Sarthak Jain

Bio: Sarthak Jain is an academic researcher from Maharaja Agrasen Institute of Technology. The author has contributed to research in topics: Photovoltaic system & AC power. The author has an hindex of 6, co-authored 21 publications receiving 264 citations. Previous affiliations of Sarthak Jain include Renesas Electronics & Kansas State University.

Raspberry Pi based interactive home automation system through E-mail

Abstract: Home automation is becoming more and more popular day by day due to its numerous advantages. This can be achieved by local networking or by remote control. This paper aims at designing a basic home automation application on Raspberry Pi through reading the subject of E-mail and the algorithm for the same has been developed in python environment which is the default programming environment provided by Raspberry Pi. Results show the efficient implementation of proposed algorithm for home automation. LEDs were used to indicate the switching action.

Autotuning Technique for the Cost Function Weight Factors in Model Predictive Control for Power Electronic Interfaces

Abstract: This paper presents an autotuning technique for the online selection of the cost function weight factors in model predictive control (MPC) The weight factors in the cost function with multiple control objectives directly affect the performance and robustness of the MPC The proposed method in this paper determines the optimum weight factors of the cost function for each sampling time; the optimization of the weight factors is done based on the prediction of the absolute tracking error of the control objectives and the corresponding constraints The proposed method eliminates the need of the trial-and-error approach to determine a fixed weight factor in the cost function The application considered is a capacitor-less static synchronous compensator based on the MPC of a direct matrix converter This technique compensates lagging power factor loads using inductive energy storage elements instead of electrolytic capacitors The result demonstrates that the proposed autotuning approach of cost function weights makes the control algorithm robust to parameter variation and other uncertainties in the system The proposed capacitor-less reactive power compensator based on the autotuned MPC cost function weight factor is verified experimentally

Decoupled Active and Reactive Power Predictive Control for PV Applications Using a Grid-Tied Quasi-Z-Source Inverter

Abstract: This paper proposes a predictive power control algorithm that decouples active and reactive power for grid integration of photovoltaic (PV) systems using a quasi-Z-source inverter. This is important to meet the emerging smart inverter requirements for grid interconnection. The proposed controller uses model predictive control framework to ensure that the maximum available power is harvested from the PV array and that the active and reactive power injected into the grid is controlled to compensate reactive power required by local loads and as need to ensure stable operation of the grid at the point of common coupling. Thus, a power electronics interface is proposed to integrate the PV array to the grid and to work as a reactive power compensator simultaneously. A robust technique is proposed to regulate the impedance network voltage and current according to the maximum operating point of PV panels and grid voltage/current requirements. The proposed controller features a simple structure suitable for practical implementation, fast-dynamic response under changing sky condition, and negligible tracking error in steady state for decoupled active and reactive power control in a typical distributed generation systems. The performance of the proposed controller is verified experimentally; the grid-side power quality analysis is provided and evaluated according to IEEE-519 standard.

Computationally Efficient Distributed Predictive Controller for Cascaded Multilevel Impedance Source Inverter With LVRT Capability

Abstract: This paper presents a decoupled active and reactive power control scheme for grid-tied quasi-impedance source cascaded multilevel inverter (qZS-CMI). For photovoltaic (PV) applications, the proposed control scheme is based on an enhanced finite-set model predictive control (MPC) to harvest the desired active power from the PV modules with the ability to provide the ancillary services for the grid. The proposed control scheme has two modes of operation: normal grid mode and low voltage ride through (LVRT) mode. In normal grid mode, the controller commands the qZS-CMI to operate at the global maximum power point (MPP). The proposed technique regulates the impedance network’s current and voltage according to the MPP of PV strings and grid current/voltage requirements. In LVRT mode, the controller commands the qZS-CMI to provide the required reactive power to the grid during voltage sags as an ancillary service from the inverter as imposed by the grid codes. The main features of the proposed system include the global MPP operation during normal grid condition, LVRT capability during a grid voltage sag, mitigation of the PV modules mismatch effect on overall energy harvesting, seamless transition between a normal grid and LVRT modes of operation, and an efficient predictive controller that exploits the model redundancies in the control objectives. Several real-time experiments are conducted to verify the system performance with transients in both the solar irradiance and the grid voltage.

Autonomous Model Predictive Controlled Smart Inverter With Proactive Grid Fault Ride-Through Capability

Abstract: This article presents an autonomous model predictive controlled smart photovoltaic (PV) inverter with proactive grid fault-ride through capability. The proposed smart inverter control features decoupled active and reactive power. It can seamlessly switch between the anticipated modes of operation based on grid condition or grid operator command. The smart inverter autonomously adjusts its active and reactive power set-points according to the grid condition, it operates in maximum power point tracking (MPPT) and low voltage ride through (LVRT) modes in normal grid and faulty grid condition modes, respectively. The proposed novel autonomous model predictive control (AMPC) scheme is leveraged to enhance the operation of the smart inverter. The AMPC includes online weight factor auto-tuning and control objective normalization to eliminate the required trial-and-error weight factor design stage in conventional model predictive control. This feature is particularly beneficial to the dual-mode smart inverter operation. The performance of the proposed grid-tied smart inverter based on the AMPC is verified experimentally. The results demonstrate that the proposed AMPC-based smart inverter features robust grid fault detection, autonomous adjustment of active and reactive power set-points, seamless transition between modes of operation, and elimination of controller tuning effort.

