Power and Energy Commons^™

Machine Learning In Peak Demand Forecasting: Foundations, Trends, And Insights, Shuang Dai, Fanlin Meng, Hongsheng Dai, Qian Wang, Xizhong Chen, Wenlei Bai, Peizhi Shi, Richard Allmendinger, Yuchen Zhang, Jian Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Peak demand forecasting involves predicting the maximum electricity demand within a specific period, which plays a key role in maintaining the efficiency and stability of power systems. The rapid evolution of power systems, driven by advanced metering infrastructure, local energy applications such as electric vehicles, and the increasing adoption of intermittent renewable energy, has introduced greater randomness and reduced predictability in peak demand. Given the pressing need to address more diverse implementation requirements across different contexts, accurate and reliable peak demand forecasting has become increasingly important. To the best of our knowledge, this study is the first to provide a …

Enhanced Load Detection With Data-Driven Appliance Signatures Using Mixed Integer Linear Programming In Non-Intrusive Load Monitoring, Marina Materikina

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Despite the numerous research studies and interest in the non-intrusive load monitoring (NILM) area to improve energy efficiency, the problem of accurate and precise disaggregation of electrical devices has not been solved yet. The goal of our research is to build a method with a focus on higher accuracy on complex state-based appliances, which most approaches struggle to detect due to their power signal complexity and low consumption. Our approach is NILM with data-driven signatures (DS), with the ability to potentially predict power usage over time that would work great for suitable applications such as demand response, anomaly detection, and …

Dynamic Modeling And Control Of A Solid State Semiconductor-Based Transformer, Microgrid And Storage Systems, Rubén Darío Viñán-Velasco

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Smart Grids are power grid models designed with the idea of including the growing new technologies, from generation to storage devices, and are a response to the growing demands from consumers and the presence of electronic components being commonplace in the modern devices. The design requires a dynamic alternative in order to build an independent grid that can also work in cooperation with other micro-grids and the power grid in an integrated way. Smart-grids present several advantages over the traditional power grid scheme, but the economic costs of the components required to implement smart-grids is currently a great limitation. This …

Energy Harvesting For Residential Microgrid Distributed Sensor Systems, Devin C. Whalen

Master’s Theses

Microgrids are localized, independent power grids that can operate while connected to the larger electrical grid. These systems make intelligent decisions regarding power management and use an array of components to monitor power generation, consumption, and environmental conditions. While this technology can save end users money, the complexity of installation and maintenance has limited the adoption of microgrids in residential spaces. To simplify this technology for end users, the next evolution of microgrid components includes sensors that are wireless and ambiently powered.

Even with a microgrid installed, significant energy is wasted in residential spaces. To address this loss, energy harvesting …

Smart Grid In Tanzania: Research Opportunities, Aviti Thadei Mushi

Tanzania Journal of Engineering and Technology (TJET)

reinvigorated its power generation capacity significantly to ensure smooth execution of its industrialization agenda and cope with the fourth industrial revolution. To ensure reliable availability of power to sustain its growing economy, Tanzania embarked on a deliberated measure to forge an energy mix. This deliberate measure encompasses the use of renewable energy technologies such as wind, solar, biomass, wastes, and micro hydro; natural gas; and other energy sources which are locally available including coal and geothermal. To effectively and efficiently manage such a growing power system and make electricity accessible to all for higher levels of industrial investment and services, …

Editorial: Internet Of Energy For Renewable Energy-Based Decarbonized Electrical Energy Systems, Onur Elma, Murat Kuzlu, Nasibeh Zohrabi

Engineering Technology Faculty Publications

[Introduction] This research topic aims to highlight the current state-of-the art technologies in digitalized smart grids, including renewable energy and others with the Internet of Energy (IoE) under the decarbonized electrical energy systems. These approaches will increase the overall efficiency of electrical power systems, along with emerging technologies and applications in the current system. IoE covers all digitalization processes with mobility, electronic devices, and energy network as seen in Figure 1.

