Towards a sustainable environment and carbon neutrality: Optimal sizing of standalone, green, reliable, and affordable water-power cogeneration systems

Today, the limited sources of freshwater supply are a significant concern. Exploiting alternative sources, especially seawater, has been the focus, but purifying it is energy-intensive. Integrating desalination with renewable energy is a proposed solution, but it comes with high costs and environmental risks during construction. Hence, this study presents a framework to enhance the modeling, optimization, and evaluation of green water-power cogeneration systems to achieve the sustainability goals of cities and societies. An improved division algorithm (DA) determines the optimal component sizes based on criteria like minimal energy demand, reduced environmental and resource damage, low total life cycle cost (TLCC), and high reliability. Optimization considers varying loss of power supply probability (LPSP) levels (0 %, 2 %, 5 %, and 10 %). The environmental assessment utilizes a life cycle assessment (LCA) approach with IMPACT 2002+ and cumulative energy demand (CED) calculations. The study models the green cogeneration systems based on weather conditions, water demand, and power requirements of Al Lulu Island, Abu Dhabi, UAE. The system comprises photovoltaic panels, wind turbines, tidal generators, and backup systems (fuel cells). Results reveal that TLCC ranges from $186,263 to $486,876 for the highest LPSP. The solar-tidal-based configuration offers the lowest TLCC ($186,263) while substituting solar with wind energy increases TLCC by 160 %. The wind-tidal-based configuration has the lowest specific environmental impact (1020 mPt/yr) and cumulative energy demand (39.06 GJ/yr) for the highest LPSP. In contrast, the solar-tidal-wind-based configuration inflicts the most damage, with 62.63 GJ/yr and 1794 mPt/yr for the highest LPSP. The finding indicates that the DA is faster (100 iterations) than the genetic algorithm (1000 iterations), particle swarm optimization (400 iterations), and artificial bee swarm optimization (300 iterations). The study underscores the solar-tidal-based configuration as the optimal choice across multiple criteria, offering a promising solution for freshwater supply and environmental sustainability on Al Lulu Island.

A resilient battery electric bus transit system configuration

Electric mobility is fundamental to combat climate change and attaining the United Nations Sustainable Development Goals (SDG-11). However, electric mobility necessitates a seamless integration between power and transportation systems, as the resiliency of both systems is becoming far more interdependent. Here, we focus on disruption to Battery Electric Bus (BEB) transit system charging infrastructure and offer a resilient BEB transit system planning model. The proposed model optimizes the BEB system costs while ensuring the system's robustness against simultaneous charging station failures. In our case study, a single charging station failure would lead to up to 34.03% service reduction, and two simultaneous failures would reduce the service by up to 58.18%. Our proposed two-stage robust model addresses this issue with a relatively small added cost (3.26% and 8.12% higher than the base model). This cost enables uninterrupted BEB system operation during disruption, ensuring personal mobility, social interaction, and economic productivity.