RESUMEN
This study proposes a novel honey bee dancing (HBD) maximum power point tracking (MPPT) algorithm inspired by the foraging behavior of honey bees. When a bee finds nectar, it returns to the honeycomb and dances to inform others about the location of the nectar. Other bees then fly towards the location and gather the nectar. The proposed HBD algorithm uses five bees searching for the nectar who communicate with each other about the location and the quantity of nectar by dancing. Finally, the five bees found the location of the most nectar which is represented by the maximum power point. The proposed HBD algorithm applies to uniform irradiance condition (UIC) and partial shaded condition (PSC). It is then compared with the PV panel output power and load relationship (OPLR) algorithm and perturb and observe (P&O) algorithm. Experimental verification has been performed under both the UIC and PSC. At the UIC's irradiance level of 200 W/m2, the PV module's output power for the proposed HBD algorithm, OPLR algorithm, and P&O algorithm are 120 W, 118 W, and 94.5 W, respectively, with efficiencies of 99 %, 97 %, and 78 %. Additionally, under the PSC with an irradiance level of 600 W/m2, the PV module's output power for the proposed HBD algorithm, OPLR algorithm, and P&O algorithm are 218 W, 189.2 W, and 74.8 W, respectively, with efficiencies of 99 %, 86 %, and 34 %, and convergence times of 4.7 ms, 6.5 ms, and 6 ms, respectively. It is evident from the results that the solar MPPT performance of the proposed HBD algorithm is better than the OPLR algorithm and P&O algorithm. This method ingeniously combines the foraging behavior of bees with solar power generation to produce the maximum natural power. This approach does not require the development of photovoltaic (PV) panel specification data, complex calculations, and additional temperature meters and heliographs. It is highly efficient and has significant economic benefits.
RESUMEN
The Energy Recovery Ventilator (ERV) is proven efficient for residential ventilation applications. Yet, certain drawbacks, including a more confined space due to descended ceiling, a lengthy accompanying duct system, and over-ventilation issues that result in extensive energy consumption, need to be addressed. In this study, a novel Chain Recooling Energy Recovery Ventilator (CR-ERV) system is proposed to replace the typical ERV system design to solve the shortcomings above. By conducting an experiment on a three-bedroom condo in a hot and humid climate, it was found that compared to the natural ventilation strategy, the proposed system can help reduce the mean indoor carbon dioxide (CO2) concentration from 976 to 677 ppm and PM2.5 concentration from 6.4 to 4.1 µg/m3, representing a 29% and 34% reduction, respectively. From the regulatory perspective, only 64.4% of the natural-ventilated hours have a CO2 concentration below the 1000 ppm limit per the local air quality Act. This fraction can be improved to 99% after adopting the proposed ventilation system. All these benefits come at the cost of a slight 2.3% increase in electricity consumption. In summary, the proposed system is proven efficient, and its implementation is fairly straightforward and economical; thus might be worth integrating into future residential building projects.