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This study examines the electrical performance and management of hybrid solar street lighting systems with the objective of optimizing their operation for sustainable urban development. Hybrid solar streetlights, which integrate photovoltaic panels with additional power sources, offer resilience and reliability that are crucial for urban settings. A hybrid solar streetlamp was installed in a city in central Italy and monitored for over a year to analyze its electrical behavior and the illuminances obtainable under different boundary conditions and operational programs. The measured data permit the development of an optimization algorithm in a Python program for the optimal management of the solar streetlamp and the forecasting of the battery charging/discharging cycles, as well as the electricity taken from the grid. The simulation scenarios permit the development of a novel management algorithm that is capable of optimizing the battery usage with a minimal draw on the grid in order to achieve a state of near self-sufficiency for the solar streetlamp. The results demonstrate that tilted solar panels enhance energy production, while optimized LED power profiles and system management enhance efficiency. The study highlights the importance of maintaining the state of charge (SOC) of the battery above 20% to extend its lifetime and reduce replacement needs. Economic analysis indicates significant potential energy savings, emphasizing the necessity of system optimization for economic viability and environmental sustainability in urban lighting. Despite initial investment costs and challenges, adopting hybrid solar lighting in urban environments presents substantial benefits, paving the way for a more sustainable and energy-efficient urban future.

Public lighting system represents a key role in the energy transition process, considering the high electricity consumptions related to this sector. The integration of renewables could be suitable for this application and many solutions of solar-based lamps for street lighting are spreading. In this research work, a specific application of a PV-integrated lighting system was installed in the center of Italy along a footpath and monitored for several months, both in terms of electricity parameters and lighting behavior. It is equipped with monocrystalline photovoltaic cells, a lithium-based battery, and a LED lamp. The measured data allow the development of an optimization algorithm in Python program for the correct management of the solar streetlamp and the forecasting of electricity consumptions for different boundary conditions (e.g. Italian geographical position). The energy taken from grid in a year is very low with respect to a traditional lamp not powered by renewables: only 43-46% in central-northern regions and 35% in south region. Data are also used to study the possible substitution of all the traditional lamppost of the walkway with the novel proposed system. A technical-economic analysis is carried out to analyze the effectiveness of this solution not only in terms of electricity consumptions reduction, but also costs savings. The suitability of the investment and the payback time depend on Italian national price of electricity and initial cost of the solar lamp. The results can be applied to similar case studies in Italy to save electricity consumptions and reduce CO2 emissions.

This article presents the application of cluster analysis (CA) to data proceeding from a testbed microgrid located at Sapienza University of Rome. The microgrid consists of photovoltaic (PV), battery storage system (BESS), emergency generator set, and different types of load with a real-time energy management system based on supervisory control and data acquisition. The investigation is based on the area-related approach - the CA algorithm considers the input database consisting of data from all measurement points simultaneously. Under the investigation, different distance measures (Euclidean, Chebyshev, or Manhattan), as well as an approach to the optimal number of cluster selections. Based on the investigation, the four different clusters that represent working conditions were obtained using methods to define an optimal number of clusters. Cluster 1 represented time with high PV production; cluster 2 represented time with relatively low PV production and when BESS was charged; cluster 3 represents time with relatively high PV production and when BESS was charged; cluster 4 represents time without PV production. Additionally, after the clustering process, a deep analysis was performed in relation to the working condition of the microgrid.

Within the policy framework of the energy union strategy started in 2015, the European Union (EU) finalized the “Clean Energy for all Europeans Package” (CEP) in 2019 [...]

This article is devoted to the relevant problem of increasing the efficiency of PV systems. The presented analysis discusses the available methods for improving the power generation of PV modules under partial shading. Mathematical models for power loss calculation were compiled based on the results of this analysis. The proposed approach minimizes the negative impact of partial shading on the energy production of PV modules. It is based on the equalization of voltages of parallel-connected arrays of modules by installing additional power elements in them. The proposed solution is promising for various areas; it allows for the minimization of the unfavorable influence of existing urban objects (buildings, trees, communications, etc.) on the energy efficiency of PV modules. The obtained results are useful for the sustainable development of the urban environment in the context of digital transformation. They are the basis for the promising methodology of the parametric optimization of power plants using renewable energy sources.

The paper presents a vector control with two cascaded loops to improve the properties of Dynamic Voltage Restorer (DVR) to minimize Voltage Sags on the grid. Thereby, a vector controlled structure was built on the rotating dq-coordinate system with the combination of voltage control and the current control. The proposed DVR control method is modelled using MATLAB-Simulink. It is tested using balanced/unbalanced voltage sags as well as fluctuant and distorted voltages. As a result, by using this controlling method, the dynamic characteristics of the system have been improved significantly. The system performed with higher accuracy, faster response and lower distortion in the voltage sags compensation. The paper presents real time experimental results to verify the performance of the proposed method in real environments.

Due to the dramatic growth of the global population, building multi-story buildings has become a necessity, which strongly requires the installation of an elevator regardless of the type of building being built. This study focuses on households, which are the second-largest electricity consumers after the transportation sector. In residential buildings, elevators impose huge electricity costs because they are used by many consumers. The novelty of this paper is implementing a Hybrid Energy Storage System (HESS), including an ultracapacitor Energy Storage (UCES) and a Battery Energy Storage (BES) system, in order to reduce the amount of power and energy consumed by elevators in residential buildings. The control strategy of this study includes two main parts. In the first stage, an indirect field-oriented control strategy is implemented to provide new features and flexibility to the system and take benefit of the regenerative energy received from the elevator’s motor. In the second stage, a novel control strategy is proposed to control the HESS efficiently. In this context, the HESS is only fed by regenerated power so the amount of energy stored in the UC can be used to reduce peak consumption. Meanwhile, the BES supplies common electrical loads in the building, e.g., washing machines, heating services (both boiler and heat pump), and lighting, which helps to achieve a nearly zero energy building.

Currently, despite the use of renewable energy sources (RESs), distribution networks are facing problems, such as complexity and low productivity. Emerging microgrids (MGs) with RESs based on supervisory control and data acquisition (SCADA) are an effective solution to control, manage, and finally deal with these challenges. The development and success of MGs is highly dependent on the use of power electronic interfaces. The use of these interfaces is directly related to the progress of SCADA systems and communication infrastructures. The use of SCADA systems for the control and operation of MGs and active distribution networks promotes productivity and efficiency. This paper presents a real MG case study called the LAMBDA MG testbed laboratory, which has been implemented in the electrical department of the Sapienza University of Rome with a centralized energy management system (CEMS). The real-time results of the SCADA system show that a CEMS can create proper energy balance in a LAMBDA MG testbed and, consequently, minimize the exchange power of the LAMBDA MG and main grid.

The use of energy storage with high power density and fast response time at container terminals (CTs) with a power demand of tens of megawatts is one of the most critical factors for peak reduction and economic benefits. Peak shaving can balance the load demand and facilitate the participation of small power units in generation based on renewable energies. Therefore, in this paper, the economic efficiency of peak demand reduction in ship to shore (STS) cranes based on the ultracapacitor (UC) energy storage sizing has been investigated. The results show the UC energy storage significantly reduce the peak demand, increasing the load factor, load leveling, and most importantly, an outstanding reduction in power and energy cost. In fact, the suggested approach is the start point to improve reliability and reduce peak demand energy consumption.