Bio: Nikhil Korada is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Photovoltaic system & Stand-alone power system. The author has an hindex of 1, co-authored 2 publications receiving 75 citations.
TL;DR: An appropriate grid adaptive power management strategy (GA-PMS) is formulated to generate current references for RES, ESS, and microgrid-connected converters and includes seamless microgrid operation under abnormal conditions, priority-based load shedding, and ensuring power quality standards at the local bus.
Abstract: The penetration of growing microgrid systems within the ac distribution network is leading to several challenges to have a safe and reliable operation of the power system. For the utility system, it is mandatory to maintain the voltage and frequency within the prescribed limits at the local bus under diverse conditions of the renewable energy sources (RESs), loads, and grid. With these conditions, the need for energy storage system (ESS) becomes extremely important for effective operation of critical and frequency sensitive loads. The vital role of ESS based on dc-bus regulation and monitoring of grid frequency in the microgrid is a challenging task and needs to be investigated in detail. Therefore, in this paper, the storage and microgrid are scheduled to work in a grid supportive manner. Also, these ESSs need to be operated within its safe state of charge limits. Hence, based on all the above constraints, an appropriate grid adaptive power management strategy (GA-PMS) is formulated to generate current references for RES, ESS, and microgrid-connected converters. Furthermore, this algorithm includes seamless microgrid operation under abnormal conditions, priority-based load shedding, and ensuring power quality standards at the local bus. The performance of proposed GA-PMS is tested and validated through the simulation and experimental studies.
TL;DR: In this paper , the authors proposed a new space vector based PWM (240CPWM) for grid-connected transformerless voltage source inverters (VSIs), which can attain much superior performance by avoiding the zero states.
Abstract: Transformerless voltage source inverters (VSIs) are one of the popular topologies for photovoltaic (PV) grid-connected applications due to the lowest component count and simple design. Because of the absence of galvanic isolation in such systems, problem of electromagnetic interference (EMI) due to high leakage current is highly pronounced. Recently various reduced common mode voltage (CMV) PWM (RCMV-PWM) methods which address these issues of CMV, and leakage current have been proposed. These schemes typically function at the expense of increased total harmonic distortion (THD), higher switching loss, high DC link current stress along with limited modulation index range. In this work, 240$^\circ$ clamped PWM (240CPWM) is selected as an ideal candidate for grid connected VSIs in terms of all round performance of switching loss, THD, DC link current stress, CMV and leakage current. 240CPWM is a relatively new space vector based PWM method which can attain much superior performance by avoiding the zero states. After a brief overview of the 240CPWM concept, the paper provides a detailed comparison of 240CPWM with conventional space vector PWM (CSVPWM) and discontinuous PWM (DPWM1) methods in terms of each of the above metrics. A 3-phase 208 V 3 kW silicon IGBT based hardware prototype is built to validate the performance of 240CPWM and compared with other popular schemes under grid-connected mode. Experimental results show a 66.7% reduction in the peak CMV and 50% reduction in leakage current with the proposed scheme as compared to CSVPWM. Also, THD, DC link current stress and inverter switching loss are greatly reduced as an added advantage using the proposed method. A new, combined performance index is proposed to compare the performance of different PWM schemes, and it is shown that the 240CPWM achieves the best value for this index among the PWM methods studied.
TL;DR: In this paper , the performance of a relatively new pulsewidth modulation (PWM) method i.e., 240$^\circ$-clamped space vector PWM (240CPWM), in three-phase grid-connected photovoltaic (PV) converters under various grid voltage conditions was evaluated.
Abstract: This article evaluates the performance of a relatively new pulsewidth modulation (PWM) method i.e., 240$^\circ$-clamped space vector PWM (240CPWM), in three-phase grid-connected photovoltaic (PV) converters under various grid voltage conditions. 240CPWM is a minimum switching loss PWM method that reduces the switching loss by 85% at unity power factor and has better total harmonic distortion (THD) as compared to conventional space vector PWM. A unique six-pulse dynamically varying dc-link voltage is required for 240CPWM. Typically, a three-phase grid-connected PV system consists of a dc–dc stage followed by a dc–ac stage. In this article, the dc–dc stage is operated in closed-loop control to shape the dynamic dc-link voltage required for 240CPWM. The dc–ac stage is operated in the current control mode using a proportional–integral controller along with a harmonic compensator to ensure sinusoidal grid currents along with maximum power point tracking. The modulation index of the dc–ac stage is uncontrolled and fixed at the maximum value, and the primary control mechanism changes the magnitude, phase, and wave shape of the dc-link voltage. The coordinated control of dc–dc and dc–ac stages is ensured for better dynamic performance and grid support functions. Finally, the performance of the grid-connected PV converter with 240CPWM is validated using a three-phase 3-kW 208-V hardware prototype under nonunity power factors, voltage unbalance, and voltage sag/swell conditions for the first time. The implemented control with 240CPWM achieves smooth operation under nonunity power factor and grid voltage disturbance conditions with THD as low as 3.5% and peak combined efficiency of dc–dc and dc–ac stages as 96.4%.
