Projects/Theses
1- Plug-and-Play Microgrid Test Bed – Funded by the Department of Defense, Office of Naval Research (DoD-ONR) (2016-2019)
This project aims to expand a successfully implemented microgrid test bed prototype (developed 2014) to a Laboratory-Scale Plug-and-Play Microgrid Test Bed. The system would offer students and faculty a safe, user-friendly platform to easily integrate new devices, test and validate innovative algorithms to further the understanding of the emerging smart grid system. Capacity of the test bed would be increased from 22kW to 45kW with the addition of renewable resources including a fuel cell system, wind power emulator, photovoltaic emulator, and additional storage facilities. The test bed will be endowed with a highly flexible data communication structure by using AMIs, relays, PLCs and controllers capable of wireless and wired communication, with diverse protocols. An equipment-to-human interface will provide safety for users and simplify the process for plugging hardware or software for testing into the test bed. This will enable researchers to use time efficiently by focusing on the intellectual aspects of the work, rather than time-consuming mechanical process of customization and integration of new systems into the test bed.
2- Decentralized Control of Modular Multi-Level Converters in Photovoltaic Systems, Institute of Energy and Environment, Penn State, (2018-2019)
Renewable energy resources (e.g. solar or wind) provide economic and environmental benefits for energy generation systems and are the best alternatives to conquer global warming issues. The goal of this project is to incorporate the novel application of Modular Multi-level Converters (MMC) to solar photovoltaic modules with energy storage devices to increase the efficiency, reliability, and value of the overall system. The new converter configuration achieves these objectives by enabling sub-module maximum power point tracking, integrated energy storage, and small transformers to reduce the voltage rating of the system. The performance of the proposed technology will be tested first through simulation, and then verified through a laboratory-scale experiment.
3- HARDWARE IMPLEMENTATION OF MICROGRID TEST BED
Joyer Benedict Lobo, MSEE, May 2015
Peter Idowu, Ph.D., P.E. (Thesis Advisor), Seth Wolpert, Ph.D., Scott Van Tonningen, Ph.D., Arnold Offner
Abstract – The ever increasing concerns of environmental pollution due to burning of fuels in power plants, have ushered in the utilization of distributed renewable energy resources which include solar, wind and other renewable sources of energy. In order to address this issue, the concept of Microgrid is introduced as a strategy to integrate renewable energy resource from various locations with the existing power system. Microgrids could be characterized as a group of interconnected loads and distributed energy resources (DER) with clearly defined electrical boundaries that acts as a single controllable entity with respect to the grid and can connect and disconnect from the grid to enable it to operate in both grid connected or island mode. The coordinated operation and control of DER sources together with storage devices, such as batteries, and controllable loads are central to the concept of microgrids. From the grid’s point of view, a microgrid can be regarded as a controlled entity within the power system that can be operated as a single aggregated load and from a customer’s point of view, microgrids are similar to traditional LV distribution networks that provide their electricity needs, but in addition, enhance local reliability, reduce emissions, improve power quality by supporting voltage and reducing voltage dips, and potentially lower costs of energy supply.
This research focuses on the hardware implementation of a laboratory scale microgrid test bed. The microgrid test bed is based on the specifications of IEEE 1547, which is a standard for incorporating distributed resources with the electric power system. Important features include voltage and frequency control when it operates in an island mode and when in a grid connected mode.
This microgrid is a plug and play test bed, which includes features like photovoltaic system (emulator), distributed control, industrial grade controllers, numerical relays, smart meters, bi-directional converters, and battery storage system, various static and dynamic loads and visualization software.
The objective of this project is to provide a test bed on which several emerging technologies in a microgrid environment could be tested and implemented. This test bed would provide a platform for carrying out research in studying the effects of integrating distributed generation in a microgrid, studying the different behavior of the microgrid at instances when it is connected to the utility and also when it is operating independently.
