Distribution Network Capacity Research Articles

Open Capacity Enhancement Model of Medium Voltage Distribution Network With Mobile Energy Storage System

In order to meet the demand of prosumer for power quality and new load in distribution network, an open capacity expansion model of distribution network with mobile energy storage system (MESS) is proposed in this paper. The model gives priority to the problem of voltage violation of prosumer group on feeders. Combined with the mobile energy storage path model, the open capacity of distribution network is calculated. Firstly, the actual distribution network geographic information and traffic routes are combined to establish the distribution network model based on mesh generation. Secondly, the traffic route model of the mobile energy storage system is established on the distribution network model based on mesh generation. Then, the optimal power flow of distribution network is calculated with the optimal network loss, and the mobile energy storage system is scheduled according to the situation of voltage violation. And the specific vehicle model and its scheduling are determined, which can better deal with the problem of distributed energy consumption and make prosumer operate safely and economically. Finally, according to the proposed N-1 security check constraint of distribution network with mobile energy storage system, the maximum open capacity of distribution network is calculated after the voltage regulation is completed. The example shows the practicability and correctness of the model in this paper. This paper formulates a mobile energy storage operation strategy to improve the open capacity of distribution network. The strategy not only fully meets users' needs, but also better guides the operation of power grid. It is conducive to releasing more potential power supply space of distribution network and improving asset utilization.

Distribution network capacity allocation for TSO flexibility services

Distribution network capacity allocation for TSO flexibility services

A review on voltage control for distribution systems with large-scale distributed photovoltaic power integration

In order to solve the problems of voltage wide-range fluctuations and over-limitation after large-scale distributed photovoltaic (DPV) integrated into distribution networks, this paper conducts a comprehensive and detailed analysis of voltage control strategy by summarizing existing voltage control technology and experience at home and abroad. The technical points and a comprehensive comparison from the perspectives of active power curtailment (APC), reactive power control (RPC) and active-reactive power coordination control (A/RC) are made. Through comparative analysis, it is found that adopting active-reactive power coordination control is a key measure to effectively improve voltage quality and increase the PV hosting capacity of distribution networks. The optimization of the control strategy can effectively improve the friendliness of large-scale PV system integration. The method and control strategy can provide a theoretical basis and practical reference for voltage management of distribution networks with high penetration PV integration.

A reliability evaluation method for radial multi-microgrid systems considering distribution network transmission capacity

The multi-microgrid (MMG) system is studied as a rudiment of the smart grid, and the radial MMG system is regarded as the comprehensive and typical one. The reliability evaluation of MMG systems are widely discussed to ensure its reliable and steady operation. The power balance between supply and demand is the core criterion for the reliability evaluation of MMG systems, which will be broken by unexpected events or inherent limits, such as the failure of equipment and the insufficient transmission capacity of distribution network (DN). In existing research, few have established a reliability model considering partial failure and imperfect repair of the equipment, and the DN transmission capacity usually is ignored. In this study, we abstract the radial MMG system as a performance-sharing system and present a Bayesian-network-based (BN-based) unified modeling method for performance and reliability to solve the deficiencies in existing research. First, the operation of radial MMG systems is analyzed to establish an abstract model to simplify the problem. Afterwards, the executive program of the BN-based reliability evaluation method is given. Further, the system modeling and the BN parameter modeling are introduced. Finally, a radial MMG system including 9 microgrids (MGs) is studied as a case, the variation of the system reliability index in grid-connected and island modes is analyzed. The results show that the method supports the reliability evaluation and analysis of radial MMG systems considering unexpected events and inherent limits.

