Working towards accomplishing SDG 7 in Australia with an effective home energy management system

The global energy landscape is undergoing transformation to mitigate climate change and fulfil Sustainable Development Goal 7 (SDG 7), which targets affordable, reliable, sustainable, and universally accessible modern energy. Despite extensive adoption of residential photovoltaic (PV) systems in Australia, several practical challenges remain, including high electricity costs, low self-consumption of PV generation, and energy accessibility for the remote regions and First Nations communities. This study proposes a home energy management system (HEMS) incorporating the reinforcement learning (RL)-based model to dynamically manage energy flows among residential PV generation, battery storage systems, household loads, and the grid. The energy scheduling problem is formulated as a Markov Decision Process (MDP) and solved using a Proximal Policy Optimization (PPO) agent that learns optimal dispatch strategies under dynamic operating conditions. The reward function integrates electricity cost, self-consumption ratio (SCR), and grid dependency (GD). A multi-objective search based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to determine suitable combinations of reward weights. To better represent real residential operation, the model further incorporates battery degradation and grid outage scenarios into the system simulation. Simulation results based on realistic Australian residential load profiles and tariff structures demonstrate satisfactory operational performance. The results demonstrate that the proposed HEMS can adapt to households with different PV generation and demand patterns while coordinating PV–battery operation to improve the utilization of locally generated solar energy and reduce reliance on grid electricity. The analysis highlights the trade-off between battery utilization and long-term degradation, as well as the potential of PV–battery systems to improve household energy resilience during grid outage events. In addressing the practical implementation of SDG 7 within the Australian context, the proposed HEMS offers critical policy, social, and economic implications. The system enhances affordability by significantly reducing household electricity bills and shortening investment payback periods, supports sustainability by increasing local renewable energy utilization, and improves energy accessibility by supporting stable and cost-effective electricity for remote and underserved communities. Policy recommendations are included to suggest stable incentives for battery storage and solar feed-in tariffs, promote integrated HEMS solutions, and advance equitable energy access.