BYOD
Customer Engagement
Demand Response
EV Charging
Incentive Processing
Program Design
Program Management Automation
Flexible Dispatch
Virtual Power Plants
Platform
Grid-Edge DERMS
Customer Engagement
Demand Forecasting
Greg Ledva
R&D Engineer
About Greg
Greg is a research and development engineer that develops customer-centric and product-driven analytics and algorithms for Virtual Peaker. He believes that advanced analytics and algorithms can overcome challenges in renewable energy and distributed resource adoption, and he is passionate about using his skills to advance the clean energy mission. In his free time, Greg likes to pretend he is handy with home improvement projects and likes to lift weights to stay physically active.
Greg beyond Virtual Peaker
Separating Feeder Demand Into Components Using Substation, Feeder, and Smart Meter Measurements
Managing Communication Delays and Model Error in Demand Response for Frequency Regulation
Real-Time Energy Disaggregation of a Distribution Feeder's Demand Using Online Learning
Applying Networked Estimation and Control Algorithms to Address Communication Bandwidth Limitations and Latencies in Demand Response
Inferring the behavior of distributed energy resources with online learning
Benchmarking of Aggregate Residential Load Models Used for Demand Response
A linear approach to manage input delays while supplying frequency regulation using residential loads
Model predictive control of a large fleet of thermal loads and electric power generators, with an assessment for the Netherlands
Control of Aggregate Air-Conditioning Load using Packetized Energy Concepts
Exploring Connections Between a Multiple Model Kalman Filter and Dynamic Fixed Share with Applications to Demand Response
Parameter Identifiability and Estimation of Thermostatically Controlled Loads
Disaggregating Load by Type from Distribution System Measurements in Real Time
Pattern Matching of In-Vehicle Acceleration Time Series Data
Overcoming the Technical Challenges of Coordinating Distributed Load Resources at Scale
Learning and Control Applied to Demand Response and Electricity Distribution Networks
Written By Greg
Virtual Power Plants: Myth or Reality?
Since the first electric power grid, system operators have dreamed of leveraging the flexibility of the energy consumers connected to […]
What Does EV Telematics Mean for EV Load Management?
Utilities have often turned to demand flexibility or distributed energy resource (DER) programs to optimize available energy assets and reduce the […]
What is Load Forecasting?
Using a variety of means, utility providers work diligently every day to keep the grid in equilibrium. Predicting future energy […]
What is a Virtual Power Plant?
Between initiatives to combat the impact of climate change and tech disruption, the modern power grid is evolving at a […]