Digital Twin For Hvac Load And Energy Storage Based On A Hybrid Ml Model With Cta-2045 Controls Capability, Rosemary E. Alden, Evan S. Jones, Huangjie Gong, Abdullah Al Hadi, Dan Ionel

Power and Energy Institute of Kentucky Faculty Publications

Building modeling, specifically heating, ventilation, and air conditioning (HVAC) load and equivalent energy storage calculations, represent a key focus for decarbonization of buildings and smart grid controls. Widely used white box models, due to their complexity, are too computationally intensive to be employed in high resolution distributed energy resources (DER) platforms without simulation time delays. In this paper, an ultra-fast one-minute resolution Hybrid Machine Learning Model (HMLM) is proposed as part of a novel procedure to replicate white box models as an alternative to widespread experimental big data collection. Synthetic output data from experimentally calibrated EnergyPlus models for three existing …

Forecast Of Community Total Electric Load And Hvac Component Disaggregation Through A New Lstm-Based Method, Huangjie Gong, Rosemary E. Alden, Aron Patrick, Dan Ionel

Power and Energy Institute of Kentucky Faculty Publications

The forecast and estimation of total electric power demand of a residential community, its baseload, and its heating ventilation and air-conditioning (HVAC) power component, which represents a very large portion of a community electricity usage, are important enablers for optimal energy controls and utility planning. This paper proposes a method that employs machine learning in a multi-step integrated approach. An LSTM model for total electric power at the main circuit feeder is trained using historic multi-year hourly data, outdoor temperature, and solar irradiance. New key temperature indicators, TmHAVC, corresponding to the standby zero-power operation for HVAC systems for summer cooling …

Multi-Physics And Artificial Intelligence Models For Digital Twin Implementations Of Residential Electric Loads, Steven Poore, Rosemary E. Alden, Huangjie Gong, Dan M. Ionel

Power and Energy Institute of Kentucky Faculty Publications

Heating, ventilation, and air-conditioning (HVAC) and electric water heating (EWH) represent residential loads. Simulating these appliances for electric load forecasting, demand response (DR) studies, and human behavior analysis using physics-based models and artificial intelligence (AI) can further advance smart home technology. This paper explains the background of residential load modeling, starting with the concept of digital twin (DT) as well as the different types of methods. Two major types of appliance load monitoring (ALM) and their advantages/disadvantages are then discussed. This is followed by a review of multiple studies on residential load modeling, particularly for HVAC, EWH, and human behavior. …

Models And Optimal Controls For Smart Homes And Their Integration Into The Electric Power Grid, Huangjie Gong

Theses and Dissertations--Electrical and Computer Engineering

Smart homes can operate as a distributed energy resource (DER), when equipped with controllable high-efficiency appliances, solar photovoltaic (PV) generators, electric vehicles (EV) and energy storage systems (ESS). The high penetration of such buildings changes the typical electric power load profile, which without appropriate controls, may become a “duck curve” when the surplus PV generation is high, or a “dragon curve” when the EV charging load is high. A smart home may contribute to an optimal solution of such problems through the energy storage capacity, provided by its by battery energy storage system (BESS), heating, ventilation, and air conditioning (HVAC) …

Artificial Intelligence Method For The Forecast And Separation Of Total And Hvac Loads With Application To Energy Management Of Smart And Nze Homes, Rosemary E. Alden, Huangjie Gong, Evan S. Jones, Cristinel Ababei, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Separating the HVAC energy use from the total residential load can be used to improve energy usage monitoring and to enhance the house energy management systems (HEMS) for existing houses that do not have dedicated HVAC circuits. In this paper, a novel method is proposed to separate the HVAC dominant load component from the house load. The proposed method utilizes deep learning techniques and the physical relationship between HVAC energy use and weather. It employs novel long short-term memory (LSTM) encoder-decoder machine learning (ML) models, which are developed based on future weather data input in place of weather forecasts. In …

Equivalent Electric And Heat-Pump Water Heater Models For Aggregated Community-Level Demand Response Virtual Power Plant Controls, Huangjie Gong, Tim Rooney, Oluwaseun M. Akeyo, Brian T. Branecky, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Advanced control techniques may be used to establish a virtual power plant to regulate the operation of electric water heaters, which may be regarded as a “uni-directional battery” and a major component of a hybrid residential energy storage system. In order to estimate the potential of regulating water heaters at the aggregated level, factors including user behavior, number of water heaters, and types of water heaters must be considered. This study develops generic water heater load curves based on the data retrieved from large experimental projects for resistive electric water heaters (EWHs) and heat pump water heaters (HPWHs). A community-level …

Smart Distributed Generation System Event Classification Using Recurrent Neural Network-Based Long Short-Term Memory, Shuva Das

College of Graduate Studies: Theses & Dissertations

High penetration of distributed generation (DG) sources into a decentralized power system causes several disturbances, making the monitoring and operation control of the system complicated. Moreover, because of being passive, modern DG systems are unable to detect and inform about these disturbances related to power quality in an intelligent approach. This paper proposed an intelligent and novel technique, capable of making real-time decisions on the occurrence of different DG events such as islanding, capacitor switching, unsymmetrical faults, load switching, and loss of parallel feeder and distinguishing these events from the normal mode of operation. This event classification technique was designed …