A Study for Integrated Measures for Installation of Photovoltaics by Stochastic Analysis of Hosting Capacity in Distribution Networks

A Study for Integrated Measures for Installation of Photovoltaics by Stochastic Analysis of Hosting Capacity in Distribution Networks

Multi-objective Optimization of Accommodation Capacity for Distributed Generation Based on Mixed Strategy Nash Equilibrium, Considering Distribution Network Flexibility

The increasing penetration of distributed generation (DG) brings about great fluctuation and uncertainty in distribution networks. In order to improve the ability of distribution networks to cope with disturbances caused by uncertainties and to evaluate the maximum accommodation capacity of DG, a multi-objective programming method for evaluation of the accommodation capacity of distribution networks for DG is proposed, considering the flexibility of distribution networks in this paper. Firstly, a multi-objective optimization model for determining the maximum accommodation of DG by considering the flexibility of distribution networks is constructed, aiming at maximizing the daily energy consumption, minimizing the voltage amplitude deviation, and maximizing the line capacity margin. Secondly, the comprehensive learning particle swarm optimization (CLPSO) algorithm is used to solve the multi-objective optimization model. Then, the mixed strategy Nash equilibrium is introduced to obtain the frontier solution with the optimal joint equilibrium value in the Pareto solution set. Finally, the effectiveness of the proposed method is demonstrated with an actual distribution network in China. The simulation results show that the proposed planning method can effectively find the Pareto optimal solution set by considering multiple objectives, and can obtain the optimal equilibrium solution for DG accommodation capacity and distribution network flexibility.

Probabilistic Evaluation and Improvement Measures of Power Supply Capability Considering Massive EV Integration

Massive electric vehicle (EV) integration has been an inevitable trend for future power distribution networks. However, the spatial-temporal randomness of EV charging behavior may cause insufficiency of power supply capability. This paper simulates the charging loads with massive EV integration, proposes a probabilistic evaluation index to evaluate the probability of insufficient power supply capability, and gives improvement measures for power distribution networks without hardware upgrading. First, the spatial-temporal distribution of EV charging loads is simulated via Monte Carlo method, which particularly divides EVs into three categories, private cars, buses, and taxis. Then, aggregated with conventional loads, total supply capacity of a power distribution network can be calculated on different time periods. Second, for the uncertainty of EV charging loads both in time and space, a probabilistic evaluation index is addressed to evaluate the probability of power supply capability insufficiency. After that, several improvement measures of the charging strategy are given to relieve the insufficiency of power supply capability. Finally, taking the simplified distribution network of a typical power supply mode in China’s Fujian province as an example, three scenarios with different vehicle quantities and parameters are designed, and the effectiveness of the evaluation index and improvement measures proposed are identified. The results can provide evidences for constraining EV charging behaviors with massive integration.

Integrated Planning for Distribution Automation and Network Capacity Expansion

Due to the large amount of resources needed for implementing distribution automation systems (DASs), distribution companies (DISCOs) should develop long term plans for this project. Similarly, DISCOs have network capacity expansion (NCX) plans which specify the scheme of constructing the feeders and substations. Since considering DAS may lead to more efficient NCX plans, the planner should revise the NCX plan through the DAS planning. On the other hand, for DAS planning it is necessary to consider a NCX plan as a platform to determine the time and location for installation of automation equipment. Therefore the planner should simultaneously work on two plans, each of them affects the other. To facilitate this complicated planning procedure, this paper presents a novel method for integrated planning for NCX and DAS implementation. The proposed method develops a comprehensive plan in which the optimal scheme and schedule for constructing the lines and substations and installation of automation equipment is specified. To reduce the huge computational burden, an optimization method based on genetic algorithm is proposed. The proposed method is evaluated on an illustrative test network and the obtained results are presented and discussed.

Optimization Strategy for Improving Power Supply Capacity in Distribution Networks with Electric Vehicle Integration

In order to alleviate the heavy air pollution problem in China in recent years, power energy alternative loads, such as electric vehicles, are widely integrated into distribution networks, which has a significant impact on power supply capability of distribution networks. In this paper, considering the randomness of electric vehicles, probabilistic multiple scenarios generation method is proposed based on Latin hypercube sampling method, Cholesky decomposition and synchronous back-off reduction, realizing the quick scenario generation with the balance of scenario number and precision. Based on probabilistic multi-scene, taking the power supply ability of distribution network as the main objective, a robust operation optimization model of distribution network containing electric vehicles is established in order to optimize the opening and closing status of the switches. Ant colony algorithm based on the Pareto optimal is adopted to solve the model. A modified IEEE 33 node system is used to verify the effectiveness of the model and algorithm, and simulation results show that the proposed method can effectively promote the power supply ability of distribution networks, and can greatly improve the computational efficiency of the model in the case that lots of uncertain parameters exist due to large-scale integration of electric vehicles.

