Giuseppe Graber

An algorithm to optimize speed profiles of the metro vehicles for minimizing energy consumption

The calculation of optimal driving speed profiles for metro vehicles that improve energy saving and, thus, reduce costs, are investigated. The optimization problem is solved in two different steps: in the first one, a Dynamic Programming Optimization (DPO) algorithm (including slopes and curves effects) is used to find a set of pseudo-optimal speed cycles; the objective is to minimize the electrical energy used for traction subject to constraints such as travel time, trip distance, acceleration limits, etc. In the second optimization step, the speed profiles set are evaluated in a simulation tool implemented to estimate the power flow among vehicles through the metro network. A test campaign monitoring the saved energy and main electric variables have been implemented and the presented results showing the effectiveness of the performance of the proposed optimization algorithm.

Siting and sizing of stationary SuperCapacitors in a Metro Network

The design of an Energy Storage System (ESS) based on SuperCapacitors (SCs) for Metro Network (MN) regenerative braking energy recovery system is investigated. A simulation tool is implemented in order to estimate the power flow among the metro vehicles and the ESSs through the MN. Several simulations are performed in order to design the number, the position along the track and the required capacity of the SCs. The energy delivered from the electric substations and the energy saved using a particular ESS configuration computed by joint sizing and siting approach are estimated to show the effectiveness of the proposed method.

Impact assessment of energy storage and electric vehicles on smart grids

The impact of non-scheduled Renewable Energy Sources on distribution networks and the forecasted deployment of Electric Vehicles can lead up to severe power quality stress (i.e. peak demand), in the next future. In order to alleviate these problems, IPP can offer a peak shaving ancillary service to DNOs by means of Energy Storage Systems (ESSs) integration, which represents a technological promising solution. Here, we analyze the sizing of ESSs, installed at the DG connection bus, by Monte Carlo simulations and assess the solutions for a real Italian MV network taking into account several proposed indices related to the ESS cost and size.

Optimal siting and sizing of stationary supercapacitors in a metro network using PSO

In this paper, we investigate the design of stationary ESSs based on supercapacitors (SCs) for metro network (MN). We implement a simulation tool in order to estimate the power flow among the metro vehicles and the ESSs through the MN. A new formulation of the ESSs siting and sizing optimisation problem is proposed and solved using particle swarm algorithm. The optimisation process minimises the energy supplied by the electrical substations and the whole ESSs capacity taking into the electrical line constraints in the metro network simulator. Several simulations are performed in order to design the number, the position along the track and the required capacity of the SCs. Using commercially available modules, a realistic design solution is compared with the theoretical one obtained by solving the optimisation algorithm. Finally, we estimate the energy delivered from the electric substations and the energy saved using the real ESSs configuration.

Application of battery auxiliary substations in 3kV railway systems

In the paper is presented an auxiliary substation equipped with battery based energy storage system (Auxiliary Battery Substation - ABS) and the benefits for railway applications are shown. The proposed solution is able to reduce the effect of the peak current and voltage drops on weak traditional 3 kV feeding line during high performance trains traction. The ABS also increase the system efficiency by recovering energy during train braking phase and making it available again at the next starting time, minimizing the energy required to the main substation. An extensive simulation framework is performed on a real Italian 3 kV DC railway system feeding a new generation high speed train where the ABS supports conventional supply system. The simulation results confirm the effectiveness of the ABS in terms of peak current reduction and voltage drops compensation. Finally, The ABS allows reducing losses and increasing the energy saving in the railway feeding line.

Performance comparison between scheduling strategies for PEVs charging in smart grids

Electric vehicles (EVs) are emerging as the future of transportation systems aimed at reducing greenhouse gas emissions and fossil fuel dependence in the transportation sector. The deepening penetration of Plug-in EVs (PEVs) forecasted for the incoming years could cause significant strain on distribution networks (DNs), as well as the need to address the growing energy demand. In order to limit the negative drawbacks associated with PEVs energy demand and to properly address related issues, in the paper we consider an energy-packet based (EPB) scheduling approach for PEVs charging, comparing its performance with a conventional charging approach. We formulate an optimization framework in order to reduce the overall peak power demand and to maximize fully charged PEVs during their declared parking time. We compare the performance among the scheduling approaches by running simulations on a real DN and using real vehicle parking data.

Generation Rescheduling and Load Shedding in Distribution Systems Under Imprecise Information

Microgrids represent a smart solution to increase power system reliability through the development of self-supplied islands that integrate distributed power generation and other smart technologies. In this paper, we formulate and solve an optimal generation rescheduling and load shedding problem in microgrids to determine a stable equilibrium state following outages. To address this problem, focused on MV distribution systems, we use a new methodology based on the use of fuzzy numbers is proposed. The approach allows representing the sources of uncertainty in the data or approximations made during the computation and considering many possible scenarios in case of outages. In order to demonstrate the performance and the effectiveness of the proposed method, several simulations have been carried out on a 69-bus radial distribution system, and results have been compared with those obtained by using a stochastic optimization approach. The encouraging results are presented and discussed.

A power split control algorithm for fuel cell electric vehicles using batteries or supercapacitors as auxiliary storage system

In recent years there is growing interest for fuel cell electric vehicles (FCVs) as electric battery technology fails to date to ensure an autonomy comparable to that of conventional vehicles. An FCV requires an auxiliary storage system to cope with peak power demand and to recovery of braking energy. In the paper, we propose a power split control algorithm able to manage the power flow between fuel cell and the auxiliary storage system according to their dynamic behavior. In particular, we define the lumped resistance of fuel cell, lithium battery and supercapacitor in order to estimate their maximum allowed current variation. In order to show the effectiveness of the proposed approach, we test the power split control algorithm by using different drive cycle. Several simulation results are presented and discussed.

A stochastic approach to size EV charging stations with support of second life battery storage systems

This paper proposes a stochastic approach to determine the number of different types of charging stations for electric vehicles (EVs) in urban parking lots: our approach minimize annual cost of energy (ACOE) while ensuring a good satisfaction level for EV users. The proposed method takes also into account a stationary energy storage system that supports the EV parking lot and consists of traction batteries no longer usable by EVs, but still performing in their so-called second life. The effectiveness of the proposed sizing method is shown by simulation results characterized by real data, gathered in the European research project CO.S.MO. By using Monte Carlo simulations, we verified the features of the electric parking lot in terms of probability that all charging stations are busy and the average waiting time to start a new charging session.

Experimental validation of a steady-state metro network simulator for eco-drive operations

In this paper, we propose a validation procedure of energy consumption patterns implemented in a steady-state railway system software simulator by using experimental measured data. The software tool is able to evaluate the energy supplied by the feeding line to move a metro vehicle implementing different speed profiles. In particular, we suggest a simply methodology aimed to calibrate the metro system models by minimizing the mean squared error (MSE) between the estimate values of the model parameters and the real ones. The optimization problem we formulated, takes into account the equality constraints between the measured energy consumption at specific instants, and that computed by the software simulator. The effectiveness of this energy validation procedure is showed on a real case study comparing the energy consumption of metro vehicle implementing eco-drive speed profiles. The encouraging results are presented and discussed.