Carbon-aware Market Participation for Building Energy Management Systems

TL;DR

This paper introduces a real-time, carbon-aware energy management system for buildings that optimizes grid interactions and demand to reduce emissions significantly with minimal cost increase, using advanced forecasting and optimization techniques.

Contribution

It presents a novel integrated framework combining MILP and Transformer-based forecasting for real-time, carbon-aware building energy management.

Findings

22.5% reduction in emissions achieved

Only 1.7% increase in operational cost

Effective in real-world PJM market data

Abstract

Tackling climate change requires the rapid and deep decarbonization of electric power systems. While energy management systems (EMSs) play a central role in this transition, conventional EMSs focus mainly on economic efficiency and often overlook the environmental impact of operational decisions. To address this gap, this paper proposes a unified, real-time building-level carbon-aware EMS (CAEMS) capable of simultaneously co-optimizing grid imports, energy storage, and flexible demand within a single integrated framework. We formulate a mixed-integer linear program (MILP) model that directly integrates time-varying marginal carbon intensity signals into the EMS objective for coordinated participation in both day-ahead (DA) and real-time (RT) markets. To relax the unrealistic assumption of perfect foresight, we incorporate a model predictive control (MPC) extension driven by a Transformer-based forecaster that jointly predicts electricity prices and carbon intensity. The proposed CAEMS is validated using real-world data from the PJM electricity market. Simulation results demonstrate that modest carbon prices can achieve a significant 22.5% reduction in emissions with only a 1.7% increase in cost.