4- MULTI-AGENT BASED INTELLIGENT DISTRIBUTED CONTROL OF A HARDWARE-IN-THE-LOOP MICROGRID TEST-BED
Ameya Pradeep Chandrayan, MSEE, May 2015
Peter Idowu, Ph.D., P.E. (Thesis Advisor), Scott Van Tonningen, Ph.D., Seth Wolpert, Ph.D., Jeremy J Blum, Ph.D., Arnold Offner
Abstract- The structure of conventional electric power systems is changing its course from few centralized entities to numerous distributed energy systems, leading to technological challenges in three key aspects – sustainability, flexibility, and reliability. Penetration of renewable energy resources into the power system seems to magnify these challenges, and requires tremendous efforts to develop new control and protection methodologies, and market policies. Various interest groups including the government, electric utilities, academic and research institutions, as well as consumers are actively working towards the goal of a new intelligent grid – ‘smart grid’. This research focuses on the development of an operation and control scheme for a laboratory-scale hardware-in-the-loop microgrid system. The main features of this microgrid system include integrated renewable energy systems, battery storage, smart loads to realize demand-side energy management for various load patterns, advanced digital relays, as well as smart energy metering devices interfaced through various communication channels and protocols. Conventional generating units synchronized to an AC bus are coupled to the energy storage and the PV system through a DC bus. In real-life microgrid systems, various synchronous, asynchronous and static sources of power generation are dispersed geographically but relatively close to the demand side. An implementation of conventional power grid control and operation methods would presumably demand very high speed central processing platforms to perform extensive computations required for such a dispersed system. On the other hand, distributed control methods allocate these number crunching operations to asynchronous and autonomous control platforms, which operate in harmony to provide reliability, flexibility and resiliency in the microgrid environment. Therefore, the distributed approach for control using Multi-Agent System (MAS) concepts becomes the primary focus of this research. Various agents in the MAS platform offer advantages of being autonomous or self-organized, social, and pro-active as opposed to the existing distributed control systems. The framework for MAS is designed using Java Agent DEvelopment (JADE), a FIPAstandard compliant and open source java based platform. The need for inter-operability between different vendors is also arising as a result of growing activities and interactions between customers, market operators and utilities. The OPC (OLE for Process Control) Classic specifications, inherited from Object Linking and Embedding (OLE) – a proprietary technology developed by Microsoft, offer a complete range of solutions for process data access (DA), alarms & events (A&E), and historical data access (HDA) from different proprietary PLC and SCADA systems. In this research, the OPC DA (Data Access) Server is employed to act as an interface between PLC systems tied to the microgrid hardware layer and open source JADE platform which resides on the computer platform.
5- DISTRIBUTED CONTROL OF A SMART GRID NETWORK USING IEC 61499
Srikrishnan Jagannathan, MSEE, May 2015
Peter Idowu, Ph.D., P.E. (Thesis Advisor), Scott Van Tonningen, Ph.D., Wolfram Bettermann, Ph.D.
Abstract – Smart grid automation, in its preliminary and evolving state is achieved through centralized control, where a central control system monitors the entire grid automation and communications. These systems are more commonly known as SCADA systems which are essentially centralized in nature. SCADA systems are implemented using large software programs that are custom developed based on the application and are difficult to reuse for other applications. Modern control systems require flexibility for the purpose of advanced automation. To achieve this high level of flexibility in these systems a new software technology is required that is based on the interaction of distributed objects and that aims at decentralizing control.
The IEC 61499 is a novel method of software development that enables modeling control applications in a distributed manner. The standard presents guidelines for automation protocol in various applications ranging from industrial to smart grid. The IEC 61499 standard defines a distributed model for splitting different parts of an automation process and complex control into functional modules called function blocks (FB). These function blocks can be distributed and controlled across multiple controllers. The function block is a software unit that encapsulates some behavior and is hardware independent. The advantage of using function blocks is that it provides a method of graphical design of the system and also an easy way of distribution of functions in automation processes. Use of FBs makes the device control open and can be reconfigured more easily. End-users can modify the firmware of their devices based on changing technology and still able to use the same software to program the FBs. This enables the devices to adapt to changes in the grid.
The objective of this research is to highlight and demonstrate the benefits of microgrid generation through an innovative economic dispatch application implemented in IEC 61499. The contribution of this research is the use of function block concept to implement an economic dispatch application considering Levelized Cost of Energy, the availability of Distributed Generators and the load forecast to balance loads. The Levelized Cost of Energy has been calculated based on studies conducted by the Energy Information Administration (EIA). Previous work in this field has been to perform load balancing using Function Blocks with a focus only on the availability, not the economic aspect. The economic modeling of renewable energy systems is implemented in the economic dispatch application in combination with a load forecasting model for each load. A saving in cost of energy production is expected to be achieved through the implementation of different test behaviors. Hence the effectiveness of each behavior is depicted by comparing the power supplied by the utility under the different applications and by comparing the cost of energy production of each of the generating sources for a single day. This cost value can help policy makers in deciding laws for interoperation of different utilities.
6- INDUCTION MOTOR FAULT CLASSIFICATION USING NOVEL PCA, SVM, AND HYBRID ANN
Mohamed Nadeem Aslam, MSEE, August 2015
Peter Idowu, Ph.D., P.E. (Thesis Advisor), Seth Wolpert, Ph.D., Scott Van Tonningen, Ph.D.
