Smart City Gnosys
Smart city article details
| Title | Financing Sustainable Smart City Projects: Public-Private Partnerships And Green Bonds |
|---|---|
| ID_Doc | 26505 |
| Authors | Xu J.; XU W. |
| Year | 2024 |
| Published | Sustainable Energy Technologies and Assessments, 64 |
| DOI | http://dx.doi.org/10.1016/j.seta.2024.103699 |
| Abstract | The escalating demand for electricity, driven by the confluence of population growth, technological advancements, and economic progress, has precipitated an energy shortfall within the smart city landscape. In addressing this challenge, smart city enterprises are strategically deploying smart grids to implement innovative Demand Response (DR) programs. These initiatives aim to optimize energy consumption by incentivizing citizens through public-private partnerships and exploring financing avenues like green bonds, thereby fostering sustainable and resilient urban energy ecosystems. The initial contribution of this paper introduces an energy management (EM) approach. An Ant Colony Optimization (ACO) procedure is implemented to address the comprehensive planning problem across three researches: one without SOLAR batteries, one with SOLAR systems, and one incorporating SOLAR batteries. The model aims to decrease energy prices, mitigate peak-load, reduce carbon dioxide discharges, and prevent rebound peaks, ultimately enhancing user comfort. Simulations are conducted to match the efficacy of this proposed approach with obtainable ways. The results demonstrate that the recommended ACO procedure effectively reduces energy prices, carbon dioxide discharges, and peak loads across various researches. Consequently, this ACO procedure-based EM routine outperforms existing benchmark approaches. Meanwhile, digital twin (DT) technology is reshaping the renewable energy sector by offering virtual replicas of physical systems. This article delves into the applications, advantages, and challenges associated with digital twin modeling in renewable energy. The technology entails the creation of virtual replicas for renewable energy systems, integrating real-time data to facilitate precise simulation. Key advantages encompass accurate prediction, dynamic monitoring, and the optimization of energy production. The synergy between digital twin modeling and smart grids enhances flexibility and bolsters grid reliability. Nevertheless, challenges include ensuring data security, managing system interconnectivity, and addressing computational demands. In essence, digital twin modeling presents a pathway for realistic representation and efficient management of renewable energy, although challenges must be navigated to unleash its full potential. |
| Author Keywords | Digital twin; Green bonds; Smart city; Smart grid; Sustainable development |
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