Residential Energy Storage Management with Bidirectional Energy Control

TL;DR

This paper introduces a real-time bidirectional energy control algorithm for residential energy storage systems with renewable sources, optimizing costs while considering battery constraints and market dynamics.

Contribution

It develops a Lyapunov optimization-based algorithm that operates in real-time without needing statistical knowledge of system variables, improving energy management efficiency.

Findings

Algorithm achieves near-optimal cost performance.

Effective in unknown and varying renewable and price conditions.

Reveals impact of battery and market factors on energy decisions.

Abstract

We consider the residential energy storage management system with integrated renewable generation, with the availability of bidirectional energy flow from and to the grid thorough buying and selling. We propose a real-time bidirectional energy control algorithm, aiming to minimize the net system cost, due to energy buying and selling and battery deterioration and inefficiency from storage activities, within a given time period, subject to the battery operational constraints and energy buying and selling constraints. We formulate the problem as a stochastic control optimization problem. We then modify and transform this difficult problem into one that enables us to develop the real-time energy control algorithm through Lyapunov optimization. Our developed algorithm is applicable to arbitrary and unknown statistics of renewable generation, load, and electricity prices. It provides a simple closed-form control solution only based on current system states with minimum complexity for real-time implementation. Furthermore, the solution structure reveals how the battery energy level and energy prices affect the decision on energy flow and storage. The proposed algorithm possesses a bounded performance guarantee to that of the optimal non-causal T-slot look-ahead control policy. Simulation shows the effectiveness of our proposed algorithm as compared with alternative real-time and non-causal algorithms, as well as the effect of selling-to-buying price ratio and battery inefficiency on the storage behavior and system cost.