Probabilistic risk-based management of distribution transformers by dynamic transformer rating

Electrical distribution networks are often inadequate to comply with the increasing load demand and to enable new installation of distributed energy resources. This inadequacy may result in upgrading existing transformers of in disconnecting the entire load during demand peaks, and into wasting a portion of the total renewable energy produced during favorable weather conditions. Increasing the capacity of electrical distribution network components is therefore mandatory in order to avoid these negative circumstances; however replacing lines and transformers is costly, and often the benefits are not worth the investments. Fortunately, the capacity of distribution networks can be unlocked by managing the electrical components by their dynamic ratings, allowing operating them even beyond their rated ampacity for a limited interval of time.This paper proposes a new risk-based procedure to manage distribution transformers by their dynamic rating. Probabilistic forecasts of loads and ambient temperatures are the inputs of the procedure, which are obtained in this paper from quantile regression forests. The procedure quantifies, in a probabilistic framework, the insulation thermal ageing due to the transformer (over)load in terms of the cost sustained for rewinding the transformer. The corresponding estimated risk is made available to the distribution system operator, who may therefore take a decision comparing it to an arbitrary level of risk coverage, favoring either the power delivery to customers or the reduction of the transformer ageing rate; this level is formulated in this paper having an intuitive physical meaning, thus enabling its setting also by non-expert operators. Comprehensive numerical experiments based on actual data are presented under different configurations and scenarios, in order to validate the proposal from an energetic and economic point of view.

Wind-solar complementarity and effective use of distribution network capacity

Exploiting the diversity between different renewable resources is regarded as a significant tool to managing their grid integration. Hybrid combinations of resources provide the potential to smooth output and so overcome limits on the export of power, but their network wide impact is not well understood. This paper examines whether combinations of renewable distributed generation can make more effective use of distribution network capacity. A multi-period, multi-resource optimal power flow approach is used to optimally configure wind and solar photovoltaic capacity to maximise energy production whilst complying with network physical limits. The effectiveness of hybrid distributed generation and the optimization method was examined through comparison with cases using single types of renewable distributed generation. This study demonstrates that by capturing the complementarity between renewables through hybrid design, the network can host more renewable generation capacity and increase total energy export. In addition, smart grid techniques, such as active network management, further boosts the value of resource diversity by allowing connection of more generation capacity of all considered renewables through isolating the infrequent co-occurrence of high outputs during periods of low electricity demand.

Enhancing photovoltaic hosting capacity—A stochastic approach to optimal planning of static var compensator devices in distribution networks

To improve photovoltaic hosting capacity of distribution networks, this paper proposes a novel optimal static var compensator planning model which is formulated as a two-stage stochastic programming problem. Specifically, the first stage of our model determines the static var compensator planning decisions and the corresponding photovoltaic hosting capacity. In the second stage, the feasibility of the first stage results is evaluated under different uncertainty scenarios of load demand and photovoltaic output to ensure no constraint violations, especially no voltage constraint violations. In addition, we simultaneously consider the minimization of static var compensator planning cost and the maximization of photovoltaic hosting capacity by formulating a multi-objective function. To improve the computational efficiency, a solution method based on Benders decomposition is developed by decomposing the two-stage problem into a master problem and multiple subproblems. The effectiveness of the proposed model and solution method is validated on modified IEEE 37-node and 123-node distribution systems. Last, our results show that the proposed model can significantly improve the photovoltaic hosting capacity. The case studies also demonstrate that the PV hosting capacity becomes insensitive to the additional SVC planning cost when the total cost exceeds about $175,000.

Optimized design method for storage systems in photovoltaic plants with delivery limitation

It results widely common for distribution network operators to impose restrictions on delivered solar photovoltaic generated power when the power plant rated power is greater than the maximum allowed due to the distribution network capacity. Thus, a feasible solution to maximize the performance of the solar power plant is the integration of battery energy storage systems. Although this configuration has been extensively studied in the existing literature, an optimal design method to determine the proper size and operation of the energy storage system needs to be developed. In this paper, a novel method to help power plants designers to determine the optimal battery energy storage capacity to integrate into any solar photovoltaic power plant is provided. The proposed algorithm minimizes the potential power curtailment and optimizes the utilization rate of the batteries storage system. The algorithm can be applied to any grid connected solar photovoltaic power plant under delivery power restrictions, regardless of power capacity and location. The algorithm has been implemented to a simulated power plant with delivery limitations based in a real case, and results with the optimal battery capacity show that the system would be able to recover up to the 83% of the curtailed energy and a yearly average capacity utilization of 56%. Moreover, the BESS operation has been validated with a scaled model run in Simulink and laboratory measurements, achieving 98% of curtailed energy recovery rate and a 57% of average capacity utilization.

