nature of solar energy brings crucial challenges in maintaining stable and sustainable operations. Furthermore, unlike land-based power systems, the deep-water semi-submersible drilling platform depends on a dynamic positioning system to be fixed in an area of deep water for producing oil, but irregular and stochastic waves make the outputs of a dynamic positioning system uncertain, increasing the difficulty and complexity of energy management. This paper develops a novel hybrid day-ahead probabilistic scheduling method to reduce the total fuel cost of the whole system and improve the energy efficiency; the method combines Taguchi's orthogonal algorithm with particle swarm optimization and a probabilistic load flow method. A detailed model of the deep-water semi-submersible drilling platform is established to validate the proposed method, which is compared with various classical methods. With the help of the proposed method, the total operation cost and greenhouse gas emissions are reduced from $7562.52 to $7333.68, and from 18.95 tons to 16.81 tons, respectively. Furthermore, compared to the two-point estimation method, the experimental times drops by half, which minimizes the computational burden. The simulation results clearly demonstrate the necessity for day-ahead energy scheduling, and the advantages of the proposed method. • A photovoltaic/diesel/battery power system in a DSDP is established. • A novel hybrid day-ahead scheduling method is proposed for a DSDP. • Cumulative probability function -based Taguchi method is developed for discretization. [ABSTRACT FROM AUTHOR]

Large quantum of photovoltaic (PV) generation into the grid would reduce system's primary frequency response (PFR) capability. Adequate PFR is critical to provide rapid frequency stability after contingencies such as large generation outage. PFR estimation and its scheduling within acceptable operational time frames is a challenging task for system operator. Uncertain PV generation makes this problem critical. Existing models for PV uncertainty characterisation with stochastic scheduling are computationally demanding. This study proposes a computationally fast modified interval scheduling approach for operation and PFR cost minimisation. Uncertainty is modelled through interval forecasting, while hourly ramp needs are based on net load scenario. The proposed model is compared with stochastic scheduling approach for PFR performance, overall cost performance, computational time and PV curtailment. Numerical results show that the proposed model drastically reduces simulation time for similar cost performance. [ABSTRACT FROM AUTHOR]

Energy storage and demand response (DR) resources, in combination with intermittent renewable generation, are expected to provide domestic customers with the ability to reducing their electricity consumption. This study highlights the role that an intelligent battery control, in combination with solar generation, could play to increase renewable uptake while reducing customers' electricity bills without intruding on people's daily life. The optimal performance of a home energy management system (HEMS) is investigated through a range of interventions, leading to different levels of customer weariness and consumption patterns. Thus, the DR is applied with efficient and specific control of domestic appliances through load shifting and curtailment. Regarding the uncertainty associated with the photovoltaic generation, a chance‐constrained (CC) optimal scheduling is considered subject to the operation constraints from each power component in the HEMS. By applying distributionally robust optimisation, the ambiguity set is accurately built for this distributionally robust CC (DRCC) problem without the need for any probability distribution associated with uncertainty. Based on the greatly altered consumption profiles in this study, the proposed DRCC‐HEMS is proven to be optimally effective and computationally efficient while considering uncertainty. [ABSTRACT FROM AUTHOR]

The uncoordinated charging of several plug-in electric vehicles in a parking garage can potentially overload distribution transformer reducing its lifespan. Attempting to mitigate this issue, this paper proposes a smart charging method to minimize electricity consumption costs and avoid transformer overloading by considering a charging station integrated with photovoltaic generation and battery energy storage system. The optimal coordination among all these elements is investigated assessing transformer hottest-spot temperature and loss-of-life, considering a case study with time-of-use rate and meteorological data from Texas, USA. In addition, an economic analysis is developed to evaluate the viability of the project, with a sensitivity study considering different charging fees and variation in the daily number of vehicles parked in the garage. The results show the proposed approach is feasible, yields tangible financial benefits and can preserve distribution transformer life. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) power generation is characterized by significant variability. Accurate PV forecasts are a prerequisite to securely and economically operating electricity networks, especially in the case of large-scale penetration. In this paper, we propose a probabilistic spatio-temporal model for the PV power production that exploits production information from neighboring plants. The model provides the complete future probability density function of PV production for very short-term horizons (0–6 h). The method is based on quantile regression and a $L_1$ penalization technique for automatic selection of the input variables. The proposed modeling chain is simple, making the model fast and scalable to direct on-line application. The performance of the proposed approach is evaluated using a real-world test case, with a high number of geographically distributed PV installations and by comparison with state-of-the-art probabilistic methods. [ABSTRACT FROM AUTHOR]

In the background of the energy Internet, the number of data centres is increasing, aiming at the shortcomings of power supply and reliability in power supply system of traditional data centre and the development trend of green data centres. This article proposes an AC & DC hybrid power supply system with high-proportion renewable energy. The system includes photovoltaic generation, wind power generation, photothermal power generation, thermal utilisation system, power storage system, and different types of loads. Therein, a multi-port power electronic transformer is used to realise AC & DC multi-level mixing system with high proportion of variety of distributed renewable energy. Thereafter, the power supply, power grid, and the load can efficiently complement each other by using the integrated energy storage system such as electricity storage and heat storage. In detail, the rationality and functionality of the AC & DC hybrid power system are analysed through the system simulation and power supply reliability calculation. Moreover, the results show that the proposed hybrid power supply can effectively improve the impact of high-proportion renewable energy access to the grid and provide a new design scheme for the green data centre. [ABSTRACT FROM AUTHOR]

