
Ranganathan PrakashUniversity of North Dakota | UND · Department of Electrical Engineering
Ranganathan Prakash
PHD IN SOFTWARE ENGINEERING
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Publications (107)
Synchrophasor technology or phasor measurement units (PMUs) are known to detect multiple type of oscillations or faults better than Supervisory Control and Data Acquisition (SCADA) systems, but the volume of Bigdata (e.g., 30-120 samples per second on a single PMU) generated by these sensors at the aggregator level (e.g., several PMUs) requires spe...
Critical infrastructures like the power grid are at risk from increasing cyber threats due to high penetration of interconnected distributed energy resources (DER). Compromised DER endpoints can cause events, data breaches, communication loss, intentional device failures, and even cascading outages. To address these challenges, this paper explores...
Integration of Renewable Energy Sources (RES) into the power grid is an important aspect, but it introduces several challenges due to its inherent intermittent and variant nature. Hybrid Energy Storage Systems (HESS) is a reliable approach to overcome this issue. HESS combines various storage technologies to improve both the performance and reliabi...
This paper investigates the detection of Global Positioning System (GPS) interference during the Dallas Fort Worth (DFW) event from 17 to 19 October 2022, utilizing various machine learning (ML) models. The study examines the effectiveness of several ML models, including neural networks (NN), tree-based models, regression-based models, Bayesian cla...
Sags are a serious issue and play a critical role for its cause due to multiple environmental factors such as extreme weather events: wind speed, blizzard, and heat loss. This paper provides a comprehensive review of sag measurements and its quantification methods. Current sag measurement and monitoring approaches are quantified using optical senso...
Malware is the short form of “Malicious Software” that is designed in a specific way to harm or exploit the host program with malicious intent. Often, the malware program replicates or appears as a legitimate executable program, which, upon the execution trigger, performs the programmed commands that cause systematic problems to the host machine. M...
Unmanned aerial systems/vehicles (UAS/UAVs) are widely employed for inspecting high-voltage (HV) Tx lines, characterized by elevated electric (E) and magnetic (H) fields. Operating on batteries, these UAVs are equipped with various electrical sensors, microprocessors, and motors, all susceptible to E/H field effects. This paper explores the distrib...
Adaptation of technologies such as the Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), and blockchain in agriculture has revolutionized farming activities, offering several benefits such as increased efficiency, reduced costs, and improved crop yields. However, these advancements also have their fair share of security challenges, opening...
Soybeans play a key role in global food security. U.S. soybean yields, which comprise $$32\%$$ 32 % of the total soybeans planted in the world, continue to experience unprecedented grain loss due to the soybean cyst nematode (SCN) plant pathogen. SCN remains one of the primary disruptive pests despite the existence of advanced management techniques...
Power system failures or outages due to short-circuits or “faults” can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, including location, type, and duration, to reduce the service time of an outage. Existing fault detection...
Alternating current optimal power flow (AC-OPF) is a fundamental tool in electric utilities to determine optimal operation of the various resources. Typically, the AC-OPF problem uses power balance formulation containing voltages and power equations. Yet, there is no comprehensive comparison of the different AC-OPF formulations, especially for larg...
Heat loss quantification (HLQ) is an essential step in improving a building’s thermal performance and optimizing its energy usage. While this problem is well-studied in the literature, most of the existing studies are either qualitative or minimally driven quantitative studies that rely on localized building envelope points and are, thus, not suita...
Environmental concerns over the past decade have driven the need to harness renewable energy resources, such as wind power generation. Forecasting wind power is beneficial to power utilities; however, predicting wind power generation has proven challenging due to the variability in wind speed. This paper has used two machine learning algorithms, Gr...
Due to the high market penetration of wind power, efficient prediction methodologies are of paramount importance to promote wind power generation in the electricity market against more secure and dispatchable energy sources. This paper has proposed mix of regression and machine learning methods, such as Auto-Regressive Integrated Moving Average (AR...
Encryption algorithms play an essential role in network security. They are one type of countermeasure that can prevent unauthorized access of data. Although the security robustness of the algorithm is the focal point in choosing one, other performance metrics are also important, especially for resource-constrained technologies like unmanned aerial...
When discussing the development of MAS for Smart Grid and the advantages of distributed MAS over centralized control in the text of this article [1] and describing MAS tools in Table 2, we inadvertently used text from a previous article by Merabet and colleagues [2] and omitted a citation
Thermal performance assessment of building(s) is an essential process for optimal energy management, heat-loss evaluation, and energy audit applications. Such an assessment can help foresee the requirements for future intervention(s) and aid in benchmarking energy performance. This paper provides a review of several thermal performance assessment t...
