In an electrical microgrid, distributed renewable generation is one of the main tools used to achieve energy sustainability, cost efficiency and autonomy from the grid. However, reliance on intermittent power sources will lead to a mismatch between generation and demand, causing problems for microgrid management. Flexibility is key to reducing the mismatch and providing a stable operation. In such a context, demand response and energy storage systems are the main factors that contribute to flexibility in a microgrid. This paper provides an assessment of the technical and economic impacts of a microgrid at the building level, considering photovoltaic generation, battery energy storage and the use of electric vehicles in a vehicle-to-building system. The main novel contributions of this work are the quantification of system efficiencies and the provision of insights into the design and implementation of microgrids using real on-site data. Several tests were conducted using real on-site data to calculate the overall efficiencies of the different assets during their operation. An economic assessment was carried out to evaluate the potential benefits of coordinating battery storage with a vehicle-to-building system regarding the flexibility and cost-efficient operation of the microgrid. The results show that these two systems effectively increase the levels of self-consumption and available flexibility, but the usefulness of private electric vehicles in public buildings is constrained by the schedules and parking times of the users. Furthermore, economic benefits are highly dependent on the variability of tariffs and the costs of energy storage systems and their degradation, as well as the efficiency of the equipment used in the conversion chain.

Achieving nearly zero-energy buildings (nZEB) is one of the main objectives defined by the European Union for achieving carbon neutrality in buildings. nZEBs are heavily reliant on distributed renewable generation energy sources, which create new challenges associated with their inherent intermittency. To achieve nZEB levels, demand management plays an essential role to balance supply and demand. Since up to two-thirds of the total consumed energy in buildings is dispended for Heating, Ventilation and Air Conditioning (HVAC) operations, intelligent control of HVAC loads is of utmost importance. The present work aims to offer a solution to improve a building microgrids’ flexibility by shifting thermal loads and taking advantage of room thermal inertia. Innovation is present in using the internet of things to link several decentralized local microcontrollers with the microgrid and in the applicability of different control algorithms, such as the pre-emptive heating/cooling of a room. The developed solution relies on smart thermostats, which can be integrated into a building management system, or in a microgrid, and are capable of fulfilling the occupants’ need for comfort while complementing the building with needed power flexibility. The equipment is capable of controlling several HVAC systems to guarantee thermal and air quality comfort, as well as coordinate with a building/microgrid operator to reduce energy costs by shifting thermal loads and enacting demand control strategies. The smart thermostat uses an algorithm to calculate room inertia and to pre-emptively heat/cool a room to the desired temperature, avoiding peak hours, taking advantage of variable tariffs for electricity, or periods of solar generation surplus. The smart thermostat was integrated into a university campus microgrid and tested in live classrooms. Since the work was developed during the COVID-19 pandemic, special attention was given to the air quality features. Results show that smart HVAC control is a viable way to provide occupant comfort, as well as contribute to the integration of renewable generation and increase energy efficiency in buildings and microgrids.

Many University campuses have been decreasing the environmental impacts and costs associated with electricity consumption through the implementation of energy efficiency programs, as well as the installation of renewable energy generation. As a next step, such buildings must be equipped with technologies able to provide the flexibility required to increase the matching between renewable generation and demand in order to enable large-scale integration of renewable generation. With such objective, this paper presents a microgrid constituted by photovoltaic generation, lithium-ion battery storage, unidirectional and bi-directional charging of electric vehicles and controllers for the space conditioning systems. Such microgrid was implemented in the Department of Electrical and Computer Engineering - University of Coimbra, for supporting sustainable energy systems operation, ensuring the optimized integration of renewable generation in large buildings. Simultaneously, the microgrid enables the assessment of new smart grid solutions, acting as a testbed for the research developed on flexibility options for future power systems.

This paper presents a multi-criteria decision-making (MCDM) approach for optimizing a microgrid system to achieve Plus-Energy Building (PEB) performance at the University of Coimbra’s Electrical Engineering Department. Using Python 3.12.8, Rhino 7, and PVsyst 8.0.1, simulations considered architectural and visual constraints, with economic feasibility assessed through a TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) analysis. The system is projected to generate approximately 1 GWh annually, with a 98% probability of exceeding 1076 MWh based on Gaussian estimation. Consumption is estimated at 460 MWh, while a 3.8 MWh battery ensures up to 72 h of autonomy. Rooftop panels and green parking arrays, fixed at 13.5° and 59°, minimize visual impact while contributing a surplus of +160% energy injection (or a net surplus of +60% energy after self-consumption). Assuming a battery cost of EUR 200/kWh, each hour of energy storage for the building requires 61 kWh of extra capacity with a cost of 12,200 (EUR/hr.storage). Recognizing environmental variability, these figures represent cross-validated probabilistic estimates derived from both PVsyst and Monte Carlo simulation using Python, reinforcing confidence in system feasibility. A holistic photovoltaic optimization strategy balances technical, economic, and architectural factors, demonstrating the potential of PEBs as a sustainable energy solution for academic institutions.

The growing frequency of natural disasters has led to an increase in occurrences in which critical infrastructure and small urban centres are damaged and isolated from the main utility grid. Microgrids, with their ability to operate independently of the utility grid, offer a practical solution to mitigate the damage caused by extreme weather events. Microgrid resiliency refers to the capability of a microgrid to minimize the effects of disruptive events and ensure a stable power supply under adverse conditions. This is particularly crucial for critical infrastructures such as hospitals, communication systems, data centres, and military bases. This paper aims to propose an algorithm for the management of electric microgrids, emphasizing resiliency in critical and disaster situations. The algorithm uses the available energy resources, demand response and load shedding to prolong the duration of critical energy supply and introduces flexibility to the microgrid by being able to adjust operation modes. Additionally, a novel resiliency index is introduced to assess the performance of a microgrid under various scenarios and conditions. As a result, the resiliency of critical loads and the duration of autonomous operation are significantly improved. The proposed solution was validated through an experimental microgrid implemented as a pilot project at the University of Coimbra.

In this paper, an experimental study on the influence of the air-gap magnetomotive force spatial harmonic content on an induction motor, is presented. In the experimental tests, a 4-kW, 4-pole, 36-slot, 400-V, 50-Hz, three-phase, squirrel-cage, induction motor with reconfigurable double-layer windings was used, allowing changing the coil pitch. Three different coil pitches were tested, namely, 9/9, 8/9, and 7/9, and the motor air-gap flux and radial vibration were measured. A Fast-Fourier Transformer was then used to build the flux and vibration spectra to be analyzed for harmonics. The coil pitch of 7/9 (77.8% short pitch) led to the best results in reducing the harmonic distortion and mechanical vibration. The conducted experiments and results are thus presented on this paper.