Browsing by Author "Devender Singh"

Now showing 1 - 9 of 9

A modified current injection load flow method under different load model of EV for distribution system
(John Wiley and Sons Ltd, 2020) Bablesh K. Jha; Abhishek Kumar; Dharmendra K. Dheer; Devender Singh; Rakesh K. Misra
In this article, a modified single-phase current injection based load flow method for the distribution network with different load models of electric vehicle (EV) is proposed. The equations related to injected currents are non-linear and are represented in rectangular co-ordinates. The PQ and PV bus representations in load flow formulation are modified for the three different load models of EV including polynomial or ZIP load model (EV LM-I), voltage dependent load model (EV LM-II) and constant current load model (EV LM-III). In addition, a stochastic modelling of EV load and selection of candidate locations for DGs integration are also presented. The effect of the proposed EV load models in terms of real power loss index (ILP), reactive power loss index (ILQ), voltage profile index (IV D) and the MVA capacity index (IC) has been studied on IEEE 38-bus distribution system. Based on the values of ILP, ILQ, IV D and IC, best load model for EVs from among the load models EV LM-I, EV LM-II and EV LM-III is finally obtained. © 2019 John Wiley & Sons Ltd
A Nested-Iterative Newton-Raphson based Power Flow Formulation for Droop-based Islanded Microgrids
(Elsevier Ltd, 2020) Abhishek Kumar; Bablesh Kumar Jha; Dharmendra Kumar Dheer; Rakesh Kumar Misra; Devender Singh
In this paper, an iterative novel power flow technique is proposed to obtain the operating point of Droop Based Islanded Microgrid (DBIMG). The proposed technique considers system frequency as an additional variable to obtain the steady-state operating point of the system. To generalize the proposed technique, four operating modes of Distributed Generations (DGs) including droop control, isochronous, PV and PQ mode are considered. In this study, the formulated power flow problem consists of a set of non linear and linear power flow equations. To solve these set of equations, a Nested-Iterative Newton-Raphson algorithm is proposed. The proposed algorithm is implemented on several test systems including 6-bus, 22-bus, 38-bus, 69-bus, and 160-bus. To examine the robustness and effectiveness of the proposed algorithm, the power flow solutions obtained by implementing the proposed algorithm are compared with the power flow solutions obtained by implementing the existing Newton-Raphson algorithms including Modified Newton-Raphson (MNR), Newton Trust-Region (NTR) and time-domain simulator: PSCAD/EMTDC. The results show better efficiency and superior convergence of the proposed algorithm in comparison to the existing algorithms. © 2019 Elsevier B.V.
A Robustness Consideration in Continuous Time [K,KL] Sector for Nonlinear System
(Institute of Electrical and Electronics Engineers Inc., 2019) Ankit Sachan; Shyam Kamal; Devender Singh; Xiaogang Xiong
In this paper, we concerned to achieve an asymptotic stabilization of a generalized nonlinear system with significant uncertainties by rendering a relatively lesser amount of control. Here, a combined control consist of Hands-Off control and an adaptive sliding mode control is allowed to adjust the movement of the system state to the interior of $\mathcal {[K,KL]}$ sector and compensate the unknown disturbance, respectively. The adaptation methodology consists of a low-pass filter to filter-out the high-frequency component and searches for minimum possible value to cancel the effect of the unknown disturbance throughout the dynamical system. Finally, a design example is shown with the simulation results for $\mathcal {[K,KL]}$ sector design. © 2013 IEEE.
Coordinated effect of PHEVs with DGs on distribution network
(John Wiley and Sons Ltd, 2019) Bablesh Kumar Jha; Abhishek Kumar; Devender Singh; Rakesh Kumar Misra
In this paper, a base case of distribution system without PHEVs and DGs has been studied to evaluate system performance characteristics. Further, effect of introduction of PHEVs has been investigated in terms of system operating cost, losses, voltage profile, and load flattening. To improve these characteristics, introduction of DGs has been investigated by simulating different penetration level of PHEVs along with different demand response (DR) levels. It has been demonstrated that with the DG scheduling considering appropriate DR levels, the system operating cost, losses, voltage profile, and load flattening can be improved. The 24-hour DG scheduling is carried out to optimize the system cost, which is function of charging/discharging cost, losses, and cost of DGs power. A differential evolution (DE) search algorithm is used to optimize single objective weighted fitness function. IEEE 38-Bus test system is used for demonstration of the investigations. In case of lower-penetration levels, operating cost is significantly affected by the DR characteristics of a system. The method suggested can help local distribution companies (LDC) in optimally scheduling the DGs, in presence of PHEV, to achieve the minimum system cost, improved voltage profile, minimum losses, and improved load fattening. © 2018 John Wiley & Sons, Ltd.
