Reliability Assessment of Distribution Power System When Considering Energy Storage Configuration Technique

Abstract

The main task of distribution systems is to provide acceptable reliability, economic and quality service of electrical power according to the demanded load value. To fulfill this task more accurately, the reliability performance of the distribution system can be performed and measured using a wide variety of indices, which are divided into energy indices and frequency/expectation indices. This study evaluates the reliability indices of a part of the distribution network selected as a model and deals with the selection of the most suitable feeder by connecting energy storage units to the busbars. Using IEEE Standard 1366 reliability indices, historical data from Prosperous Electricity Distribution Company (PEDC), which is used to evaluate reliability based on the 5-year past reliability assessment of the power system (RAPS), was selected. In addition, as an innovation in this application process, energy storage systems (ESS) have been evaluated according to four different network configurations (A-B-C-D) to increase RAPS and achieve more realistic results. Using DigSILENT, ESS-based configurations are designed, comparisons are made, and configuration B is the best result to increase system reliability and the 80E6 feeder is optimal. In addition, reliability changes achieved by network configuration have demonstrated the importance of optimal configuration planning to improve the uninterrupted and sustainable energy quality of the system based on storage technology. INDEX TERMS Energy storage, Monte Carlo methods, power distribution faults, power system control, power system reliability.

Transmission of Frequency Balance Instructions and Secure Data Sharing Based on Chaos Encryption in Smart Grid-Based Energy Systems Applications

“…As a result, it has been accepted that power cuts should be taken into consideration first in obtaining DR [11][12][13][14]. In addition, reserve planning is gaining importance day by day in the face of difficulties in energy storage in power systems, which also provides the frequency balance [15]. Frequency control in power systems has great importance in terms of system balance and uninterrupted energy, which instructions should be reliable and protected for reserve control.…”

Multi‐stage dynamic optimal allocation for battery energy storage system in distribution networks with photovoltaic system

“…In terms of decision variables, the related researches can be divided into two categories, the static ones and the dynamic ones, that is, to optimize the investment time of ESS or not. The static optimal allocation [5][6][7][8][9][10][11][12][13][14][15] only focuses on the ESS location and capacity, and all the equipment are put into use at the same time. The dynamic optimal allocation optimizes the location, capacity, and time of ESS considering the dynamic growth characteristics of loads and distributed renewable energy.…”

“…The technical constraints include system operation constraints such as the energy balance constraint, power flow constraint, ESSs' operation constraints, and design constraints which are set for actual design requirements such as renewable energy curtailment constraint, power supply reliability constraint, upper and lower limits of installed capacity of ESSs, and so on. [5][6][7][8][9][10][11][12][13][14][15] The actual constraints are mainly to consider the impacts of investment budget, actual environment on the site, construction conditions, and so on. Ref.…”

“…Ref. 11 improves the uninterrupted and sustainable energy quality of the system based on storage technology.…”

Integration Problems of Photovoltaic Systems-Wind Power, Solutions and Effects on Power Quality

“…Many studies have examined the output variations of PV systems [17] and proposed different mitigation methods [18]. Some of the methods that analyze these propositions; Volt-Var control strategies, local control of reactive power, efficient inverters [19], application of storage units [20][21][22][23][24] and the use of forecasting techniques [25,26], mitigating the negative effects of fluctuations in PV systems.…”