Credit policies for clean and renewable energy businesses play a crucial role in supporting carbon neutrality efforts to combat climate change. Clustering the credit capacity of these companies to prioritize lending is essential given the limited capital available. Support Vector Machine (SVM) and Artificial Neural Network (ANN) are two robust machine learning algorithms for addressing complex clustering problems. Additionally, hyperparameter selection within these models is effectively enhanced through the support of a robust heuristic optimization algorithm, Particle Swarm Optimization (PSO). To leverage the strength of these advanced machine learning techniques, this paper aims to develop SVM and ANN models, optimized with the PSO, for the clustering problem of green credit capacity in the renewable energy industry. The results show low Mean Square Error (MSE) values for both models, indicating high clustering accuracy. The credit capabilities of wind energy, clean fuel, and biomass pellet companies are illustrated in quadrant charts, providing stakeholders with a clear view to adjust their credit strategies. This helps ensure the efficient operation of banking green credit policies.

The co-hydrothermal carbonization of biomasses has shown many advantages on charcoal yield, carbonization degree, thermal-stability of hydrocar and energy recovered. The goal of this study is to investigate the effect of co-combustion of cattle manure and sawdust on energy recovered. The results show that ash content ranged between 10.38%–20.00%, indicating that the proportion of each variable influences energy recovered. The optimum is obtained at 51% cattle manure and 49% sawdust revealing 37% thermal efficiency and 3.9 kW fire power. These values are higher compared to cattle manure individually which gives values of 30% and 2.3 kW respectively for thermal efficiency and fire power. Thus, the mixture of biomasses enhances energy recovered both in combustion and hydrothermal carbonization. Volatile matter is lower in mixture predicting that the flue gas releases is lower during combustion. Fixed carbon is higher in mixture predicting that energy recovered increases during the combustion of mixture than cattle manure individually. Higher Carbon content was noticed in mixture than cattle manure indicating that the incorporation of sawdust enhances heating value. The incorporation of sawdust in cattle manure can also enhance energy recovered and is more suitable for domestic and industrial application.

Distributed Energy Resources (DERs), such as solar photovoltaic (PV) systems, wind turbines, and energy storage systems, offer many benefits, including increased energy efficiency, sustainability, and grid reliability. However, their integration into the smart grid also introduces new vulnerabilities to cyber threats. The smart grid is becoming more digitalized, with advanced technologies like Internet of Things (IoT) devices, communication networks, and automation systems that enable the integration of DER systems. While this enhances grid efficiency and control, it creates more entry points for attackers and thus expands the attack surface for potential cyber threats. Protecting DERs from cyberattacks is crucial to maintaining the overall reliability, security, and privacy of the smart grid. The adopted cybersecurity strategies should not only address current threats but also anticipate future dangers. This requires ongoing risk assessments, staying updated on emerging threats, and being prepared to adapt cybersecurity measures accordingly. This paper highlights some critical points regarding the importance of cybersecurity for Distributed Energy Resources (DERs) and the evolving landscape of the smart grid. This research study shows that there is need for a proactive and adaptable cybersecurity approach that encompasses prevention, detection, response, and recovery to safeguard these critical energy systems against cyber threats, both today and in the future. This work serves as a valuable tool in enhancing the cybersecurity posture of utilities and grid-connected DER owners and operators. It allows them to make informed decisions, protect critical infrastructure, and ensure the reliability and security of grid-connected DER systems in an evolving energy landscape.

Heat recovery is one of the measures proposed for the appropriate use of ammonia in tropical countries. This article analyzes a heat recovery system installed in an industrial refrigeration plant. Based on comparative readings of operating parameters of the installation, determined the effectiveness of the heat exchange, the increase in the efficiency of the refrigeration system, as well as the fuel saved by heating water in the industry. The results obtained reported that the thermal design based on heat exchange in annular spaces allows a significant saving of resources and a high rate of thermal utilization.

As China’s urbanisation continues, the building area is expanding, of which the occupancy of rural residential buildings is also very large. However, most rural buildings have poor thermal performance. This paper analyses the energy-saving potential of green facades for rural buildings in China by simulating typical buildings with different types of facades in rural China. The simulation results show that indirect green façades can achieve good energy savings. Buildings with four types of facades: red brick, rubble, hollow brick, and concrete achieve energy savings of 18.39%, 17.85%, 14.47%, and 11.52%, respectively, after retrofitting with green facades.