Demand response based congestion management of power system with uncertain renewable resources

Prajapati, Vijaykumar K.; Mahajan, Vasundhara

doi:10.1080/01430750.2019.1630307

Cited by 17 publications

(8 citation statements)

References 31 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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“…For wind power, its standard deviation and wind speed for 24 h is considered whereas for solar power, the solar irradiance, temperature and Fill Factor of solar cell are considered. The mean wind speed and solar irradiation data is taken from Ref [40,52].The available wind and solar capacity for 24 h is shown in Figs. 8 and 9 respectively.…”

Section: Resultsmentioning

confidence: 99%

Efficient Energy Management and Reliability Assessment by Optimal Placement of Renewable Energy Sources with Pump Storage Plant

Jain

Mahajan

2023

Smart Grids and Energy

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Deteriorating environment conditions due to global warming and depleting fossil fuels, has forced mankind to shift towards renewable energy sources (RES). The integration of RES in existing power system is challenging due to its intermittent nature. This study formulates novel sensitivity index i.e. nodal price of energy index (NPEI) to assist the location of sensitive buses for optimal placement of RES. Firstly, the proposed approach subjects power system to (N-1) contingency including both loss of generator and line outage. The NPEI is computed for every bus in various contingency conditions. The most severe contingency is identified based on highest value of sensitivity index in peak load period. The buses with highest values of NPEI is the optimal location for RES placement in the most critical contingency scenario. Secondly, the proposed approach focuses on efficient and cost-effective energy management by optimally scheduling disparate energy generation sources. The system incorporates pumped storage plant (PSP) based energy storage devices to effectively utilize wind and solar energy. The objective of this study is to minimize the total generation cost which includes the generation cost associated with conventional generators, its emission cost and valve-point loading effect, generation cost of RES, and the cost associated with energy supplied by PSP. The partial shading of PV modules is also implemented and its impact on system parameters are observed. The penetration of RES and energy storage effects system reliability hence, the proposed approach computes reliability indices expected energy not supplied (EENS) and loss of load expected (LOLE) for both presence and absence of RES and PSP. Finally, the proposed approach results in optimal placement of RES and optimal energy scheduling of disparate energy sources along with analyzing its effect on system reliability. The study is performed on IEEE 30 bus system.

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“…Tus, targeted DSM along with distributed generation (DG) can be an efective alternative of CM [10]. Under DSM, customers adjust their demands on the basis of awareness for energy conservation or by getting fnancial incentives [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Salp Swarm Algorithm Approach for Transmission Congestion Management

Agrawal¹,

Pandey²,

Srivastava³

et al. 2022

International Transactions on Electrical Energy Systems

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In the newly emerged electric supply industry, the profit maximizing tendency of market participants has developed the problem of transmission congestion as the most crucial issue. This paper proposes a multiobjective salp swarm algorithm (MOSSA) approach for transmission congestion management (CM), implementing demand side management activities. For this, demand response (DR) and distributed generation (DG) have been employed. For willingly reducing the demand, demand response has been called by providing appropriate financial incentives that supports in releasing the congestion over critical lines. Distributed generation implementing wind plant as renewable independent power producer (RIPP) has also been included in order to reduce the load curtailment of responsive customers to manage transmission congestion. The proposed incentive-based demand response and distributed generation approach of CM, has been framed with various strategies employing different thermal limits over transmission lines and has resulted into significant reduction in congestion and in-turn improvement of transmission reliability margin. Diversity has been obtained in multiobjective optimization by taking two and three objective functions, respectively (minimization of overall operational cost, CO2 emission, and line loading). The by-products of the proposed algorithm for multiobjective optimization are minimized demand reduction, optimum size, and location of DG. To examine the proposed approach, it has been implemented on IEEE 30-bus system and a bigger power system IEEE 118-bus system; as well as the proposed technique of MOSSA has been compared and found better than reported methods and two other meta heuristic algorithms (multiobjective modified sperm swarm optimization and multiobjective adoptive rat swarm optimization).

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Demand response based congestion management of power system with uncertain renewable resources

Cited by 17 publications

References 31 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

Efficient Energy Management and Reliability Assessment by Optimal Placement of Renewable Energy Sources with Pump Storage Plant

Multiobjective Salp Swarm Algorithm Approach for Transmission Congestion Management

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