Showing 10 results for Distribution System
A. Fereidunian, H. Lesani, C. Lucas, M. Lehtonen, M. M. Nordman,
Volume 2, Issue 3 (7-2006)
Abstract
Almost all of electric utility companies are planning to improve their
management automation system, in order to meet the changing requirements of new
liberalized energy market and to benefit from the innovations in information and
communication technology (ICT or IT). Architectural design of the utility management
automation (UMA) systems for their IT-enabling requires proper selection of IT choices for
UMA system, which leads to multi-criteria decision-makings (MCDM). In response to this
need, this paper presents a model-based architectural design-decision methodology. The
system design problem is formulated first then, the proposed design method is introduced,
and implemented to one of the UMA functions–feeder reconfiguration function (FRF)– for
a test distribution system. The results of the implementation are depicted, and
comparatively discussed. The paper is concluded by going beyond the results and fair
generalization of the discussed results finally, the future under-study or under-review
works are declared.
M. Padma Lalitha, V.c Veera Reddy, N. Sivarami Reddy,
Volume 6, Issue 4 (12-2010)
Abstract
Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss, etc. This paper presents a new methodology using Fuzzy and Artificial Bee Colony algorithm(ABC) for the placement of Distributed Generators(DG) in the radial distribution systems to reduce the real power losses and to improve the voltage profile. A two-stage methodology is used for the optimal DG placement . In the first stage, Fuzzy is used to find the optimal DG locations and in the second stage, ABC algorithm is used to find the size of the DGs corresponding to maximum loss reduction. The ABC algorithm is a new population based meta heuristic approach inspired by intelligent foraging behavior of honeybee swarm. The advantage of ABC algorithm is that it does not require external parameters such as cross over rate and mutation rate as in case of genetic algorithm and differential evolution and it is hard to determine these parameters in prior. The proposed method is tested on standard IEEE 33 bus test system and the results are presented and compared with different approaches available in the literature. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency.
M. Sedighizadeh, M. Esmaili, M. M. Mahmoodi,
Volume 13, Issue 3 (9-2017)
Abstract
Distribution systems can be operated in multiple configurations since they are possible combinations of radial and loop feeders. Each configuration leads to its own power losses and reliability level of supplying electric energy to customers. In order to obtain the optimal configuration of power networks, their reconfiguration is formulated as a complex optimization problem with different objective functions and network operating constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with objective functions of minimization of power losses, System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), Average Energy Not Supplied (AENS), and Average Service Unavailability Index (ASUI). The optimization problem is solved by the Imperialist Competitive Algorithm (ICA) as one of the most modern heuristic tools. Since objective functions have different scales, a fuzzy membership is utilized here to transform objective functions into a same scale and then to determine the satisfaction level of the afforded solution using the fuzzy fitness. The efficiency of the proposed method is confirmed by testing it on 32-bus and 69-bus distribution test systems. Simulation results demonstrate that the proposed method not only presents intensified exploration ability but also has a better converge rate compared with previous methods.
M. Esmaeilzadeh, I. Ahmadi, N. Ramezani,
Volume 14, Issue 2 (6-2018)
Abstract
Distributed generation (DG) has been widely used in distribution network to reduce the energy losses, improve voltage profile and system reliability, etc. The location and capacity of DG units can influence on probability of protection mal-operation in distribution networks. In this paper, a novel model for DG planning is proposed to find the optimum DG location and sizing in radial distribution networks. The main purpose of the suggested model is to minimize the total cost including DG investment and operation costs. The operation costs include the cost of energy loss, the cost of protection coordination and also the mal-operation cost. The proposed DG planning model is implemented in MATLAB programming environment integrated with DIgSILENT software. The simulation results conducted on the standard 38-bus radial distribution network confirm the necessity of incorporating the protection coordination limits in the DG planning problem. Additionally, a sensitivity analysis has been carried out to illustrate the significance of considering these limits.
R. Mohammadi, H. Rajabi Mashhadi,
Volume 15, Issue 1 (3-2019)
Abstract
Distribution system reliability programs are usually based on improvement of average reliability indices. They have weakness in terms of distinguishing between reliability of different customers that may prefer different level of reliability. This paper proposes a new framework based on game theory to accommodate customers’ reliability requests in distribution system reliability provision. To do this, distribution reliability equations are developed so that it is recognized how game theory is suitable for this purpose and why conventional methods could not provide customer reliability requirements appropriately. It would be shown that customer participation in distribution system reliability provision can make conflict of interest and leads to a competition between customers. So, in this paper a game theoretic approach is designed to model possible strategic behavior of customers in distribution system reliability provision. The results show that by implementing the proposed model, distribution utilities would have the capability to respond to customers’ reliability requirements, such that it is beneficial for both utility and customers.
M. Ajoudani, A. Sheikholeslami, A. Zakariazadeh,
Volume 16, Issue 4 (12-2020)
Abstract
The development of communications and telecommunications infrastructure, followed by the extension of a new generation of smart distribution grids, has brought real-time control of distribution systems to electrical industry professionals’ attention. Also, the increasing use of distributed generation (DG) resources and the need for participation in the system voltage control, which is possible only with central control of the distribution system, has increased the importance of the real-time operation of distribution systems. In real-time operation of a power system, what is important is that since the grid information is limited, the overall grid status such as the voltage phasor in the buses, current in branches, the values of loads, etc. are specified to the grid operators. This can occur with an active distribution system state estimation (ADSSE) method. The conventional method in the state estimation of an active distribution system is the weighted least squares (WLS) method. This paper presents a new method to modify the error modeling in the WLS method and improve the accuracy SVs estimations by including load variations (LVs) during measurement intervals, transmission time of data to the information collection center, and calculation time of the state variables (SVs), as well as by adjusting the variance in the smart meters (SM). The proposed method is tested on an IEEE 34-bus standard distribution system, and the results are compared with the conventional method. The simulation results reveal that the proposed approach is robust and reduces the estimation error, thereby improving ADSSE accuracy compared with the conventional methods.