Today’s modern vehicles contain anywhere from sixty to one-hundred sensors and exhibit the characteristics of Cyber-Physical- Systems (CPS). There is a high degree of coupling, cohesiveness, and interactions among vehicle’s CPS components (e.g., sensors, devices, systems, systems-of-systems) across sensing, communication, and control layers. Cyber-...
Any biomedical device requiring power from a source other than the human body or gravity is considered an active device. Currently available active biomedical devices encompass an enormous variety of technologies, ranging from large imaging machines to miniature implantable stimulators. These devices are vulnerable to cybersecurity threats, especia...
In the near future, Visible Light Communication (VLC) is expected to be used in multiple environments which were due to radio frequency RF congestion and health limitations, RF should not be employed. VLC is a combination of optical wireless communications and illumination. Due to the misconception that VLC-based communications cannot be eavesdropp...
As modern vehicles are capable to connect to an external infrastructure and Vehicle-to-Everything (V2X) communication technologies mature, the necessity to secure communications becomes apparent. There is a very real risk that today's vehicles are subjected to cyber-attacks that target vehicular communications. This paper proposes a three-layer fra...
Synchrophasor technology or phasor measurement units (PMUs) are known to detect multiple type of oscillations or faults better than Supervisory Control and Data Acquisition (SCADA) systems, but the volume of Bigdata (e.g., 30-120 samples per second on a single PMU) generated by these sensors at the aggregator level (e.g., several PMUs) requires spe...
Accurate forecast of the hourly spot price of electricity plays a vital role in energy trading decisions. However, due to the complex nature of the power system, coupled with the involvement of multi-variable, the spot prices are volatile and often difficult to forecast. Traditional statistical models have limitations in improving forecasting accur...
Unmanned aerial vehicles (UAVs) have significantly disrupted the aviation industry. As technology and policy continue to develop, this disruption is only going to increase in magnitude. A specific technology poised to escalate this disruption is UAV swarm. UAV swarm has the potential to distribute tasks and coordinate operation of many UAVs with li...
With the increasing integration of Distributed Energy Resources (DER) in the power grid, a decentralized approach becomes essential for scheduling and allocation of resources in a smart grid. Economic Dispatch (ED) and Unit Commitment (UC) are the two major resource allocation problems that play critical role in the safe and stable operation of a g...
Forecasting of consumer electricity usages plays an important role to make total smart grid system more reliable. As the activities of individual residential consumers has many uncertain variables, it is hard to accurately forecast the residential load levels. For planning of the electrical resources and to balance demand and supply, accurate forec...
Because electric-grid sensor data originating from several sensors, such as the phasor measurement units (PMUs); intelligent relays; and the new installation of smart meters, Plug-in Hybrid Electric Vehicles (PHEV), or Gridable Vehicles (GV), are exponentially growing, the Smart Grid’s data-analytic platform has huge potential (generation, transmis...
Microgrid decomposition (partitioning, splitting, and clustering) or otherwise determining community structures within a power transmission network is important to optimal management of the transmission system. Power transmission system decomposition is not itself a novel concept. Similar concepts have been utilized dating back to the 1950s for var...
Today’s and tomorrow’s smart-grid systems are made more efficient, cleaner, and reliable with “smart” control mechanisms and decision models that deliver information to consumers so that they can better manage energy resources. The rapidly changing needs and opportunities of today’s electric-grid market require unprecedented levels of inter-operabi...
Wind-power plants that are connected to power systems are often unable to utilize all available power due to transmission constraints.
Creating an autonomous, self-healing electrical grid is one of the most important challenges facing electric-energy providers. Such a system, known as the “smart grid,” must interweave a multitude of systems, both software and hardware, in order to form a complete solution that is capable of meeting the requirements outlined by the United States De...
When a malfunction occurs in a smart-grid electricity-provisioning system, it is vitally important to quickly diagnose the problem and to take corrective action. The self-healing problem refers to the need to take action in near real time in order to reallocate power to minimize the disruption. To address this need, we present a collection of integ...
This chapter presents a linear-programming-based optimal solution for an Optimal Placement Problem (OPP) of Synchrophasors or Phasor Measurement Units (PMU). With the increasing use of Synchrophasors for smart-grid monitoring and control, the problem with PMU placement has become a major concern due to its large installation costs. This chapter uti...
A distributed linear-programming model has been created, developed, implemented, and tested. Two standard IEEE bus systems are modeled and successfully decomposed, in multiple ways, into sub-problems. The problem is solved iteratively in each case and directly supports resource allocation in a Smart-grid environment. I have shown that the LP-based...
