Dimitrios Thomas

Implementation of an e-bike sharing system: The effect on low voltage network using pv and smart charging stations

Nowadays distribution systems are becoming more and more complicated mainly due to the new methods of producing and storing electricity (PV, fuel cells, battery storage systems) as well as due to the new tensions of consuming electric energy (smart appliances, e-vehicles, e-bikes, etc.). Uncertainty in load, generation, and cost requires modeling power systems with a probabilistic approach. In such a way, the probabilistic nature of demand side management (DSM) problem can also be addressed. This work presents the design of an e-bike sharing system, in terms of system components and user mobility patterns. The integration of the designed system in the Low Voltage (LV) grid is simulated with a probabilistic analysis framework that uses real smart metering (SM) data. The stochastic character of the loading parameters at the network nodes is studied taking into account the charging energy needs of the proposed e-bikes sharing system. PV generation produced on the parking roof of the e-bikes smart charging stations (SCS) along with the energy stored in a local battery is also studied.

Simulation and design of a fast charging battery station in a parking lot of an e-carsharing system

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.

Effect of electric vehicles' optimal charging-discharging schedule on a building's electricity cost demand considering low voltage network constraints

Nowadays, one of the dominant reasons of excessive energy consumption is the high energy demand in corporate and/or public buildings. At the same time, electric vehicles (EVs) are becoming more and more popular worldwide being a considerable alternative power source when parked. In this work we initially propose an energy management framework which optimizes the control of the charging-discharging schedule of a fleet of EVs arriving at a university building for two typical load-days in February and May aiming at the minimization of the energy demand and, thus, the electricity cost of the building. To this end, a mixed integer linear programing (MILP) model containing binary and continuous variables was developed. Uncertainties in load, generation, and cost require modeling power systems with a probabilistic approach. In such a way, the probabilistic nature of demand side management (DSM) problem is also possible to be addressed. The integration of the EVs in the Low Voltage (LV) grid is simulated with a probabilistic analysis framework that uses real smart metering (SM) data. The stochastic character of the loading parameters at the network nodes is studied taking into account the charging energy needs of the corresponding EVs fleet.

A scheduling optimization model for minimizing the energy demand of a building using electric vehicles and a micro-turbine

High energy demand in corporate and/or public buildings is nowadays one of the main reasons of excessive energy consumption. At the same time, electric vehicles (EVs) have become very popular worldwide being a considerable alternative power source when parked. In this work we propose a scheduling mechanism which optimizes the control of the charging-discharging schedule of an altered but finite number of EVs arriving at a university building for a typical load-day in February aiming at the minimization of the energy demand and the electricity cost of the building. In the aforementioned framework, a parallel operation of a small sized gas turbine generator (GGT) is considered. To this end, a mixed integer linear programing (MILP) model containing binary and continuous variables has been developed to optimize the control process and minimize energy cost. Results showed that the use of the EVs as an alternative energy source can significantly contribute to the reduction of the buildings energy demand leading to important cost decrease. The exploitation of the energy produced by the GGT further contributed to the minimization of the total energy consumption of the building and the total electricity cost.

Coupling building thermal network and control system, the first step to smart buildings

Buildings are one of the main energy consumer and carbon emission sources in European countries. Population growth in cities may be effective for economic growth, but by considering overpopulated cities, making new efficient buildings and optimizing energy consumption in older ones may be a good solution for energy management and carbon reduction in them. For doing this, one needs to collect buildings data for months to get an idea about the energy consumption in a building. On the other hand, computer simulations may not provide very accurate results, but they can give a crude idea about energy consumption in buildings. There are many different tools to simulate energy consumption in buildings, among all of them simplified models provide fast and accurate results. Developing building model based on lumped capacitance method by means of resistance-capacitance (RC) circuits provides good results and a comprehensive schematic about the heat transfer in the building. In this paper, the application of thermal networks for building load calculation is introduced and it will be shown how effectively it can be used in control systems to make a smart building.