Distribution Transformer Capacity Research Articles

Construction of an Adaptive Metric Model for Maximum Access Capacity of Distributed Photovoltaic in Active Distribution Networks

Distributed photovoltaic (PV) access to the active distribution network can easily cause power fluctuation and affect the reasonable setting. The maximum access capacity is constructed as an adaptive metric model. Taking the total installed capacity as the objective function, the maximum access capacity adaptive metering model is constructed. For the constructed model, the constraints of light abandonment constraint, energy storage system constraint, voltage deviation constraint at the common connection point, line limit capacity constraint and distribution transformer capacity constraint are set. The model is solved by using multiple swarm genetic algorithms, output maximum access capacity. The abandonment rate of PV nodes is less than 3%, and the voltage overrun rate and line capacity overrun rate are less than 1%.

Optimization Model of Electric Vehicles Charging and Discharging Strategy Considering the Safe Operation of Distribution Network

Against the background of carbon neutrality, the power dispatching operation mode has undergone great changes. It not only gradually realizes the coordinated control of source–grid–load–storage, but also strives to realize the multi-level coordination of the transmission network, distribution network and microgrid. Disorderly charging and discharging of large-scale electric vehicles (EVs) will have a great negative impact on the distribution network, but aggregating EVs and guiding them to charge and discharge in an orderly manner will play a positive role in delaying investment in the distribution network. Therefore, it is urgent to adopt an effective scheduling control strategy for electric vehicle charging and discharging. First, a variety of indexes were set to analyze the influence of EVs access on distribution network and the correlation between the indexes. Then, by defining the EVs penetration rate and the load simultaneous rate, the charging load planning of EVs was calculated. Based on the simultaneous load rate, the regional electricity load plan was calculated, and a configuration model of distribution capacity suitable for charging loads in different regions was constructed. Finally, an optimal dispatch model for electric vehicles considering the safety of distribution network was proposed and the distribution transformer capacity allocation model was used as the optimization target constraint. Compared with most optimized dispatch models used to maximize aggregator revenues and reduce peak-to-valley differences and load fluctuations in distribution networks, this model could effectively reduce unnecessary investment while meeting regional distribution transformer needs and maintaining distribution network security. Taking the improved IEEE 34-bus systems as an example, the simulation analysis was carried out and the investment demand of distribution network under the condition of disordered and orderly charge and discharge was compared. The results show that the proposed optimal scheduling method can effectively reduce the load fluctuation of distribution network, keep the voltage offset within the allowable voltage deviation range, and can effectively delay the investment of distribution network.

Enhancing the hosting capacity of distribution transformers for using dynamic component rating

With the increasing deployment of solar power, high photovoltaic (PV) penetration is expected to adversely impact the distribution grid. One of the challenges relates to the power flow and transfer capacity of the distribution transformers. Transformers might not have sufficient capacity to accommodate for all the downstream PV to feed back to a higher voltage level during sunny periods with low consumption. In this paper, we estimate the transformer hosting capacity considering dynamic thermal rating for residential consumption with increasing amounts of PV penetration. This paper analyzes the impact of PV integration and increased consumption on the aging of a transformer. The potential of dynamic rating to enhance transformer hosting capacity is studied under varying environmental conditions.

Investigation on Temperature Rise Characteristic and Load Capacity of Amorphous Alloy Vegetable Oil Distribution Transformers with 3D Coupled-Field Method

The large differences in the load peak and valley of rural distribution networks always bring severe problems to system planners and operators. Given this issue, this paper deals with the hot-spot temperature (HST) of the transformer and its overload capability, and proposes a modeling method-based online monitoring of practical parameters. In the current work, a temperature-fluid coupling field of the 315 kVA vegetable oil distribution transformer is developed in both the two-dimensional and three-dimensional geometry, by which the convection and heat dissipation process can be studied. The grid of the model is divided into regions to increase the calculation speed and ensure the accuracy of the calculation. Secondly, tests related to the temperature rise of the transformer are carried out. The accuracy of the three-dimensional model is later discussed in terms of temperature and fluid velocity distribution. Finally, the temperature distribution laws of the amorphous alloy vegetable oil distribution transformers (AVDT) are compared and analyzed under different load conditions. Findings reveal that the AVDT has low no-load loss and strong overload capacity, which is capable of reducing the internal overheating accidents of the transformer.