Enhanced Electric Vehicle Integration in the UK Low-Voltage Networks With Distributed Phase Shifting Control

Electric vehicles (EV) have gained global attention due to increasing oil prices and rising concerns about transportation-related urban air pollution and climate change. While mass adoption of EVs has several economic and environmental benefits, large-scale deployment of EVs on the low-voltage (LV) urban distribution networks will also result in technical challenges. This paper proposes a simple and easy to implement single-phase EV charging coordination strategy with three-phase network supply, in which chargers connect EVs to the less loaded phase of their feeder at the beginning of the charging process. Hence, network unbalance is mitigated and, as a result, EV hosting capacity is increased. A new concept, called Maximum EV Hosting Capacity (HC max ) of low voltage distribution networks, is introduced to objectively assess and quantify the enhancement that the proposed phase-shifting strategy could bring to distribution networks. The resulting performance improvement has been demonstrated over three real UK residential networks through a comprehensive Monte Carlo simulation study using Matlab and OpenDSS tools. With the same EV penetration level, the under-voltage probability was reduced in the first network from 100% to 54% and in the second network from 100% to 48%. Furthermore, percentage voltage unbalance factors in the networks were successfully restored to their original values before any EV connection.

Optimization of Power Supply Capacity of Distribution Network Considering the Participation of Power Sales Companies in Spot Power Trading

As an important part of the electricity trading market, the power sales company is an important part of the electricity trading market. It can not only be used as the main body to buy electricity from the market transaction but also as the main body to transmit electricity to the market and users, which changes the power flow distribution of the distribution network and has a certain impact on the power supply capacity of the distribution network. Based on the dual roles of power sales companies, this paper, first, analyzes the interaction between market transactions and power supply capacity of distribution networks. Second, considering the internal controllable distributed generation and controllable load participating demand-side response, a double-layer model of distribution network power supply capacity considering the participation of power sales companies in spot trading is established. According to the characteristics of the model, this paper uses the improved repetitive power flow algorithm and the original dual interior point method to solve the model. Finally, the improved IEEE33 node is verified. The example shows that the power sales company participates in the power transaction by flexibly adjusting the power purchase and sale strategy, which not only ensures the profit but also improves the power supply capacity of the distribution network.

Impact of Smart Inverters on Feeder Hosting Capacity of Distribution Networks

Penetration of renewable energy based distributed generators into power networks is limited. This is due to several reasons such as intermittency of the generation, low-inertia during disturbances and high variation of local voltage and frequency. Traditionally, distribution networks are designed for a finite voltage drop with distance from feeder connection. When PV panels are deployed at households, their impact on the local voltage profile becomes very substantial. Especially, when there is high solar radiation, generated power increases and the local voltage exceeds the permittable limits. Smart inverters are introduced to tackle this problem. Unlike other inverters, they can follow the local network measurements and provide auxiliary voltage and frequency support. With these features, smart inverters have the ability to push the renewable energy penetration level further. To investigate this phenomenon, custom smart inverter models are developed. Power flow calculation steps are modified to include smart inverter's active inputs. Then, feeder hosting capacity studies were run with conventional and smart inverters to investigate the improvement. Developed models, modified power flow algorithm and results of simulations are reported. Findings show renewable energy share can be increased in networks with smart inverter deployments only, without making substantial changes to rest of the network.