Abstract –Induction motors have a long history of applications in wide ranging environments and have a proven track record in climate control applications, industrial processes, traction and in various consumer appliances. They are robust, cost-effective, efficient, and amenable to performance control with the availability of advanced drive systems. Due to the ever-expanding share of the application base, more focus are being placed on preventive and predictive maintenance, and early diagnosis of motor faults that ultimately lead to equipment or process downtime and economic repercussions. In this work, three different fault diagnosis algorithms using techniques such as Principal Component Analysis (PCA), Support Vector Machines (SVM) and Artificial Neural Networks (ANN) is presented with simulation results. Principal Component Analysis (PCA) based algorithm analyzes the three-phase current signal, which obtained from the sensors and stored in the host computer, to detect the fault. The current signal processed by the PCA based algorithm are given as input to the SVM and ANN based algorithms that analyze the data and classify the motors into five categories: Healthy, Air Gap Eccentricity (AGE), Bearing Failure (BF), Broken Rotor Bars (BRB), and Damaged Stator Slots (DSS). Through simulation in Matlab, the fault diagnosis and classification system proved to have a good ability to detect and classify faults in an induction motor.
Industries have utilized customized hardware tools that tend to be very expensive to diagnose these faults. This work also attempts to build a low cost, non-invasive induction motor fault diagnostic tool using the classical Fast Fourier Transform (FFT) analysis of motor current signature. The core of this tool is a Field Programmable Gate Array (FPGA) processor. The FPGA is programmed to perform FFT of the time domain current signal that is then analyzed to detect the fault. FPGAs are an appropriate choice as they are available at cheap prices and have flexible reconfigurable properties. This property makes FPGAs more adaptable in experiments where different scenarios have to be implemented at different times. They also have higher computing speed than the general-purpose computer based software simulation tools.
7- EFFECT OF WIRELESS MESH NETWORK PARAMTERS ON SMART GRID MONITORING AND CONTROL
Lucas McCoy, MSEE, December 2014
Peter Idowu, Ph.D., P.E. (Thesis Advisor), Seth Wolpert, Ph.D., Scott Van Tonningen, Ph.D.
Abstract –As the power grid transforms from a unidirectional flow of power to a bidirectional flow of power and data, the need to deploy a fast, reliable, and expandable communications network will be one of the biggest challenges faced by utility companies. The communications network must be capable of supporting the many requirements of a smart grid as set forth by the United States Department of Energy’s 2010 Smart Grid System Report (dynamic pricing, real-time system operations data sharing, load participation, distributed generation, grid-responsive demand-side equipment, advanced metering, and renewable resources). This research will focus specifically on evaluating a wireless mesh network in regards to the impact of network characteristics on power control algorithms such as power flow. This research will establish why a wireless mesh network is a reasonable communications network for use in the distribution level of the power grid, define a model for the network based on the characteristics of the radios, and evaluate the impact of the modeled network on power control systems. The development of such a model is crucial in allowing power utility companies to deploy networks that can provide communications capable of maintaining control efficiency and stability while also minimizing deployment cost.
8- MULTI AGENT SYSTEM-BASED SIMULATION OF A LABORATORY-SCALE MICROGRID
Le Chen, MSEE, August 2014
Peter Idowu, Ph.D., P.E. (Thesis Advisor), Aldo Morales, Ph.D., Seth Wolpert, Ph.D., Mohammad Tofighi, Ph.D.
Abstract -The Multi-Agent-System (MAS) technology has many desirable attributes such as autonomy, sociality, reactivity and pro-activity. It is widely accepted as the technology platform for implementing effective and efficient management and automation processes within a microgrid environment. This paper proposes an implementation of a microgrid simulation utilizing Matlab and a MAS software program. The MAS software is implemented with the aid of the Java Agent Development Framework (JADE) middleware platform. The three intelligent agents are: Controller agent, Distributed Energy Resource (DER) agent and Load agent. The Controller agent monitors network processes, performs critical control task such as network reconfiguration and it is also capable of detecting network anomaly. The DER agent stores the associated energy resources information, monitors and controls the DER power levels. Finally, the Load agent stores information about the users and loads such as power consumption and the priority status of the load. Both DER and Load agents are able to interact and respond to Controller agent’s command for connecting / disconnecting from the power network. This simulation will demonstrate the benefits of employing a standard MAS environment that could serve as a platform for studying real-time microgrid’s communication, monitor and control technologies.
9- PENNSYLVANIA STATE HARRISBURG CAMPUS MICROGRID TEST-BED DESIGN AND EVALUATION
Lavinia M. Pintiuta, M.Eng. EE, June 2014
Peter Idowu, Ph.D., P.E. (Paper Advisor), Hossein Jula, Ph.D., Seth Wolpert, Ph.D.