This chapter discusses the AMPL implementation and results for running the IEEE 14-bus and IEEE 30-bus systems. The environment for the AMPL modeling software is discussed regarding how to specify the model, data, and run-file information.
The chapter describes a resource-allocation problem in a smart-grid application that is formulated and solved as a binary integer-programming model. To handle power outages from the main distribution circuit, the Smart grid’s intelligent agents have to utilize and negotiate with distributed-energy resource agents that act on behalf of the grid’s lo...
Dantzig-Wolfe decomposition is a technique for dealing with linear- and integer-programming problems that have embedded substructures that permit efficient solution. The technique has been successfully applied in a variety of contexts [Dan63, Chv83, BJN98]. Implementing DW-decomposition-based algorithms poses various challenges. The primary constra...
This book showcases the strengths of Linear Programming models for Cyber Physical Systems (CPS), such as the Smart Grids. Cyber-Physical Systems (CPS) consist of computational components interconnected by computer networks that monitor and control switched physical entities interconnected by physical infrastructures. A fundamental challenge in the...
In this paper, we discuss a distributed Agent Oriented Linear Programming (AOLP) decision model, where large scale electric grid is decomposed in to many sub models (sub problems) that can support prompt resource assignment, computation, and control functions necessary to restore the grid processes quickly during cascading blackouts or outages. The...
This paper presents an approach describing transmit power controlled clusters for Heterogeneous Sensor Networks (HSNs). There are two types of nodes in the network: the low-end and high-end nodes. The objective is to set a threshold limit of transmit power for low end nodes for the intra-cluster communication, and also set a limit for high end node...
We describe a novel framework for designing and implementing agent based simulations of the smart electrical grid. The framework is based on two primary concepts. First, the eletrical grid system is separated into semi-autonomous microgrids, each with their own set of hierarchically organized agents. Second, models for automating decision-making in...
Today's and tomorrow's smart grid systems are made more efficient, cleaner, and reliable by "smart" control mechanisms and decision models that deliver information to consumers so they can better manage energy resources. The rapidly changing needs and opportunities of today's electric grid market require unprecedented levels of interoperability to...
As electric grid sensor data originating from several sensors such as the phasor measurement units (PMUs), intelligent relays, and new installation of smart meters, Plug-in Hybrid Electric Vehicles (PHEV) or Gridable Vehicles (GV), are exponentially growing, the data analytic platform for Smart Grid has huge potential (generation, transmission or d...
We describe the design and implementation of an agent based simulation for a smart grid. The design supports the evaluation of procedures for self healing. The main design goal is to support the testing and comparing of alternative decision models that can specify grid-management actions that can be applied in scenarios that call for self healing....
When a malfunction occurs in a Smart Grid electricity provisioning system, it is vitally important to quickly diagnose the problem and take corrective action. The self-healing problem refers to the need to take action in near real time to reallocate power to minimize the disruption. To address this need, we present a collection of integer linear pr...
The work is focused on modeling Smart Grid functional requirements using use case descriptors and UML class diagrams. The design patterns help identify appropriate agents in the event of any outage in a microgrid. The paper presents selective UML diagrams for different layers in a multi agent design for a power system called UML-MAPS. The architect...
Electrical grids are highly complex and dynamic systems that can be unreliable, insecure, and inefficient in serving end consumers. The promise of Smart Grids lies in the architecting and developing of intelligent distributed and networked systems for automated monitoring and controlling of the grid to improve performance. We have designed an agent...
The requirements for modeling a software product are growing in size and increasingly getting complex, interdependent and to understand them requires the availability of simple representational requirement engineering tools and measures to evaluate them. Requirements engineering still remains a key factor to guarantee stakeholders involvement, faci...
As the distance learning environment has evolved into a more convenient and simple to use teaching platform in recent days, but student assessment instrument of most institutions do not follow any concrete model or protocol, when delivering a distance course. Educational institutions worldwide are recognizing that teaching core courses in the curri...
This paper proposes a method to estimate the flicker severity index using the Walsh Hadamard transform (WHT). A weighting filter in the sequency domain is utilized for direct computation of the flicker index. The proposed method is compared with a flicker meter in the frequency domain that uses the fast Fourier transform (FFT). It is seen by numeri...
Agent Oriented Programming (AOP) is a recent promising software paradigm that brings concepts from the theories of artificial intelligence into the mainstream realm of distributed systems, and yet it is rather difficult to find a successful application of agent oriented system (specifically) when large-scale systems are considered. When adopting an...