Optimizing the effect of charging electric vehicles on distribution transformer using demand side management

This paper mainly aims to present the demand side management (DSM) of electric vehicles (EVs) by considering distribution transformer capacity at a residential area. The objective functions are formulated to obtain charging schedule for individual owner by i) minimizing the load variance and ii) price indicated charging mechanism. Both the objective functions profit the owner in the following ways: i) fulfilling their needs, ii) minimizing overall charging cost, iii) lessening the peak load, and iv) avoiding the overloading of distribution transformer. The proposed objective functions were worked on a residential area with 8 houses each house with an EV connected to a 20 kVA distribution transformer. The formulations were tested in LINGO platform optimization modeling software for linear, nonlinear, and integer programming. The results obtained were compared which gives good insight of EV load scheduling without actual price prediction.

PENEMPATAN DAN PEMILIHAN KAPASITAS TRANSFORMATOR DISTRIBUSI SECARA OPTIMAL PADA PENYULANG PERUMNAS

Some distribution transformers in densely populated areas have a loading percentage of more than 100% and also less than 10%. This problem shows that the use of a distribution transformer is inappropriate. With descriptive, correlational and comparative research methods, it is hoped that it can optimize the placement and capacity selection of distribution transformers. Data were taken from 25 people living in the Pemecutan Kelod and Tegal Harum areas using questionnaires and interviews. The data were tested using the T and Pearson tests to determine the effect of placing the distribution transformer. The results of equalization of the load with the addition of a new distribution transformer and relocation of the distribution transformer capacity to the feeder are expected to get optimal results. The technical solution is obtained with a voltage of less than 10% and a distribution transformer capacity that is in accordance with the growth of the population electrical load. Socially and culturally, for the level of conformity there is an increase in the harmony of the population after the placement of a new distribution substation (t = -7.71 and p <0.05), for the comfort level there is an increase in the comfort of the population after the placement of a new distribution substation (t = -9.57 and p <0.05), and for the level of security there was an increase in the tranquility of the population after the placement of a new distribution substation (t = -8.42 and p <0.05). The relationship between suitability and comfort obtained a very strong relationship (r = 0.90), the relationship between suitability and safety obtained a very strong relationship (r = 0.85), and the relationship between comfort and safety obtained a very strong relationship (r = 0.86).

Grid-connected Micro-grid Power Supply and Distribution Transformer Capacity Optimization System Design in the Electricity Sales Environment

With the current gradual opening of our country’s electricity sales market and the successive improvement of related policies for grid-connected micro-grids, grid-connected micro-grid power supplies and their distribution transformer capacity have received attention and development. Based on the good development of my country’s electricity sales market environment, this paper designs the grid-connected microgrid power supply optimization system and its distribution and conversion capabilities to optimize the quality of electricity sales and optimize the grid configuration. In view of the fact that the operation of the microgrid system in my country’s market environment is more flexible at this stage, after a long time simulation test, a simulation analysis of the operation status of the grid-connected microgrid is carried out. In the course of the experiment, the electricity price in the distribution point process and the real-time changes of the electricity purchase price in the market will be considered comprehensively, and the processing in the micro-electricity system based on its distribution transformer capacity optimization system and the load forecast result will be considered. This article uses a power grid project actually constructed in East China as an example to analyze the results of simulation calculations. Then the NSGA-II algorithm is used to solve the optimized model for the cost and benefit composition of the grid. The optimized configuration method of the optical storage microgrid proposed in this paper can ensure the reliable power supply of users’ important loads during the off-grid operation of the microgrid, increase the installed capacity of distributed photovoltaics, and the configured energy storage system also allows enterprises to achieve low electricity prices. Purchase electric energy at any time and use it to supplement the load’s demand for electric energy during peak electricity price periods, thereby increasing revenue. The experimental research results show that the design of the grid-connected microgrid power supply capacity optimization system under the electricity sales environment studied in this paper can effectively reduce the additional investment required by external loads and the capacity of optical storage and distribution transformers. Only then can the economic marketing profit of the microgrid be improved to a certain extent.