Abstract -The purpose of this paper is to present the design and simulation of a conceptual microgrid and test-bed for Penn State Harrisburg Campus. Besides producing renewable and efficient energy, the microgrid will establish a test-bed for research, development and testing of new technologies for Smart Grid applications. This paper describes and simulates (using ETAP and Homer Energy) the existing electric system and the proposed Distributed Energy Resource (DER) and Distributed Energy Storage (DES) systems. The on-site heating plant is used for cogeneration (use of waste heat resulting from conversion of primary fuel to electricity), thereby increasing the system’s overall efficiency.
10- ANN-BASED PSS DESIGN FOR REACTIVE POWER REGULATION USING SYNCHRONOUS CONDENSER
Mohammed Abdullah Hatatah, MSEE, April 2015
Peter Idowu, Ph.D., P.E. (Thesis Advisor), Seth Wolpert, Ph.D., Scott Van Tonningen, Ph.D.
Abstract -The behavior of the electric system requires a balanced operation between resources and customer demand including various electrical losses. As loads change, the reactive power requirements of the power system change. Since the reactive power cannot be transferred over long distances, voltage control has to be affected by using special equipment to keep sufficient levels of voltage in the power system network. The right selection of equipment for controlling reactive power and voltage stability are among the major challenges of system engineering [1]. With today’s modern equipment designs and the modern control techniques, it is appropriate to again examine synchronous condensers as a reactive power solution. A synchronous condenser can work and support the system with an effective reactive power under low voltage conditions. In addition, it can raise the short circuit level of the system.
Stabilization is one of the most significant aspects in power system dynamics. The power system stabilizer (PSS) has become the primary means for supplying supplementary excitation signals to regulate reactive power delivery. In this thesis, the artificial neural network (ANN) was used to create a power system stabilizer. A three-layer feed-forward neural network PSS (FNNPSS) was employed. The back-propagation algorithm was used for the purpose of training. The main contribution of the control scheme is that it can improve the learning process by using the generalization property of the ANN. The test system (IEEE 9-bus) and the ANN-based PSS synchronous condenser were simulated in the MATLAB/SIMULINK environment. Results revealed that a system with ANN-based PSS can stabilize the system under various parameters in the power system.
11- LABVIEW AND MATLAB-BASED INDUCTION MOTOR SIGNATURE ANALYSIS LABORATORY
Christopher Root, M.Eng. EE, December 2012
Peter Idowu, Ph.D., P.E. (Paper Advisor), Aldo Morales, Ph.D., Seth Wolpert, Ph.D., Biswajit Ray, Ph.D.
Abstract -Induction machines are the primary electrical load for the industrial sector in the United States, their importance and impact on industrial productivity could not be ignored without consequence on economic growth. The ability to predict faults and failures of these devices is therefore critical in industrial operations as this would make planned maintenance feasible, as well as minimize production equipment downtime. Unfortunately, undergraduate electrical engineering curriculum rarely includes topics on induction machine fault diagnosis and prediction techniques, so the typical EE graduate is underprepared and lacking skills for this important industry need.
The purpose of my research is to introduce four different computer interfaces developed for studying induction motor faults in the undergraduate educational laboratory setting, using National Instruments LabVIEW and MathWorks MATLAB. Custom laboratories developed in LabVIEW feature real-time motor controls, remote capabilities and motor current data capture. The MATLAB laboratories for offline fault prediction and diagnosis utilize Fast Fourier Transforms (FFT) and Artificial Neural Networks (ANN), with each capable of accepting motor current data from external sources. The research results show some improvement on classical induction motor fault prediction techniques, while taking a more practical approach in FFT analysis and application of an ANN back propagation algorithm.
12- PRECISION STATE-OF-CHARGE AND STATE-OF-HEALTH INDICATION USING COULOMB COUNTING AND PULSE TESTS
Christopher Lashway, M.Eng. EE, August 2012
Peter Idowu, Ph.D., P.E. (Paper Advisor), Aldo Morales, Ph.D., Seth Wolpert, Ph.D.
Abstract – Many electric devices in everyday use do not have the capability for accurate estimation of power remaining in storage or state-of-charge (SOC). Industry products such as cellular phones, portable computers, and uninterruptible power supplies (UPS) utilize the classical method of coulomb-counting, relying only on current to make their estimations. Unfortunately, this method alone is weak as it does not take into account the age of the battery nor the number of cycles the battery has charged and discharged. As a result, these devices can report false information, initially depicting a full charge and only minutes later show that the battery has been exhausted.
Historical information is essential for depicting the capacity-loss that is associated with batteries over time and continuous use. Battery history can aid in determining not only a precise SOC but also the condition or state-of-health (SOH) of the battery. Through the implementation of an advanced book-keeping system and incorporating other battery parameters and measurements, the accuracy of the SOC and SOH assessments can be dramatically increased. This could lead to the development of a more precise measurement tool which could provide a low-cost alternative to common everyday devices.
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