Computational Intelligence Approaches For Energy Optimization In Microgrids, Tamal Roy

Electronic Theses and Dissertations

The future electrical system termed as smart grid represents a significant paradigm shift for power industry. Nowadays, microgrids are becoming smarter with the integration of renewable energy resources (RESs) , diesel generators , energy storage systems (ESS), and plug-in electric vehicles (PEV or EV) . However, these integration bring with new challenges for intelligent management systems. The classical power generation approaches can no longer be applied to a microgrid with unpredictable renewable energy resources. To relive these problem, a proper power system optimization and a suitable coordination strategy are needed to balance the supply and demand. This thesis presents three …

Anonymous And Efficient Message Authentication Scheme For Smart Grid, Libing Wu, Jing Wang, Sherali Zeadally, Debiao He

Information Science Faculty Publications

Smart grid has emerged as the next-generation electricity grid with power flow optimization and high power quality. Smart grid technologies have attracted the attention of industry and academia in the last few years. However, the tradeoff between security and efficiency remains a challenge in the practical deployment of the smart grid. Most recently, Li et al. proposed a lightweight message authentication scheme with user anonymity and claimed that their scheme is provably secure. But we found that their scheme fails to achieve mutual authentication and mitigate some typical attacks (e.g., impersonation attack, denial of service attack) in the smart grid …

Ict-Enabled Control And Energy Management Of Community Microgrids For Resilient Smart Grid Operation, Mahmoud Saleh

Dissertations and Theses

Our research has focused on developing novel controllers and algorithms to enhance the resilience of the power grid and increase its readiness level against major disturbances.

The U.S. power grid currently encounters two main challenges: (1) the massive and extended blackouts caused by natural disasters, such as hurricane Sandy. These blackouts have raised a national call to explore innovative approaches for enhanced grid resiliency. Scrutinizing how previous blackouts initiated and propagated throughout the power grid, the major reasons are lack of situational awareness, lack of real-time monitoring and control, underdeveloped controllers at both the transmission and distribution levels, and lack …

Applications Of Complex Network Analysis In Electric Power Systems, Mahmoud Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

This paper provides a review of the research conducted on complex network analysis (CNA) in electric power systems. Moreover, a new approach is presented to find optimal locations for microgrids (MGs) in electric distribution systems (EDS) utilizing complex network analysis. The optimal placement in this paper points to the location that will result in enhanced grid resilience, reduced power losses and line loading, better voltage stability, and a supply to critical loads during a blackout. The criteria used to point out the optimal placement of the MGs were predicated on the centrality analysis selected from the complex network theory, the …

Communication Based Control For Dc Microgrids, Mahmoud S. Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

Centralized communication-based control is one of the main methods that can be implemented to achieve autonomous advanced energy management capabilities in DC microgrids. However, its major limitation is the fact that communication bandwidth and computation resources are limited in practical applications. This can be often improved by avoiding redundant communications and complex computations. In this paper, an autonomous communication-based hybrid state/event driven control scheme is proposed. This control scheme is hierarchical and heuristic, such that on the primary control level, it encompasses state-driven local controllers, and on the secondary control level, an event-driven MG centralized controller (MGCC) is used. This …

Robust Power Interface For Smart Grid With Renewable Energy Source-To-Grid Functionality, Bohyun Ahn

All Graduate Theses, Dissertations, and Other Capstone Projects

Many renewable energy companies design wind turbine generators, solar panels, or electrical car batteries with different specifications according to their management philosophy. And typical commercial power converters are not universally designed for all different types of renewable energy systems. Because of this lack of flexibility and interoperability, a universal and scalable smart grid power converter design is desirable. Designing a robust controlled bi-directional power converter is the motivation for this thesis as the first step to develop a more universal converter topology connecting renewable energy sources and the electrical smart-grid of the future.

Renewable energy such as wind or solar …

Hardware Based Testing Of Communication Based Control For Dc Microgrid, Mahmoud Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

This paper further describes our work presented in Industry Application Society 2016 Conference, with more details related to the control and operation of the microgrid. The DC microgrid facility was custom designed and implemented at CCNY with minimal off-the-shelf components to enable flexibility and reconfiguration capability. The design steps, requirements, and experimental results of the developed testbed were discussed. As a case study, a central controller for energy management algorithm was developed and tested under several operational scenarios. The experimental results verify the applicability of the developed testbed for validating DC microgrid controllers.