The Added Value of Coordinating Inverter Control

Coordinated photovoltaic inverter control with centralized coordination of curtailment can increase the amount of energy sent from low-voltage (LV) distribution networks to the grid while respecting voltage constraints. First, this paper quantifies the improvement of such an approach relative to autonomous droop control, in terms of PV curtailment and line losses in balanced networks. It then extends the coordinated inverter control to unbalanced distribution networks. Finally, it formulates a control algorithm for different objectives such as the fairer distribution of PV curtailment and rewarding PV customers for utilizing the excess power locally. The coordinated inverter control algorithm is tested on the 114-node and 906-bus LV European test feeders with cable sizes between 50mm^2 and 240mm^2 and validated with reference to OpenDSS. The results demonstrate that coordinated inverter control is superior when applied to high impedance LV networks and LV networks constrained by the distribution transformer capacity limits compared to autonomous inverters. On the 95mm^2 overhead line, it yields a 2% increase on average in the utilized PV output with up to 5% increase for some PV locations at higher penetration levels. Up to a 20% increase in PV hosting capacity was observed for location scenarios with PV system clustering.

ANALISIS JARINGAN DAN PEMELIHARAAN PADA JARINGAN DISTRIBUSI DI PT.PLN WILAYAH CABANG PINRANG

Abstract— Used in electrical energy distribution effort to the community. Know the factors that affect the capacity of power distribution transformers for 3 phase and 1 phase and to know system maintenance performed on the distribution network and transformer at. PLN ( Persero ) Branch Pinrang .All data that is required in this study was obtained through several instruments such as surveys or direct observation , interviews , and a review of literature used to complement and meet the required data. All data were collected and analyzed using descriptive analysis . These results prove that the distribution network is used on the PT . PLN ( Persero ) Branch Pinrang consists of a primary distribution channels , distribution transformers and secondary distribution channels. This distribution network is used to distribute electrical energy to the entire community of Pinrang. Kapasitas of a distribution transformer for 3 phases and the first phase is determined by the amount of load that is served is added to the burden of the future development. System maintenance is performed on the distribution network and transformer at. PLN ( Persero ) Branch Pinrang done regularly and proactively with emphasis on preventive measures aiming to prevent disturbance of the action reprensif in overcoming the disorder.

Coordinating the operations of smart buildings in smart grids

With big thermal storage capacity and controllable loads such as the heating ventilation and air conditioning systems, buildings have great potential in providing demand response services to the smart grid. However, uncoordinated energy management of a large number of buildings in a distribution feeder can push power distribution systems into the emergency states where operating constraints are not completely satisfied. In this paper, we propose a bi-level building load aggregation methodology to coordinate the operations of heterogeneous smart buildings of a distribution feeder. The proposed methodology not only reduces the electricity costs of buildings but also guarantees that all the distribution operating constraints such as the distribution line thermal limit, phase imbalance, and transformer capacity limit are satisfied.

Coordinated Operation of a Neighborhood of Smart Households Comprising Electric Vehicles, Energy Storage and Distributed Generation

In this paper, the optimal operation of a neighborhood of smart households in terms of minimizing the total energy procurement cost is analyzed. Each household may comprise several assets such as electric vehicles, controllable appliances, energy storage and distributed generation. Bi-directional power flow is considered both at household and neighborhood level. Apart from the distributed generation unit, technological options such as vehicle-to-home and vehicle-to-grid are available to provide energy to cover self-consumption needs and to inject excessive energy back to the grid, respectively. The energy transactions are priced based on the net-metering principles considering a dynamic pricing tariff scheme. Furthermore, in order to prevent power peaks that could be harmful for the transformer, a limit is imposed to the total power that may be drawn by the households. Finally, in order to resolve potential competitive behavior, especially during relatively low price periods, a simple strategy in order to promote the fair usage of distribution transformer capacity is proposed.

Decentralized Charging of Plug-In Electric Vehicles Using Lagrange Relaxation Method at the Residential Transformer Level

Abstract The expected rise of plug-in electric vehicles (PEVs) will lead to a significant additional demand on low voltage distribution systems, and PEVs can challenge power quality and reliability of power systems if their charging is not coordinated. The PEV aggregator, acting as an intermedium between customers and the grid operator, can solve the charging management problem effectively. In this study, a decentralized scheduling scheme of aggregators for PEV charging based on Lagrange Relaxation method is proposed. At the same time, a centralized model of aggregators is also formulated in the same situation in order to make comparisons with the proposed scheme. The two charging models are both aimed at maximizing the charging profit of PEV aggregators considering constraints including users’ electricity demand, charging time, available capacity of distribution transformers, etc. A number of charging scenarios are simulated to evaluate the proposed method. The economic benefits, computational complexity and efficiency are compared and analyzed between the centralized charging and the decentralized charging. Simulation results verify that the decentralized charging strategy based on Lagrange Relaxation method gains charging profit close to the centralized charging yet is more efficient and realizable than the centralized charging.

