A Multi-Agent Reinforcement Learning (MARL) based pricing and incentive strategy for demand response in smart grids.

Repository for development of public schemas

This repository contains my thesis project in which I applied demand repsonse program using matlab and simulink.

Smart power manager for optimized solar power usage as well as greenest and cheapest energy purchase

Agentic AI Home Energy Management System: A Large Language Model Framework for Residential Load Scheduling

Transforms electricity spot price into thermostat control signal. Home Assistant custom component.

Incentivize VPP adoption using smart home Hubs already installed. Hubs can leverage the Communal Grid API to eliminate the guesswork for homes & businesses to understand what current (and potential) Distributed Energy Resource (DER) devices can be enrolled in a locally-available Virtual Power Plant (VPP) — Part of Civilian Power

SEMDR - Smart Energy Management & Demand Response Capabilities for Cyprus Hospitality Sector. Modern website showcasing AI-powered energy management solutions for hotels developed by Neura Energy.

This repository contains the implementation of reinforcement learning algorithms for optimizing energy demand response in commercial buildings. The project focuses on reducing peak loads and improving energy efficiency by controlling HVAC and lighting systems using state-of-the-art RL techniques.

An agent based model to simulate consumer enrollment in residential demand response based on both financial and social factors of consumers

Dynamic electricity carbon emission factors and prices for Europe

Demand Response Analysis Framework (DRAF)

Targeted demand response for flexible energy communities

MATLAB code and data for the research article : I. Daminov, R. Rigo-Mariani, R. Caire, A. Prokhorov, M-C Alvarez-Herault, “Demand Response Coupled with Dynamic Thermal Rating for Increased Transformer Reserve and Lifetime” in Energies (IF: 2.702, Q2), 2021

OpenADR-2B-PyServer is a free, open-source, and secure implementation of an OpenADR 2.0B server written in Python. Utilizing the OpenLEADR library, this project aims to provide a robust and reliable platform for Automated Demand Response (ADR) solutions.

GoEpexSpot aims to be a comprehensive API client for fetching Day-ahead EPEX SPOT prices using Golang (Go).

Quantify geospatial heating flexibility potential based on heating consumption data

Repository of FlexDR application developed within I-NERGY project.

Paper on estimating hourly demand side responses to intermittent electricity prices for the seminar course Energy Economics at UCPH

Code for the paper "MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response"