Optimal Energy Management for SmartGrids Considering Thermal Load and Dynamic Pricing

TL;DR

This paper explores optimal energy management strategies for smart grids that incorporate thermal loads and dynamic pricing, aiming to enhance demand response and integrate distributed energy resources effectively.

Contribution

It introduces a novel energy scheduling framework that considers thermal loads and dynamic pricing to improve smart grid efficiency and user benefits.

Findings

Enhanced demand side management efficiency

Reduced peak demand through thermal load scheduling

Cost savings for electricity users

Abstract

More active participation of the demand side and efficient integration of distributed energy resources (DERs) such as electric vehicles (trVs), energy storage (ES), and renewable energy sources (RESs) into the existing power systems are important design objectives of the future smart grid. In general, effective demand side management (DSM) would benefit both system operators (e.g., peak demand reduction) and electricity customers (e.g., cost saving). For building and home energy scheduling design, heating, ventilation, and air-conditioning (HVAC) systems play a very important role since HVAC power consumption is very significant and the HVAC load can be scheduled flexibly while still maintaining user comfort requirements. This thesis focuses on energy scheduling design for two different application scenarios where HVAC and various DERs are considered to optimize the benefits electric users.