Effect of voltage step constraint and load models in optimal location and size of distributed generation
(2013) Rajendra P. Payasi; Asheesh. K. Singh; Devender Singh
The distributed generation planning (DGP) in distribution system is affected with load models. Further, The size of distributed generation is also affected with voltage step constraints. In previous works, the effects of load models and voltage step constraint, in distributed generation planning (DGP), have not been studied together by the researchers so for. In this paper, voltage step constraint, along with usual constraints i.e. bus voltage limits and line capacity limits, and basic load models have been considered in DGP. The study has been carried out in 38 bus test system using incremental power flow and exhaustive search method. The results show that optimal location and size along with intake power from grid are significantly affected by voltage step constraint and load models. © 2013 IEEE.
Intelligent fuzzy rough set based feature selection using swarm algorithms with improved initialization
(IOS Press, 2019) Tarun Maini; Abhishek Kumar; Rakesh Kumar Misra; Devender Singh
This paper focuses on Fuzzy rough set, which is the fusion of fuzzy sets and rough sets theory for doing feature selection. For selecting the appropriate feature subset, swarm algorithms are used. The fitness function used here is Fuzzy Rough Dependency Measure. This paper demonstrates that by optimizing the fitness function, swarm algorithms are capable to select the best subset of features. Further, in this paper, an attempt has been made to improve the capability of the swarm based algorithms such as Intelligent Dynamic Swarm (IDS) and Particle Swarm Optimization (PSO) through modified initialization of solutions, for picking the appropriate features for the feature selection task. Improvement in the size of reducts and classification accuracy of these reducts are observed when initialization is done using the proposed method. Statistical t-tests have also been performed for the validation of the results. © 2019 - IOS Press and the authors. All rights reserved.
Optimal scheduling of PHEVs and D-BESSs in the presence of DGs in a distribution system
(Institution of Engineering and Technology, 2019) Amit Singh; Bablesh Kumar Jha; Devender Singh; Rakesh K. Misra
Optimisation of cost and load flattening for a distribution network is attempted in this work. The objective function is described in terms of energy cost, CO2 emissions, real power losses, and load flattening. The solution is envisaged in terms of hourly scheduling of distributed generations (DGs), distributed battery energy storage systems (D-BESSs), and plug-in hybrid electric vehicles (PHEVs). An investigation in the reformulation of the cost of energy is carried out to eliminate the solutions involving excessive charging and discharging of BESSs/D-BESSs and PHEVs. It is demonstrated that simultaneous optimisation of cost, CO2 emissions, real power losses, and load flattening cannot be effectively solved as a weighted sum objective function. An e-constraint method is applied to obtain the optimal scheduling to achieve cost optimisation, load flattening, and minimisation of CO2 emissions from the utility point of view. A case of decentralised multi-agent optimisation problem is also formulated and compared. It is observed that the combination of the scheduling of DGs, BESSs/D-BESSs, gridto-vehicle/vehicle-to-grid can successfully be used to significantly reduce the system peak demand along with system cost, losses and CO2 emissions. © The Institution of Engineering and Technology 2019.
Phase unbalance and PAR constrained optimal active and reactive power scheduling of Virtual Power Plants (VPPs)
(Elsevier Ltd, 2021) Bablesh Kumar Jha; Amit Singh; Abhishek Kumar; Rakesh Kumar Misra; Devender Singh
In near future, the integration of unknown and unpredictable quantity of Electric Vehicles (EVs) can violate reliable and quality power service of distribution system. In spite of that, ability of simultaneously regulate active and reactive power by Plug-in-Hybrid Electric Vehicles (PHEVs) in quick response time, without affecting the batteries can help to ensure reliable and quality power service in distribution system. This paper investigates the optimal active and reactive power scheduling of PHEVs and Distributed Generations (DGs) in Virtual Power Plants (VPPs), considering unbalance and Peak-to-Average Ratio (PAR) constraints. To compute stochastic model of PHEVs, we considers dynamic nature of driving pattern based on NHTS 2017 data. The proposed approach is implemented on IEEE-25 bus unbalanced distribution system. The developed planning and operational investigation of VPPs also presents dependencies of cost and losses in terms of Unbalance factor and PAR. © 2020 Elsevier Ltd
Smart home energy management system under false data injection attack
(John Wiley and Sons Ltd, 2020) Basant K. Sethi; Debottam Mukherjee; Devender Singh; Rakesh Kumar Misra; S.R. Mohanty
Modern smart home energy management system (SHEMS) is naturally prone to cyber attack, hence it demands cyber attack resilient scheduling schemes. Current scenario of SHEMS may result in increased charging and discharging cycles deteriorating the battery life. Therefore, demand scheduling formulations also need to cater the effect of battery degradation cost along with user comfort. The present work attempts to formulate a comprehensive scheduling problem in terms of energy cost minimization considering the battery degradation cost. Further, a cyber attack resilient scheduling model is proposed in this study. This article investigates the effect of demand scheduling on the life span of battery as well as the energy cost. Further, false data injection attack (FDIA) has been modeled using machine learning techniques, and its effects on the scheduling has also been incorporated in the objective function. Scenario tree based stochastic bill generation has been also formulated to develop an FDIA resilient scheduling. Optimisation results of the study have established that the resulting formulation is robust against FDI attacks. © 2020 John Wiley & Sons Ltd