Engineering Commons^™

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 …

Home Energy Management System For Coordinated Pv And Hvac Controls Based On Ai Forecasting, Huangjie Gong, Rosemary E. Alden, Dan M. Ionel

Power and Energy Institute of Kentucky Presentations

Introduction

• This HEMS serves to transform HVAC system demand into a schedulable load bank or “dispatchable load” through controls based on day ahead forecasts
• Within this poster, a complete structure from data acquisition to day-ahead load scheduling is proposed
• For the purpose of study, measured data is used in place of forecasts to showcase best case results.

Vpeak: Exploiting Volunteer Energy Resources For Flexible Peak Shaving, Phuthipong Bovornkeeratiroj, John Wamburu, David Irwin, Prashant Shenoy

Publications

Traditionally, utility companies have employed demand response for large loads or deployed centralized energy storage to alleviate the effects of peak demand on the grid. The advent of Internet of Things (IoT) and the proliferation of networked energy devices have opened up new opportunities for coordinated control of smaller residential loads at large scales to achieve similar benefits. In this paper, we present VPeak, an approach that uses residential loads volunteered by their owners for coordinated control by a utility for grid optimizations. Since the use of volunteer resources comes with hard limits on how frequently they can be used …

Gold Tree Solar Farm - Machine Learning To Predict Solar Power Generation, Jonathon T. Scott

Computer Science and Software Engineering

Solar energy causes a strain on the electrical grid because of the uncontrollable nature of the factors that affect power generation. Utilities are often required to balance solar generation facilities to meet consumer demand, which often includes the costly process of activating/deactivating a fossil fuel facility. Therefore, there is considerable interest in increasing the accuracy and the granularity of solar power generation predictions in order to reduce the cost of grid management. This project aims to evaluate how sky imaging technology may contribute to the accuracy of those predictions.

Wind Turbine Noise And Wind Speed Prediction, Tyler H. Blanchard

Electronic Theses and Dissertations

In order to meet the US Department of Energy projected target of 35% of US energy coming from wind by 2050, there is a strong need to study the management and development of wind turbine technology and its impact on human health, wildlife and environment. The prediction of wind turbine noise and its propagation is very critical to study the impacts of wind turbine noise for long term adoption and acceptance by neighboring communities. The prediction of wind speed is critical in the assessment of feasibility of a potential wind turbine site. This work presents a study on prediction of …

Solar Power Deployment: Forecasting And Planning, Mohana Shandal Alanazi

Electronic Theses and Dissertations

The rapid growth of Photovoltaic (PV) technology has been very visible over the past decade. Recently, the penetration of PV plants to the existing grid has significantly increased. Such increase in the integration of solar energy has brought attention to the solar irradiance forecasting. This thesis presents a thorough research of PV technology, how solar power can be forecasted, and PV planning under uncertainty.

Over the last decade, the PV was one of the fastest growing renewable energy technologies. However, the PV system output varies based on weather conditions. Due to the variability and the uncertainty of solar power, the …