Joaquim Meléndez

Energy communities are increasingly recognized as key actors in decentralized power systems, yet most studies focus on individual communities using synthetic datasets. This paper presents a mixed-integer linear programming framework for the day-ahead optimization of shared battery energy storage systems, applied to four real energy communities in Catalonia (Spain) using one year of measured electricity demand and photovoltaic generation data; the optimization framework has been deployed in the operational management of the physical shared BESS in one community, while modeled BESS scenarios are evaluated for the remaining communities. Furthermore, the potential benefits of coordinated operation among multiple energy communities are assessed through energy exchange and virtual battery aggregation scenarios. The optimization reduced annual electricity costs in all communities, achieving savings between 1.57\% and 5.82\% under the current tariff, while the PVPC tariff consistently increased the value of battery scheduling. Although 99.87\% of the available renewable energy surplus could theoretically be exchanged between communities, this surplus represented only 0.71\% of the aggregated annual electricity deficit, indicating that renewable surplus availability is the principal limitation to energy sharing. Coordinated battery operation increased battery utilization by approximately 13\% and provided additional economic benefits without increasing installed storage capacity. The results demonstrate that, under the current renewable penetration levels of the studied communities, the principal value of aggregation lies in improving the utilization of distributed flexibility resources rather than enabling direct energy exchange. These findings provide practical insights into the coordinated operation of real energy communities and their future evolution towards aggregator-based flexibility services.

The integration of renewable energy sources into modern power systems introduces new operational challenges for collective self-consumption schemes, especially when managing shared assets in energy communities. This study proposes a cohesive framework for forecasting and optimizing. This framework combines day-ahead load and PV generation forecasts with a Mixed-Integer Linear Programming model to schedule battery energy storage system (BESS) operation under real regulatory and technical constraints. The approach is implemented and validated in a real energy community in Catalonia, where 26 members share a hybrid PV-BESS installation. Three operational scenarios are evaluated: charging only from PV surplus, charging from total PV production, and a third scenario where the battery can charge from the grid — tested solely for comparison, since grid charging is not allowed in the actual installation. Results from several week-long windows across different seasons show that optimized operation can reduce annual electricity costs for the energy community by 15.3–31.2\%, depending on the scenario and seasonal conditions. The findings emphasize that, despite regulatory constraints limiting grid-charging capabilities, data-driven BESS scheduling can significantly enhance economic performance and local renewable consumption. Overall, this study demonstrates the practical value of combining forecasting infrastructure with optimization tools for real-world energy communities and outlines pathways for improving future profitability through enhanced flexibility services.

This paper presents the design and implementation of a Complex Order Fractional Proportional Resonant (COFPR) controller. The proposed COFPR controller is an evolution of the Fractional Proportional Resonant (FPR) controller suitable for high-frequency tracking. The best performance of the COFPR is obtained by reducing the excitation region promoted by FPR controllers and PR controllers. The COFPR is analysed in the frequency domain. For comparison purposes, Proportional Resonant with Harmonic Compensators (PRHC), FPR and COFPR controllers are designed for the current regulation of a voltage source converter. They are compared considering the same controller gains tuning criteria and also the same phase margin. A set of simulations and experimental results on a 3.6 kVA gallium nitride (GaN) inverter are discussed. The proposed COFPR controller arises superior at high frequencies when the same gains for the controllers are used. The COFPR controller can reduce excitation regions on PR controllers tuned with a similar phase margin without losing a close tracking capability. This advantage promotes COFPR as a proper alternative regarding program memory and execution time required, as it can be properly implemented within a specific frequency range by an approximation of order three or four.

This paper investigates the application of fractional proportional–resonant controllers within the voltage control loop of grid-forming inverters. The use of such controllers introduces an additional degree of freedom, enabling greater flexibility in manipulating frequency trajectories. This flexibility can be harnessed to improve tracking error and enhance disturbance rejection, particularly in applications requiring precise voltage regulation. The paper conducts a conceptual stability analysis of ideal fractional proportional–resonant controllers using the Nyquist criterion. A tuning procedure based on robustness criteria for the proposed controller is also addressed. This tuning strategy is used to compare different controllers under the same conditions. In addition, a sensitivity analysis is provided, comparing the performance of fractional proportional–resonant controllers with traditional proportional–resonant controllers equipped with harmonic compensation. The controller’s formulation and performance are validated through simulations and tested with a 20 kVA inverter under high non-linear loads. Compared to classical control approaches, the fractional tuning parameter enhances tracking performance, reduces phase delay, and improves disturbance rejection. These improvements are achieved with a controller designed to minimise computational demands in terms of memory usage and execution time.

As cities evolve, the need for systems that aid in their management becomes more necessary. Regarding traffic, and specifically the issues generated by vehicle parking, various smart parking system solutions have emerged in recent years. Although there is considerable available literature, most of it focuses on specific parts of the solution, such as providing a system architecture, analyzing types of sensors, or studying different communication methods. However, there is no proposed guide to follow for tackling the design and deployment of a comprehensive smart parking system. To address this gap, a possible workflow is proposed to guide the design and implementation of such systems. The article describes the step-by-step guide, as well as how it has been applied in the specific case of designing a limited-time paid parking system for the Girona City Council. The system aims to monitor the occupancy of various parking spaces in a zone and visibly indicate (using an LED) whether the vehicle parked in a space is within the allowed time limit or has exceeded it. It is worth noting that the city of Girona already has a LoRaWAN network, so the system development was carried out leveraging its existence. The application of the guide to the specific case is accompanied by examples of real sensors used, field measurements conducted to study user behavior, as well as radio coverage simulations and sensor network simulations that allow analysis of the effect of using message acknowledgments (ACK) or ADR. Although the use of the proposed guide is shown in a specific case, it can be easily extrapolated to other application cases.

Background: In recent years, the monitoring of occupant presence patterns has become an imperative for building energy optimization. Very often, there is a significant discrepancy between the building energy performance predicted at the design stage and the actual performance rendered during the building operation. This stems from the difference in user occupancy. In spite of this, user interaction and feedback are rarely taken into account and evidence of the impact of occupant presence patterns on energy consumption is still scarce. Thus, the purpose of this study is to apply crowd-sensing techniques to understand how energy is consumed and how appropriate performance indicators should be defined to provide inputs for building operations regarding more efficient use of resources. Methods: Monitoring strategies were implemented in an office lab with controlled variables to collect quantitative data on occupancy patterns, ambient factors and energy consumption. In addition, crowd-sensing techniques were applied to model user activity in different ambient conditions over time and to contrast their occupancy with energy consumption patterns in combination with new inquiry tools to identify how occupants perceive their comfort level. In addition, a set of energy efficiency indicators was used to compare energy performance over different periods. Results: It was discovered that there is a strong relation between user occupancy patterns and energy consumption. However, more than 50% of energy was consumed when no user activity was registered. Energy performance indicators revealed that measuring energy efficiency in terms of kWh per surface area encourages a less efficient use of space and, therefore, including a coefficient of person hours is advisable. It was also discovered that users do not fully rely on feedback mechanisms and they prefer to take action to adapt the ambient conditions rather than simply expressing their opinion. Analysis of energy usage during the Covid-19 lock down revealed substantial use of energy contrary to what was expected. This was because home computers were used as terminals only, while the actual tasks were performed on the lab computers, using remote desktop connections, which were turned on 24/7. In addition, energy consumed by each employee at his/her home should be taken into account. Moreover, a set of practical recommendations was formulated.