Smart Grid Technology In The Developing World, Jacob R. Young

Honors Projects

A smart grid is the integration of communication and information technologies with contemporary power infrastructure to enhance load service and to incorporate continually evolving end-use applications. It is the latest advancement in the areas of power generation, transmission and distribution. It has advanced beyond the traditional grid structure at every stage; a smart grid is capable of incorporating distributed generation (DG) renewable sources and has improved transmission capabilities through implementation of technologies such as Flexible AC Transmission Systems (FACTS). Through the addition of control technology in the distribution network a smart grid is able to implement “self-healing” and other methods …

Centralized Control For Dc Microgrid Using Finite State Machine, Mahmoud Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

In this paper, an autonomous communication-based centralized control for DC microgrids (MG) has been developed and implemented. The proposed controller enables smooth transition between various operating modes. Finite state machine (FSM) has been used to mathematically describe the various operating modes (states), and events that may lead to mode changes (transitions). Therefore, the developed centralized controller aims at optimizing the performance of MG during all possible operational scenarios, while maintaining its reliability and stability. Results of selected cases have been presented. These results show stable transition between modes, verifying the validity and applicability of the proposed controller.

Impact Of Clustering Microgrids On Their Stability And Resilience During Blackouts, Mahmoud S. Saleh, Ammar Althaibani, Yusef Esa, Yassine Mhandi, Ahmed Mohamed

Publications and Research

In this paper, the impact of clustering multiple microgrids during blackouts, on their stability and supply availability, will be investigated. Microgrids have the capability of satisfying their emergency loads during blackouts. However, distributed energy resources (DERs)-dominated microgrids are affected by the uncertainty of their input energy supply, e.g. impact of solar irradiance on photovoltaic (PV) output. Moreover, an individual islanded microgrid is prone to instability issues due to large sudden load/generation changes. In order to increase the supply security, and enhance system stability, we propose to use the existing distribution grid infrastructure, if applicable, during blackouts to form microgrid clusters. …

Experimental Verification And Integration Of A Next Generation Smart Power Management System, Tavis Clemmer

Graduate Theses and Dissertations

With the increase in energy demand by the residential community in this country and the diminishing fossil fuel resources being used for electric energy production there is a need for a system to efficiently manage power within a residence. The Smart Green Power Node (SGPN) is a next generation energy management system that automates on-site energy production, storage, consumption, and grid usage to yield the most savings for both the utility and the consumer. Such a system automatically manages on-site distributed generation sources such as a PhotoVoltaic (PV) input and battery storage to curtail grid energy usage when the price …

Load Frequency Control Of Battery Based Energy Storages, Neeru Saini

Theses and Dissertations

This work is the study of potential applications of battery-based energy storages in the power system so that the performance can be improved. The research is focused on the case where batteries are installed at the load side. Such a battery works like an energy buffer between power system and a load. It is possible to control the battery charging time based on the status of the power system operation and the state of charger of the battery so that the power flow in the power system can become more stable. The strategy of load frequency control (LFC) was investigated …

Con-Resistant Trust For Improved Reliability In A Smart Grid Special Protection System, Crystal M. Shipman, Kenneth M. Hopkinson, Juan L. Lopez Jr.

Faculty Publications

This paper applies a con-resistant trust mechanism to improve the performance of a communications-based special protection system to enhance its effectiveness and resiliency. Smart grids incorporate modern information technologies to increase reliability and efficiency through better situational awareness. However, with the benefits of this new technology come the added risks associated with threats and vulnerabilities to the technology and to the critical infrastructure it supports. The research in this paper uses con-resistant trust to quickly identify malicious or malfunctioning (untrustworthy) protection system nodes to mitigate instabilities. The con-resistant trust mechanism allows protection system nodes to make trust assessments based on …

Smart Distributed Generation Systems Using Improved Islanding Detection And Event Classification, Bikiran Guha

College of Graduate Studies: Theses & Dissertations

Distributed Generation (DG) sources have become an integral part of modern decentralized power systems. However, the interconnection of DG systems to the power grid can present several operational challenges. One such major challenge is islanding detection. Islanding occurs when a DG system is disconnected from the rest of the power grid. Islanding can present serious safety hazards and therefore an accurate and fast islanding detection technique is mandated by DG interconnection standards such as IEEE 1547 and UL 1741. Conventional islanding detection techniques passively monitor the local power system parameters such as voltage and frequency to detect islanding. These techniques …

Short-Term Load Forecasting Using Neural Network For Future Smart Grid Application, Jixuan Zheng

Electronic Theses and Dissertations

Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised.

This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries.

Then the thesis compares main aspects about latest products of smart meter from different companies.

Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term …