Modelling and allocation planning of voltage‐sourced converters to improve the rooftop PV hosting capacity and energy efficiency of distribution networks

This paper presents a planning approach for improving the rooftop photovoltaic (PV) hosting capacity and energy efficiency of distribution networks with the placement of voltage-sourced converters (VSCs). The PV hosting capacity (PVHC) is the maximum amount of PV generation that a distribution network can accommodate without deteriorating the operational performance of the network. The PVHC is derived under the constraint of a maximum allowable network power loss. Two different types of VSCs are modelled for the placement in distribution networks to improve the PVHC. These are series and shunt VSCs. The series VSC is designed to inject a series voltage in quadrature with the line current to maintain a constant bus voltage. The shunt VSC is designed to improve the load power factor to unity by injecting a shunt compensating current in quadrature with the bus voltage. The objective function is to maximise the PVHC to obtain the maximum PV generation capacity to be integrated in each bus. The particle swarm optimisation is used as a solution approach. The results show that the placements of VSCs improve the PVHC. This also reduces energy loss when there is no PV generation available.

Calculation of maximum permitted capacity of photovoltaic based on flower pollination algorithm combined with genetic algorithm (GA-FPA) in distribution network

The interconnection of distributed photovoltaic (PV) power in the distribution network will bring plenty of adverse effects. It is critical of researching on maximum permitted capacity (MPC) of distribution network to maintain the safe operation of distribution network. A mathematical optimization model was constructed for the MPC of distributed PV with the objective of maximizing the difference between the sum of distributed PV introduction and the network loss, and the constraints of system power flow, node voltage, feeder current, and short-circuit current. At the same time, an improved Flower Pollination Algorithm (FPA) that is Flower Pollination Algorithm combined with Genetic Algorithm (GA-FPA) was proposed to analyse IEEE 33-bus system. Further, by comparing with other optimization algorithms in terms of convergence speed and convergence accuracy, like original FPA and Genetic Algorithm (GA), the correctness of the model and the effectiveness of the algorithm are verified.

Simultaneous optimisation of photovoltaic hosting capacity and energy loss of radial distribution networks with open unified power quality conditioner allocation

This study presents a multi-objective planning approach to optimally place open unified power quality conditioner (UPQC-O) by simultaneously optimising the photovoltaic (PV) hosting capacity (PVHC) and energy loss of distribution networks. The modelling of UPQC-O consisting of a series and a shunt inverter is carried out so as to place in distribution networks. The Pareto-dominance-based approach is used to simultaneously optimise the objective functions to determine the optimal PV generation capacity in each bus and the locations of the inverters of UPQC-O. The limits on bus voltage magnitude, line current flow, maximum PV generation capacity in each bus, and the percentage of voltage sag mitigated load are considered to be the operational constraints in this planning problem. The solution strategy used is the multi-objective particle swarm optimisation. The approach provides the Pareto-approximation set consisting of a number of trade-off solutions in view of PVHC and energy loss. A utility can choose a solution for implementation depending on its desired PVHC and/or energy loss level. The results show that the PV deployment in distribution networks reduces the energy loss. However, the amount of energy loss reduction diminishes with higher and higher values of PV capacity integration.

E-fulfilment and distribution in omni-channel retailing: a systematic literature review

PurposeGiven the progressive growth of e-commerce sales and the rising interest in omni-channel (OC) retailing amongst academics and practitioners, the purpose of this paper is to provide an up-to-date literature review on the logistics involved when moving towards OC retailing. Specifically, we have examined the main issues relating to e-fulfilment and distribution, highlighting how the topic has been developed over time, and identifying the most promising research streams for the near future.Design/methodology/approachA systematic literature review methodology is adopted. The review is based on 58 papers published from 2002 to 2017 in 34 international journals. The papers were analysed and categorised according to their defining characteristics, methodologies adopted and themes addressed.FindingsThis paper provides an overview of the main issues relating to e-fulfilment and distribution experienced by companies shifting towards OC, mapped along three dimensions: distribution network design, inventory and capacity management, delivery planning and execution. Despite the growing interest in OC retailing, many key topics are still under-represented, including the evolution of retail distribution networks, assortment planning over multiple channels, the logistics role played by stores in the delivery process and the interplay between different logistics aspects.Originality/valueThe paper offers insights into the main logistics issues in MC and OC retailing, as well as highlights potential fields for further investigation. From a managerial perspective, this paper is useful for retailers adopting an OC approach to guide their future efforts concerning their business logistics model.