Congestion management of power system with uncertain renewable resources and plug‐in electrical vehicle

Prajapati, Vijaykumar K.; Mahajan, Vasundhara

doi:10.1049/iet-gtd.2018.6820

Cited by 19 publications

(18 citation statements)

References 40 publications

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“…Congestion management of deregulated power system containing RES is carried out by considering various approaches such as demand response program, plug-in electrical vehicles, ESS, enhancement of available transfer capacity (ATC). [23][24][25][26] However, during contingency/stressed condition, generation rescheduling approach alone is not able to relieve the congestion in the network but it is essential to apply load shedding for attaining new equilibrium state of power system. Load shedding is the process of load curtailment using set of control variables to reach new operating point.…”

Section: Literature Surveymentioning

confidence: 99%

“…The techniques to relieve congestion such as rescheduling of generators, price‐based approach, sensitivity‐based approach, optimal placement of flexible AC transmission system (FACTS) devices, auction‐based approach, zonal congestion‐based approach, responsive demand‐based approach have been demonstrated in References 17‐22. Congestion management of deregulated power system containing RES is carried out by considering various approaches such as demand response program, plug‐in electrical vehicles, ESS, enhancement of available transfer capacity (ATC) 23‐26 …”

Section: Introductionmentioning

confidence: 99%

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Congestion management of integrated transmission and distribution network with RES and ESS under stressed condition

Prajapati

Mahajan

Padhy

2021

Int Trans Electr Energ Syst

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Summary In this article, the multi‐objective optimization‐based congestion management approach for integrated transmission and distribution system under stressed condition is presented. The congestion is managed by optimized charging and discharging of energy storage systems (ESSs). The coordination among transmission system operator (TSO) and distribution system operator (DSO) takes place for the economic and optimum exchange of power. The main intent of this study is to minimize the amount of load shedding (MW) and its cost ($/MWh) by minimizing the generation cost ($/MWh). These are conflicting objectives as for less load shedding, the system has to have more generation and hence higher cost. The negotiable solution among conflicting objectives is obtained by using the fuzzy min‐max approach. The ESS charging and discharging are optimized for their maximum contribution. This increases the available power (MW), thereby reducing the uncertainty of renewable energy sources and hence lesser load shedding. The analysis is conducted for constant load modeling (CLM) and voltage‐dependent load modeling. The results show that CLM has less load shedding. The proposed approach is implemented on a modified IEEE‐30‐bus test system integrated with the nine‐bus distribution network. Simulations and validations are done using General Algebraic Modeling Solver.

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Section: Literature Surveymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Congestion management of integrated transmission and distribution network with RES and ESS under stressed condition

Prajapati

Mahajan

Padhy

2021

Int Trans Electr Energ Syst

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“…In a restructured power system environment, the congestion in the transmission line is a condition where more power will be scheduled to flow across transmission lines and transformers than the specified physical limits [1][2][3]. The different constraints for the system are thermal limit of lines, bus voltage limits, etc.…”

Section: Introductionmentioning

confidence: 99%

A Soft Computing-Based Analysis of Congestion Management in Transmission Systems

Subramaniyan¹,

Venugopal

2023

Teh. vjesn.

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Congestion in the transmitting system is unitarily responsible for technological problems that appear, especially in a deregulated environment. The postderegulation operation history of the electrical power system has placed greater pressure on the Independent System Operator (ISO) to assure a secure, congestion-less transmission network. Blackout and brownout voltage dip issues occur due to the heavy loading condition. Hence, this paper presents a novel approach for the relief of congestion by using a nature-inspired algorithm, namely Particle Swarm Optimization and Firefly Algorithm by considering various factors for re-dispatching active power of generators during overloading conditions. The algorithms are tested on IEEE 30 and IEEE 39 Bus standard test systems and the obtained results show the effectiveness of the proposed algorithm in the MATLAB environment. The congestion management (CoM) method is formulated as a constrained optimization problem with the objective function of relieving the overloading through minimization of factors such as Generator Shift Factor (GSF), Bus Sensitivity Factor (BSF), Line utilization Factor (LUF), and Congestion Index (CI). These factors are helpful to mitigate the transmission congestion, which in turn helps to reduce the real power losses.

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“…However, as the number of EVs increases, the negative effects of their charging on the power grid become more evident, especially at the low-voltage level. In fact, high concentrations of EVs have various harmful effects due to the overlap between EV charging, residential peak loads and renewable generation [8][9][10]. For these reasons, the growing number of EVs, in parallel with the growing penetration of renewable energy sources, leads the power grid facing a challenging future [11,12].…”

Section: Introductionmentioning

confidence: 99%

Impact of Different Charging Strategies for Electric Vehicles in an Austrian Office Site

et al. 2020

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Electric vehicles represent a necessary alternative for wheeled transportation to meet the global and national targets specified in the Paris Agreement of 2016. However, the high concentration of electric vehicles exposes their harmful effects on the power grid. This reflects negatively on electricity market prices, making the charging of electric vehicles less cost-effective. This study investigates the economic potential of different charging strategies for an existing office site in Austria with multiple charging infrastructures. For this purpose, a proper mathematical representation of the investigated case study is needed in order to define multiple optimization problems that are able to determine the financial potential of different charging strategies. This paper presents a method to implement electric vehicles and stationary battery storage in optimization problems with the exclusive use of linear relationships and applies it to a real-life use case with measured data to prove its effectiveness. Multiple aspects of four charging strategies are investigated, and sensitivity analyses are performed. The results show that the management of the electric vehicles charging processes leads to overall costs reduction of more than 30% and an increase in specific power-related grid prices makes the charging processes management more convenient.

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Congestion management of power system with uncertain renewable resources and plug‐in electrical vehicle

Cited by 19 publications

References 40 publications

Congestion management of integrated transmission and distribution network with RES and ESS under stressed condition

Congestion management of integrated transmission and distribution network with RES and ESS under stressed condition

A Soft Computing-Based Analysis of Congestion Management in Transmission Systems

Impact of Different Charging Strategies for Electric Vehicles in an Austrian Office Site

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