••01 Nov 2015
TL;DR: A control algorithm is proposed to operate a BLDC drive on PV and and a hybrid energy storage system (HESS) and the efficacy of this algorithm is confirmed to obtain desired drive performance under various disturbances in PV and HESS.
Abstract: There has been an increasing interest in the development of energy-efficient appliances using renewable energy sources. This paper deals with a Photovoltaic (PV) powered BLDC drive as a sustainable solution to air conditioning compressor drive. Compressor of an air conditioner (AC) accounts for 95% of its total power consumption. The bottle necks of operating a compressor drive on PV are: supplying high starting current, effect of intermittent nature of PV on drive performace, effective power management and stable operation in standalone mode. In this work, a control algorithm is proposed to operate a BLDC drive on PV and and a hybrid energy storage system (HESS). HESS is employed to smoothen the intermittent nature of PV and a HESS SOC control algorithm is formulated. The control algorithm limits the drive starting/transient current to 1.5 times the rated current. A virtual damping of DC link voltage is employed to make the system stable. The simulation results confirm the efficacy of control algorithm to obtain desired drive performance under various disturbances in PV and HESS.
TL;DR: In this article , the authors proposed a generalized design methodology of a robust controller to mitigate the impact of system uncertainty on controller stability and performance which includes steady-state error, disturbance rejection, high-frequency noise attenuation and speed of dynamic response.
Abstract: This paper proposes a generalized design methodology of a robust controller to mitigate the impact of system uncertainty on controller stability and performance which includes steady-state error, disturbance rejection, high-frequency noise attenuation and speed of dynamic response. The first step is to select the weighting functions that bound the transfer functions for the entire range of uncertainty. The second step is to form mathematical representation for both robust stability and robust performance. The third step is to conduct the robust H-infinity controller synthesis to generate the full-order controller, and then carry out order reduction and recheck of the design objectives. The last step is to select an optimized controller based on the multi-dimensional Pareto Front algorithm. The proposed method has been firstly applied to the current controller design of a grid-connected inverter with variable grid impedance, and secondly to the voltage controller design of an LLC resonant DC/DC converter with variable resonant capacitance. The results indicate that the selected optimal H-infinity controller has an overall more satisfactory performance in terms of stability, steady-state error, disturbance/noise rejection capability and dynamic performance, compared with conventional PI and PR controllers when there is a large variation of system parameters.
TL;DR: A new energy management scheme is proposed for the grid connected hybrid energy storage with the battery and the supercapacitor under different operating modes and the effectiveness of the proposed method is validated by both simulation and experimental studies.
Abstract: DC-coupled microgrids are simple as they do not require any synchronization when integrating different distributed energy generations. However, the control and energy management strategy between the renewable energy sources and the energy storages under different operating modes is a challenging task. In this paper, a new energy management scheme is proposed for the grid connected hybrid energy storage with the battery and the supercapacitor under different operating modes. The main advantages of the proposed energy management scheme are effective power sharing between the different energy storage systems, faster dc link voltage regulation to generation and load disturbances, dynamic power sharing between the battery and the grid based on the battery state of charge, reduced rate of charge/discharge of battery current during steady state and transient power fluctuations, improved power quality features in ac grid and seamless mode transitions. The effectiveness of the proposed method is validated by both simulation and experimental studies.
TL;DR: Through numerical simulation case studies, it is demonstrated that the proposed BEMS is capable of achieving the following: reduction in DGs’ operating hours, reduction in PV power fluctuations, and concurrent management of multiple batteries of different characteristics and extension of battery lifetime by controlling battery charge and discharge rate.