A Survey on Smart Grid CommunicationInfrastructures: Motivations, Requirements andChallenges

Abstract: A communication infrastructure is an essential part to the success of the emerging smart grid. A scalable and pervasive communication infrastructure is crucial in both construction and operation of a smart grid. In this paper, we present the background and motivation of communication infrastructures in smart grid systems. We also summarize major requirements that smart grid communications must meet. From the experience of several industrial trials on smart grid with communication infrastructures, we expect that the traditional carbon fuel based power plants can cooperate with emerging distributed renewable energy such as wind, solar, etc, to reduce the carbon fuel consumption and consequent green house gas such as carbon dioxide emission. The consumers can minimize their expense on energy by adjusting their intelligent home appliance operations to avoid the peak hours and utilize the renewable energy instead. We further explore the challenges for a communication infrastructure as the part of a complex smart grid system. Since a smart grid system might have over millions of consumers and devices, the demand of its reliability and security is extremely critical. Through a communication infrastructure, a smart grid can improve power reliability and quality to eliminate electricity blackout. Security is a challenging issue since the on-going smart grid systems facing increasing vulnerabilities as more and more automation, remote monitoring/controlling and supervision entities are interconnected.

IoT based monitoring and control system for home automation

Abstract: The project proposes an efficient implementation for IoT (Internet of Things) used for monitoring and controlling the home appliances via World Wide Web. Home automation system uses the portable devices as a user interface. They can communicate with home automation network through an Internet gateway, by means of low power communication protocols like Zigbee, Wi-Fi etc. This project aims at controlling home appliances via Smartphone using Wi-Fi as communication protocol and raspberry pi as server system. The user here will move directly with the system through a web-based interface over the web, whereas home appliances like lights, fan and door lock are remotely controlled through easy website. An extra feature that enhances the facet of protection from fireplace accidents is its capability of sleuthing the smoke in order that within the event of any fireplace, associates an alerting message and an image is sent to Smartphone. The server will be interfaced with relay hardware circuits that control the appliances running at home. The communication with server allows the user to select the appropriate device. The communication with server permits the user to pick out the acceptable device. The server communicates with the corresponding relays. If the web affiliation is down or the server isn't up, the embedded system board still will manage and operate the appliances domestically. By this we provide a climbable and price effective Home Automation system.

Model Predictive Control of Power Electronic Systems: Methods, Results, and Challenges

Abstract: Model predictive control (MPC) has established itself as a promising control methodology in power electronics. This survey paper highlights the most relevant MPC techniques for power electronic systems. These can be classified into two major groups, namely, MPC without modulator, referred to as direct MPC, and MPC with a subsequent modulation stage, known as indirect MPC. Design choices, and parameters that affect the system performance, closed-loop stability, and controller robustness are discussed. Moreover, solvers, and control platforms that can be employed for the real-time implementation of MPC algorithms are presented. Finally, the MPC schemes in question are assessed, among others, in terms of design, and computational complexity, along with their performance, and applicability depending on the power electronic system at hand.

Hybrid PV-Wind Micro-Grid Development Using Quasi-Z-Source Inverter Modeling and Control –Experimental Investigation

Abstract: This research work deals with the modeling and control of a hybrid photovoltaic (PV)-Wind micro-grid using Quasi Z-source inverter (QZsi). This inverter has major benefits as it provides better buck/boost characteristics, can regulate the phase angle output, has less harmonic contents, does not require the filter and has high power performance characteristics over the conventional inverter. A single ended primary inductance converter (SEPIC) module used as DC-DC switched power apparatus is employed for maximum power point tracking (MPPT) functions which provide high voltage gain throughout the process. Moreover, a modified power ratio variable step (MPRVS) based perturb & observe (P&O) method has been proposed, as part of the PV MPPT action, which forces the operating point close to the maximum power point (MPP). The proposed controller effectively correlates with the hybrid PV, Wind and battery system and provides integration of distributed generation (DG) with loads under varying operating conditions. The proposed standalone micro grid system is applicable specifically in rural places. The dSPACE real-time hardware platform has been employed to test the proposed micro grid system under varying wind speed, solar irradiation, load cutting and removing conditions etc. The experimental results based on a real-time digital platform, under dynamic conditions, justify the performance of a hybrid PV-Wind micro-grid with Quasi Z-Source inverter topology.