Real-Time Residential-Side Joint Energy Storage Management and Load Scheduling with Renewable Integration

TL;DR

This paper presents a real-time control algorithm for residential energy storage and load scheduling with renewable energy, optimizing costs under uncertain conditions with proven performance guarantees.

Contribution

It introduces a novel Lyapunov optimization-based method that separates scheduling and storage control, providing simple, closed-form solutions for real-time implementation.

Findings

The algorithm achieves near-optimal performance with bounded guarantees.

Simulation results show improved cost savings over alternative methods.

The approach effectively handles renewable and load uncertainties.

Abstract

We consider joint energy storage management and load scheduling at a residential site with integrated renewable generation. Assuming unknown arbitrary dynamics of renewable source, loads, and electricity price, we aim at optimizing the load scheduling and energy storage control simultaneously in order to minimize the overall system cost within a finite time period. Besides incorporating battery operational constraints and costs, we model each individual load task by its requested power intensity and service durations, as well as the maximum and average delay requirements. To tackle this finite time horizon stochastic problem, we propose a real-time scheduling and storage control solution by applying a sequence of modification and transformation to employ Lyapunov optimization that otherwise is not directly applicable. With our proposed algorithm, we show that the joint load scheduling and energy storage control can in fact be separated and sequentially determined. Furthermore, both scheduling and energy control decisions have closed-form solutions for simple implementation. Through analysis, we show that our proposed real-time algorithm has a bounded performance guarantee from the optimal T-slot look-ahead solution and is asymptotically equivalent to it as the battery capacity and time period goes to infinity. The effectiveness of joint load scheduling and energy storage control by our proposed algorithm is demonstrated through simulation as compared with alternative algorithms.