Abstract: Using solar photovoltaics (PV) to help a microgrid (MG) operator for cost reduction may not be a straightforward problem due to the intermittent nature of PV power generation and unpredictable load demands. One potential way to address this challenge is to use batteries that can store the surplus PV energy whenever possible and supply the energy back to the MG when needed. In this context, this paper proposes a battery energy management system (BEMS) for an MG, in which PVs and diesel generators (DGs) are the primary sources of electricity. The novelty of the proposed BEMS lies within the energy management of multiple types of batteries’ characteristics and the reduction of DGs’ operating hours simultaneously. Furthermore, the proposed BEMS also takes into account different characteristics of the batteries when controlling the charging and discharging decision to extend the battery lifetime. Real-world data of MG load and PV power generations are used to verify the effectiveness of the proposed BEMS. Through numerical simulation case studies, it is demonstrated that the proposed BEMS is capable of achieving the following: reduction in DGs’ operating hours, reduction in PV power fluctuations, and concurrent management of multiple batteries of different characteristics and extension of battery lifetime by controlling battery charge and discharge rate.
TL;DR: This article attempts to bring the numerous control strategies proposed in the literature at one place on various control techniques implemented for HESS including their features, limitations and real-time applications.
Abstract: The ever increasing trend of renewable energy sources (RES) into the power system has increased the uncertainty in the operation and control of power system. The vulnerability of RES towards the unforeseeable variation of meteorological conditions demands additional resources to support. In such instance, energy storage systems (ESS) are inevitable as they are one among the various resources to support RES penetration. However, ESS has limited ability to fulfil all the requirements of a certain application. So, hybridization of multiple ESS to form a composite ESS is a potential solution. While integrating these different ESS, their power sharing control plays a crucial role to exploit the complementary characteristics of each other. Therefore, this article attempts to bring the numerous control strategies proposed in the literature at one place. Various control techniques implemented for HESS are critically reviewed and the notable observations are tabulated for better insights. Furthermore, the control techniques are classified into broad categories and they are briefly discussed with their limitations. From the carried-out analysis, the challenges faced towards the implementation of HESS for standalone and grid connected microgrid systems are presented. Finally, the future directions are laid out for the researchers to carry out the research and implementation of HESS technologies. Overall, this article would serve as a thorough guide on various control techniques implemented for HESS including their features, limitations and real-time applications.
TL;DR: In this paper, a hybrid evolutionary algorithm, hybrid grey wolf optimizer-particle swarm optimization algorithm, is also proposed to solve the proposed MOEM and the accuracy of the proposed algorithm is evaluated on IEEE 84-bus standard distribution system.
Abstract: This paper introduces a novel approach for optimal operation of distribution networks at the presence of distributed generation resources and battery energy storage system. Modern power distribution networks must operate not only at the most economical way but also at a reasonable level of system reliability. Toward this end a special attention has been paid to reliability assessment in which turns the proposed problem into a multiobjective energy management (MOEM). Energy not supplied, a prominent reliability index, is considered as an objective function beside the operation cost. A hybrid evolutionary algorithm, hybrid grey wolf optimizer-particle swarm optimization algorithm, is also proposed to solve the proposed MOEM. Accuracy of the proposed algorithm is evaluated on IEEE 84-bus standard distribution system. Obtained results are compared with those available in literatures to prove the supremacy of the proposed algorithm. Furthermore, a benefit analysis has been done to assess the associated cost of the photovoltaic installment.
TL;DR: In this article, a hybrid model consisting of neural networks and wavelet transform is proposed to forecast the incoming solar energy and estimate the power generated from solar photovoltaic (SPV) systems.
Abstract: The growing penetration level of solar photovoltaic technology is becoming a challenging task in the smart energy management systems. The power generated from the solar photovoltaic (SPV) systems is intermittent. Therefore, it is imperative to best predict the incoming solar energy and estimate the power generated from SPV systems. In this paper, the solar energy forecasting is performed using a hybrid model consisting of neural networks and wavelet transform. The performance of the proposed model is evaluated based on both root mean square error (RMSE) and mean absolute error (MAE). To validate the proposed method the above results are compared with other existing approaches like ANN and found better within desired limits. There is a pumped hydro storage (PHS) in the configuration under study to meet the grid requirements. In order to obtain more accurate and practical results, demand response (DR) program has been also integrated in the formulation of the problem. An adequacy analysis is also carried out under various consumer flexibility scenarios. Performance analysis of the proposed energy management system has been done using MATLAB/Simulink platform, and the same is validated on 5 kW SPV system. Further, the proposed model can be applied to large-scale systems.