Modelling for Composite Load Model Including Participation of Static and Dynamic Load

Saxena, Nitin Kumar; Kumar, Ashwani

doi:10.1007/978-3-030-34050-6_1

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…Load modelling plays a crucial role in power system studies. The load can be represented by static (polynomial (ZIP) or exponential type load model), dynamic, or composite models [30]. This paper's focus is on CVR planning, with an emphasis on employing static load models, namely polynomial (ZIP) or exponential types.…”

Section: Objective Functionmentioning

confidence: 99%

Dynamic investment planning of CVR implementation considering PEVs’ reactive power compensation capability

Alaei,

Latify

2024

IET Generation Trans & Dist

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Conservation voltage reduction (CVR) is a strategy that tries to save energy consumption by managing consumers’ voltage. On the other hand, enhancing reactive power compensation in the power system gives rise to CVR implementation more effectively. This paper addresses how the power system planner could encourage investment to establish the above‐mentioned topics. Here, a model for encouraging industrial loads to dynamically invest in implementing the CVR strategy over the planning horizon is presented. To make CVR implementation more efficient, investment in upgrading plug‐in electric vehicles (PEVs) chargers to be utilized as reactive power compensators is also considered. Industrial loads benefit from saving in their electricity bills and incentive payments that might be paid by utilities (if necessary). The objective function of the proposed planning model is to maximize the energy‐saving of industrial loads and to minimize incentive payment by electric utilities over the planning horizon. This objective is achieved subject to that the investment plan is economically feasible. Moreover, power system operation constraints in the planning horizon based on AC power flow equations and voltage‐dependent load models are considered. The proposed planning problem is modelled as a non‐linear optimization problem that can be solved by off‐the‐shelf software, for example, GAMS. The proposed model is applied to the Ontario transmission system. The numerical results show the proposed model's effectiveness in designing an investment plan for industrial loads to implement the CVR strategy and upgrade PEVs’ chargers.

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Section: Objective Functionmentioning

confidence: 99%

Dynamic investment planning of CVR implementation considering PEVs’ reactive power compensation capability

Alaei,

Latify

2024

IET Generation Trans & Dist

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“…The transfer function ΔQ/ΔV, which represents reactive power response to voltage changes, is important for composite loads in optimisation studies related to compensation of reactive power and voltage management. The reactive power response to voltage fluctuations for such composite loads is calculated by developing the mathematical model [22]. To adopt EVs on a larger scale, a dependable and sustainable charging infrastructure is very much essential.…”

Section: Introductionmentioning

confidence: 99%

“…Reference [22][23][24][25][26][27] highlight various loads' modelling based on their characteristics, CS placement and sizing to optimize the cost of CS. The effect of EVs on the distribution system and advantages of DGs are studied and the DGs are optimally placed in the distribution system.…”

Section: Introductionmentioning

confidence: 99%

A probabilistic approach on uncertainty modelling and their effect on the optimal operation of charging stations

K. K.,

N. S.,

Jadoun

2024

IET Generation Trans & Dist

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Uncertainty analysis deals with the fluctuations and unpredictability of the electrical power generated from renewable resources (RRs), such as solar PV and wind energy systems. This paper gives an insight into various techniques used for the uncertainty analysis and a probabilistic Monte Carlo Simulation is applied for modelling the uncertainties concerned with RRs and electric vehicle (EV) load in the MATLAB platform. The uncertainty associated with the price sensitivity of EV charging and the state of charge of EVs is taken as a prime factor for analysis in the present work. Despite the fluctuations and unpredictability of electricity generation and consumption, the considered system ensures that the total amount of electricity supplied by solar PV, wind and grid matches the total amount of electricity demanded by EV load. Rao‐1, Rao‐2 and Rao‐3 algorithms are applied in this work to optimize the operation cost of charging stations under uncertain conditions and without any uncertainties. The results obtained without uncertainties by Rao algorithms are compared with the existing particle swarm optimisation method. In the presence of uncertainties, Rao‐1 and Rao‐2 algorithms are compared with Rao‐3 and it is found that the Rao‐3 algorithm performed better.

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Role of compensators' hybrid participation for isolated wind-driven electrical system in presence of input and load uncertainties

Saxena¹,

Kumar

Gao

2021

Uncertainties in Modern Power Systems

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Modelling for Composite Load Model Including Participation of Static and Dynamic Load

Cited by 4 publications

References 21 publications

Dynamic investment planning of CVR implementation considering PEVs’ reactive power compensation capability

Dynamic investment planning of CVR implementation considering PEVs’ reactive power compensation capability

A probabilistic approach on uncertainty modelling and their effect on the optimal operation of charging stations

Role of compensators' hybrid participation for isolated wind-driven electrical system in presence of input and load uncertainties

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