T. Agheb, I. Ahmadi, A. Zakariazadeh,
Volume 17, Issue 3 (9-2021)
Abstract
Optimal placement and sizing of distributed renewable energy resources (DER) in distribution networks can remarkably influence voltage profile improvement, amending of congestions, increasing the reliability and emission reduction. However, there is a challenge with renewable resources due to the intermittent nature of their output power. This paper presents a new viewpoint at the uncertainties associated with output powers of wind turbines and load demands by considering the correlation between them. In the proposed method, considering the simultaneous occurrence of real load demands and wind generation data, they are clustered by use of the k-means method. At first, the wind generation data are clustered in some levels, and then the associated load data of each generation level are clustered in several levels. The number of load levels in each generation level may differ from each other. By doing so the unrealistic generation-load scenarios are omitted from the process of wind turbine sizing and placement. Then, the optimum sizing and placement of distributed generation units aiming at loss reduction are carried out using the obtained generation-load scenarios. Integer-based Particle Swarm Optimization (IPSO) is used to solve the problem. The simulation result, which is carried out using MATLAB 2016 software, shows that the proposed approach causes to reduce annual energy losses more than the one in other methods. Moreover, the computational burden of the problem is decreased due to ignore some unrealistic scenarios of wind and load combinations.
Reza Behnam, Gevork Gharehpetian,
Volume 18, Issue 4 (12-2022)
Abstract
State estimation is used in power systems to estimate grid variables based on meter measurements. Unfortunately, power grids are vulnerable to cyber-attacks. Reducing cyber-attacks against state estimation is necessary to ensure power system safe and reliable operation. False data injection (FDI) is a type of cyber-attack that tampers with measurements. This paper proposes network reconfiguration as a strategy to decrease FDI attacks on distribution system state estimation. It is well-known that network reconfiguration is a common approach in distribution systems to improve the system’s operation. In this paper, a modified switch opening and exchange (MSOE) method is used to reconfigure the network. The proposed method is tested on the IEEE 33-bus system. It is shown that network reconfiguration decreases the power measurements manipulation under false data injection attacks. Also, the resilient configuration of the distribution system is achieved, and the best particular configuration for reducing FDI attacks on each bus is obtained.
Akanksha Jain, S.c. Gupta,
Volume 20, Issue 3 (9-2024)
Abstract
Due to the anticipated increase in loads, the power grid will encounter the issue of system peak loads in the future, which is typically addressed through grid reinforcement. However, implementing a flexibility service option can prevent the need for grid development. As the overall load continues to rise, the distribution transformer becomes overloaded. The presented work focuses on enhancing one of the parameters that define the insulation life of the transformer, known as the Loss-of-Life (LOL). Transactive approach involves the rescheduling of the battery and photovoltaic generation. Dominated Group Search Optimization (DGSO) algorithm is utilized to optimize the objective function of reducing the peak transformer load under the power flow and voltage constraints of the network. Experimental validation of the proposed method is conducted using MATLAB 2018 software. Modified IEEE 34-bus system is used to implement the proposed methodology. Numerical results obtained from various cases elucidate that the proposed model reduces the LOL of the transformer from 0.0103 to 0.0017 p.u.Comparative analysis of the proposed method with the already used methods of voltage-control and Volt-Var control have been presented.
Aida Gholami, Masume Khodsuz, Valiollah Mashayekhi,
Volume 21, Issue 1 (3-2025)
Abstract
Ensuring the protection of all components within power systems from lightning-induced overvoltage is crucial. The issue of power interruptions caused by both direct and indirect lightning strikes (LS) presents significant challenges in the electrical sector. In medium voltage distribution feeders, the relatively low dielectric strength makes them susceptible to insulation degradation, which can ultimately lead to failures in the distribution system. Therefore, implementing effective protective measures against LS is vital for maintaining an acceptable level of reliability in distribution systems. This paper presents an analytical assessment of LS-induced system overvoltage through high-frequency modeling of components within a 20kV distribution system. The study utilizes EMTP-RV software for precise component modeling, including the grounding system, surge arresters, and distribution feeders. Additionally, the operational impacts of protective devices, such as ZnO surge arresters, shield wires, and lightning rods, are evaluated to mitigate LS-induced overvoltage. A frequency grounding system is implemented using the method of moments (MOM) to analyze the grounding system's influence on LS-induced overvoltage. Furthermore, eight different scenarios are explored to assess the anti-LS capabilities of the 20kV distribution system. Each scenario involves evaluating dielectric breakdown and overvoltage across the insulator chain while proposing suitable protective solutions. The results indicate that the absence of shielding wires and surge arresters leads to higher breakdown voltages, with the lowest breakdown voltage occurring when surge arresters are installed during LS events. Additionally, the use of a frequency grounding system, due to its accurate modeling, yields more precise results compared to a static resistor approach. The MOM simulation reveals a 50% reduction in breakdown voltage under the worst-case scenario, and overall overvoltage experiences a 2% decrease.