The accessing of distributed generation resources to distribution network leads to a multi power grid structure. The direction of power flow changes with it. The photovoltaic (PV) generation contains a large number of power electronic devices and control links, which causes that the output responses and fault characteristics are significantly different from the synchronous machine. In consideration of the topological structure of the distributed distribution network, this paper analyses the differences of transient characteristics of AC distribution line with PV power supply between internal and external faults. Then, a new principle for constructing directional element using transfer and consumption characteristics of high-frequency transient energy is proposed. This directional element only uses high-frequency transient fault voltage and current in early stage, which can reliably distinguish the fault direction. What's more, the existence of transition resistance will be conducive to the judgement. Finally, corresponding simulation cases were carried out to verify the feasibility and superiority of the proposed directional element. [ABSTRACT FROM AUTHOR]

Renewable power generation combined with energy storage (ES) is expected to bring enormous economical and environmental benefits to the future smart grid. However, the ES management in smart grid is facing significant technical challenges due to the volatile nature of renewable energy sources and the buffering effect of ES units. The challenges are further complicated by the increasing size and complexity of the system, as well as the consideration of random usage patterns of electrical appliances by customers. To address these challenges, this study proposes a parallel decomposition method for large‐scale stochastic programming in a distribution system with renewable energy sources and ES units. By leveraging nested decomposition, the problem can be converted into independent sub‐problems with a series of time periods. In addition, the reformulated problem is fully parallel for speed up in execution. The performance of the proposed method is evaluated based on the IEEE 4‐bus and 33‐bus test distribution systems with real photovoltaic generation and electrical appliance usage data. The case study demonstrates that the proposed scheme can substantially reduce the system operation cost, with low computational complexity. [ABSTRACT FROM AUTHOR]

With the rapid development of high-speed railway, EMU has become an important research hotspot. How to improve the stability and reliability of EMU power supply, while reducing energy consumption, protecting the environment, become the future direction of development. Therefore, in view of the power failure of the contact network, this paper proposes the idea of installing solar panels on the roof of the EMU and using photovoltaic power to supply power to important auxiliary equipment. Taking China Railway High-speed 2 (CRH2) EMU as an example, according to the characteristics of roof and auxiliary power supply system, the feasibility of roof photovoltaic generation is analysed. At the same time, the scheme and strategy of the grid-connected power supply with deadbeat control under normal conditions and the droop control of the island under power supply failure are proposed. Matlab/Simulink software is used to simulate the photovoltaic generation system of two kinds of control strategy and the transition time. Finally, by comparing the photovoltaic system and the traditional power supply plan, the many advantages of EMU to introduce the photovoltaic generation system are analysed, and gets the conclusion that it is of great significance in practical application. [ABSTRACT FROM AUTHOR]

Although output of individual RE (Renewable Energy) such as PV (Photovoltaic Generation) severely varies, total output of many REs locate with geographical diversity is considerably smoothed out. The phenomenon is well known and is called as (mutual) smoothing effect. To quantitatively and mathematically express it, a theory named "Transfer Hypothesis" using "Transfer Swing Period Tx" as an important parameter is presented. Since the theory regards the effect as a kind of low pass filter, the theory can be applied to not only spectrum on frequency axis but also time sequential data. However, whole view of factors that affect Tx is not made clear yet. Therefore, it is questionable that once identified Tx in the studied area can be always adequate for practical use. The paper verifies the adequacy. Seasonal factors such as month and week, impact by number of sites in the studied area, and geographical factors such as distance between neighboring sites and studied area's size are examined. It has been demonstrated that Tx of two sites strongly depends on their distance, that number of sites does not affect Tx, and that Tx of the studied area is equal to that of two sites separated a distance 1/3 the length of the studied area. Therefore, it has been found that long time measurement on many sites is not necessary to identify Tx. [ABSTRACT FROM AUTHOR]

This paper proposes a novel power smoothing control method for a photovoltaic generation (PV) system using a water electrolyzer (ELY). This method realizes that the long‐period components of the PV power fluctuation are supplied to the power grid and the short‐period components of the PV power fluctuation are supplied to the ELY. The power supplied to the ELY is converted to hydrogen for fuel cell vehicles. The results of the power smoothing control method are evaluated in terms of the power in the load frequency control (LFC) band and the ability of generating hydrogen. Furthermore, filtering characteristics of the proposed method are clarified. As the result, the proposed method has reduced the power in LFC band by 83.7% compared to the PV power without the power smoothing control. The filter characteristics of the proposed method have shown that fluctuating components with periods less than 1000 seconds, in which the step voltage regulator does not perform, can be sufficiently eliminated from the PV power fluctuation components. When applying the proposed method for a PV system rated at 800 kW, the ability of generating hydrogen was about 2.30% of the hydrogen required for one hydrogen station. [ABSTRACT FROM AUTHOR]

Distributed generators including photovoltaic (PV) panels have been integrated dramatically in active distribution networks (ADNs). Due to the strong volatility and uncertainty, the high penetration of PV generation immensely exacerbates the conditions of voltage violation in ADNs. However, the emerging flexible interconnection technology based on soft open points (SOPs) provides increased controllability and flexibility to the system operation. For fully exploiting the regulation ability of SOPs to address the problems caused by PV, this paper proposes a robust optimization method to achieve the robust optimal operation of SOPs in ADNs. A two-stage adjustable robust optimization model is built to tackle the uncertainties of PV outputs, in which robust operation strategies of SOPs are generated to eliminate the voltage violations and reduce the power losses of ADNs. A column-and-constraint generation algorithm is developed to solve the proposed robust optimization model, which are formulated as second-order cone program to facilitate the accuracy and computation efficiency. Case studies on the modified IEEE 33-node system and comparisons with the deterministic optimization approach are conducted to verify the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]