PulseAugur
EN
LIVE 09:10:34

Metaheuristic Algorithms Optimize Appliance Scheduling for Solar Energy

This paper introduces a metaheuristic approach using Iterated Local Search (ILS) and Simulated Annealing (SA) to optimize appliance scheduling for solar energy management. The goal is to maximize the utilization of solar energy by aligning appliance usage with generation times, while minimizing user inconvenience and adhering to system constraints like battery charge and inverter limits. The proposed method extends scheduling beyond a single day to handle tasks that spill over, ensuring continuity and enabling multi-day sequential operations. AI

IMPACT This research could lead to more efficient home energy management systems by better integrating solar power with appliance usage.

RANK_REASON The cluster contains an academic paper detailing a new metaheuristic approach for appliance scheduling.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Hiba Ahmed, Alexander E. I. Brownlee, Jason Adair, Simon T. Powers ·

    Optimizing Appliance Scheduling for Solar Energy Management Using Metaheuristic Algorithms

    arXiv:2606.13407v1 Announce Type: new Abstract: Renewable energy is essential for meeting future energy demands; however, solar energy generation, which occurs only during daylight hours often does not align with household consumption patterns. Appliances such as cookers, washing…

  2. arXiv cs.AI TIER_1 English(EN) · Simon T. Powers ·

    Optimizing Appliance Scheduling for Solar Energy Management Using Metaheuristic Algorithms

    Renewable energy is essential for meeting future energy demands; however, solar energy generation, which occurs only during daylight hours often does not align with household consumption patterns. Appliances such as cookers, washing machines, and dryers are typically operated acc…