• Energy Research

There is a growing awareness that forecasting of solar irradiance is of special importance for forecasting the power output of photovoltaic (PV) systems and thus for optimizing their operation. This work presents the development of solar irradiance and PV power output forecasting models, based on artificial neural networks (ANNs), operating with a time horizon of 24 h in order to be integrated as part of home energy management systems (HEMS). The key characteristic of the proposed approach consists of employing statistical feature parameters to reduce the size of input data, while the results obtained indicate that it provides a reasonable balance between computational requirements and forecasting accuracy of the PV power output within the considered time frame.

This paper considers the case of São Miguel in the Azores archipelago as a typical example of an isolated island with high renewable energy potential, but low baseload levels, lack of energy storage facilities, and dependence on fossil fuels that incurs high import costs. Using the Integrated MARKAL-EFOM System (TIMES), a number of scenarios are examined in order to analyze and assess the potential benefits from the implementation of a seawater pumped-storage (SPS) system, in the absence or presence of electric drive vehicles (EDVs) under a grid-to-vehicle (G2V) approach. The results obtained show that the proposed solution increases the penetration of renewable energy in the system, thus reducing the dependence on fossil fuel imports and allowing, at the same time, for the deployment of EDVs as a promising environmentally friendly alternative to conventional vehicles with internal combustion engines.

The widespread deployment of electric vehicles is typically viewed as an approach that could help decarbonize the transportation sector, which is becoming increasingly linked not only to environmental problems, but also to social issues that contribute to the degradation of the quality of life. Alternative modes of transport with the aim to increase the occupancy of private cars are emerging as a means of alleviating the problems from traffic congestion, mainly in urban areas. At the same time, the university members are often considered to be more receptive to alternative transportation services such as carsharing, compared to the general population. Considering that academic communities offer fertile ground for the promotion of innovative actions, this paper presents a preliminary survey conducted at the University of Deusto, Bilbao, Spain, that aims to explore the potential interest and willingness to adopt the use of carsharing/carpooling services and electric vehicles. The results of this exploratory study provide the indication that the population under study maintains a positive attitude towards the transition to electromobility and use of alternative modes of transportation.

The widespread deployment of electric vehicles (EVs), combined with the shift towards alternative modes of transportation, has the potential to alleviate the problems associated with the high use of private vehicles for commuting trips, mainly in urban areas. In this context, the present paper discusses a survey conducted at the University of Mons (UMONS), Belgium, in order to examine the characteristics and attitude of the students in this university community with respect to renting an electric bike (e-bike), as well as to identify the key factors that influence the use of an e-bike sharing system as integrated part of smart cities. The results of the survey indicate the preferences and intentions of the population under study to use such a system and provide some useful insight for its implementation in the city of Mons.

Carsharing has the potential to reduce the total number of cars on the road, with significant benefits to the society and the environment, while at the same time relevant studies show that university communities are often more receptive to alternative transportation services compared to the general population. With the growing interest in electromobility, as a means of decarbonizing the transportation sector, this paper considers the case of combining carsharing with electric vehicles (EVs) to serve the commuting needs of students, employees and faculty of a university in Bilbao, Spain. The aim of the present work is to conceptualize the design of the charging infrastructure of the e-carsharing system under a fast charging scheme and define its components, their attributes and interactions. To this end, a MATLAB/Simulink based simulator is developed incorporating the dynamics of a real-world scenario based on arrival and departure data from the university parking lot.

Abstract This paper presents an integrated tool to mitigate power quality issues in a microgrid through coordinating the operating schedule of its generating resources and loads. Such a microgrid includes renewable and conventional distributed energy resources, electric vehicles, energy storage, linear and nonlinear loads, while it serves as an example small-to-medium scale residential and commercial buildings. The proposed tool operates on a sequential, two-stage basis: at the first stage the energy management system (EMS) ensures that the microgrid’s generation resources and loads are dispatched at the minimum total system cost. In addition, it assesses the potential provision of flexibility services towards the system operator, relying on financially incentivized power signal requests. At the second stage, the power quality (PQ) framework evaluates whether the proposed optimal solution complies or not with several PQ standards applicable to the distribution level. The unique characteristic of the proposed tool is the self-triggered interaction between the EMS and the PQ framework, which identifies potential PQ violations, and restores the PQ indices to acceptable levels through an iterative process. Case studies have been performed with realistic model parameters to verify the performance of the proposed integrated tool. The obtained results demonstrate the effectiveness of the algorithm in managing voltage deviations, voltage unbalance, as well as harmonic distortions with a small additional cost for the total system.

Abstract The renewed interest in the deployment of electric vehicles promises enhanced environmental and social compatibility, higher energy efficiency, as well as effective power grid support through the vehicle-to-grid energy exchange mode. Focusing on a smaller scale, such as buildings with large parking lots for electric vehicles, the aim of the so-called vehicle-to-building concept is to regulate the power consumption of a building by either throttling the charging rate of electric vehicles or by delivering electricity (discharging) into the building when needed. In this paper, a mathematical model is implemented in MATLAB to peak-shave and valley-fill the power consumption profile of a university building by scheduling the charging/discharging process in an electric vehicle parking lot, using real-world data of power consumption and parking lot occupancy. The simulation of three scenarios with different number of parking spots reveal the feasibility of the proposed approach to effectively flatten the power consumption profile during daytime, which is particularly important for electricity customers that the energy cost depends on the contracted power capacity. In detail, the results indicate that the peak power consumption is reduced by approximately 3% and 20% for the scenarios with the minimum and maximum number of electric vehicle parking spots respectively.

Carpooling is a mobility concept that has the potential to effectively reduce the single occupancy trips with passenger cars, and thus energy consumption as well as traffic congestion, while coupled with electric vehicles (EVs) and intelligent transportation systems (ITS) can contribute to the smarter and more sustainable use of transportation networks as integrated part of smart cities. However, in practice, the success of carpooling systems has been limited by psychological barriers related to the level of trust for sharing a ride with strangers, and the necessity for convergence of schedules and trips for ride-matching. To this end, the present work advances the concept of a university-based carpooling system with EVs (e-carpooling), as a means of restricting the access to a closed community with a critical mass of users having the same origin/destination. In particular, this paper reports on the results of a preliminary survey conducted at University of Mons (UMONS), Belgium, in order to explore the characteristics of this user community with respect to the concepts of carpooling and electro-mobility. The results of the survey not only reveal the user preferences for the adoption of the proposed system, but also provide some useful insight for the implementation of the e-carpooling concept in the city of Mons.

Abstract This paper presents the EB (energy box) concept in the context of the V2G (vehicle-to-grid) technology to address the energy management needs of a modern residence, considering that the available infrastructure includes micro-renewable energy sources in the form of solar and wind power, the electricity loads consist of “smart” and conventional household appliances, while the battery of an EV (electric vehicle) plays the role of local storage. The problem is formulated as a multi-objective DSP (dynamic stochastic programming) model in order to maximize comfort and lifestyle preferences and minimize cost. Combining the DSP model that controls the EB operation with a neural network based approach for simulating the thermal model of a building, a set of scenarios are examined to exemplify the applicability of the proposed energy management tool. The EB is capable of working under real-time tariff and placing bids in electricity markets both as a stand-alone option and integrated in a SmartGrid paradigm, where a number of EBs are managed by an aggregator. The results obtained for the Portuguese tertiary electricity market indicate that this approach has the potential to compete as an ancillary service and sustain business with benefits for both the microgrid and residence occupants.