Impact of EV Charger Load on Distribution Network Capacity: A Case Study in Toronto

This paper presents a study of the impact of the electric vehicle (EV) charger load on the capacity of distribution feeders and transformers of an urban utility. A residential neighborhood of the city of Toronto, Canada, is selected to perform the study based on survey results that showed a high tendency for EV adoption. The two most loaded distribution transformers of such a neighborhood are studied along with their cable feeders via steady-state simulations in CYME software. A worst case scenario of full EV penetration is studied, where all chargers are connected to the system simultaneously at the peak summer or winter load. The effect of increasing the rate of EV adoption on the performance of distribution networks is examined with correlation to the ambient temperature. Finally, the impact of increasing the charger size on system performance is explored. The results send a few warning signals of potential equipment overload to utility companies under certain system loading and EV charging levels as EV use grows, impacting utility future planning and operation. This will assist utilities in taking appropriate measures with respect to operating the existing system and also planning for the future.

Study on the Energy Management System of Electric Vehicle Charging Station Based on Multi-Agent System

Under the constraints of distribution transformer capacity and customer charging needs, a UML model for EMS of EV Charging Station is proposed to analyze energy dispatching functions and integrate control strategies of Charging Station. Due to the fact that EV charging system is a complex adaptive system, Multi-Agent System method is utilized in this model. The UML development process provides an extensible and integrated framework, which lays the foundations for the further development on EMS of EV Charging station.

Design of artificial neural networks for distribution feeder loss analysis

To enhance the efficiency for power loss analysis of voluminous distribution feeders, ANN-based simplified power loss models with the Levenberg–Marquardt (LM) algorithm have been developed for overhead feeders and underground feeders, respectively. The three-phase load flow analysis is executed to obtain the sensitivity of feeder loss with variations in power loading, conductor length, and total capacity of distribution transformers. Through this, the data set for neural network training is prepared to derive the ANN-based simplified power loss models. The power loss of each distribution feeder can be easily derived from the key factors of hourly loading, feeder length, and transformer capacity. By integrating the power loss of all feeders, the power loss of the entire distribution system can thus be obtained to estimate the operation efficiency of the Taipower system.

A Systematic Loss Analysis of Taipower Distribution System

This paper presents a systematic methodology to analyze the power loss of whole distribution system in Taipower. The total power delivered to the distribution system has been calculated according to the total power generation and power loss of transmission system. To enhance the efficiency for power loss analysis of voluminous distribution feeders, the artificial neural network (ANN)-based simplified power loss models have been developed for the overhead feeders and underground feeders, respectively. The three-phase load flow analysis is executed to find the sensitivity of feeder loss with the variation of power loading, conductor length, and total capacity of distribution transformers. By this way, the data set for neural network training is prepared to derive the ANN-based simplified power loss model. The power loss of each distribution feeder can be derived easily according to the key factors of hourly loading, feeder length, and transformer capacity. By integrating the power loss of all feeders, the power loss of whole distribution system is therefore obtained to estimate the operation efficiency of Taipower system.

Optimal distribution transformer sizing by dynamic programming

The objective of this article is to propose an efficient strategy for transformer planning by taking into account the load characteristics so that the overall life cycle cost of distribution transformers can be reduced. The typical load patterns and load growth of residential, commercial and industrial customers are derived by a load survey system and then used to solve the transformer copper loss and core loss. The three-phase load flow analysis is performed to solve the yearly peak power loss and annual energy loss according to the customer typical load patterns. The transformer peak power loss and energy loss as well as the initial investment cost, installation cost and depreciation cost of distribution transformers are combined to form the overall cost function. The dynamic programming (DP) is then applied to find the optimal capacity and installation strategy of distribution transformers. To verify the accuracy of the proposed methodology, a practical Taipower distribution feeder has been selected for computer simulation. The conventional transformer sizing by considering the customer peak loading is also investigated for comparison. It is found that more than 5% of overall life cycle cost of distribution transformers can be saved by the proposed optimal transformer sizing strategy.