In this paper, an optimal energy management strategy (EMS) for a light rail vehicle with an onboard energy storage system (ESS) combining batteries (BT) and supercapacitors (SC) is presented. The optimal operating targets for the proposed EMS and ESS sizing (BT+SC) are obtained by multiobjective (MO) optimization with genetic algorithms. The MO fitness function is expressed in economic terms and includes the cost of the energy absorbed from the catenary, as well as the operating cost of the BT and SC pack (initial investment and cycling cost). The case study selected is the tramway of Seville. The aim is to minimize the daily operating cost of the tramway, taking into account the fulfillment of the tramway performance in the catenary-less zone and the BT-SC degradation by cycling during operation. Furthermore, a sizing analysis is done by comparing the current scenario (SC-based) with the proposed approach (optimal EMS and sizing) in terms of daily operating cost reduction.

Energy storage systems (ESS) integration with large-scale photovoltaic (PV) power plants, named intelligent PV (IPV) power plant, could contribute to improving the viability of these plants and to provide ancillary services to the main grid. The number and extension of the provided services depend not only on the size of the ESS, but also on the manner in which this storage system is managed. In this paper, the market participation based on different firming control strategies of an IPV power plant is proposed to optimize the economic exploitation based on the storage system management considering PV generation predictions. The most appropriate firming control strategy is selected to participate on the daily market, which is strengthened with an online model predictive control (MPC) to compensate the PV prediction errors participating in the intraday market. The real operation of the Iberian Peninsula market integration is also explained and analyzed. The development of this management strategy considers as a case study a real IPV plant located in Tudela (Navarre, Spain) and owned by Acciona Energía, which included a Lithium-ion based ESS from 2012 to 2013 in the framework of a European project. The results show that considering the MPC approach, an increase around 20% in the benefits is obtained by comparing with the daily market participation.

In this paper an optimal energy management strategy (EMS) for a light rail vehicle with an onboard energy storage system combining battery (BT) and supercapacitor (SC) is presented. The optimal targets for the proposed EMS are obtained by an optimization process with multi-objective genetic algorithms (GA). The fitness functions are expressed in economic terms, and correspond to the costs related to the energy absorbed from the catenary as well as the BT and SC cycling cost. The case study selected is the tramway of Sevilla. The aim was to minimize the daily operating cost of the tramway taking into account the BT and SC degradation approach and fulfilling the performance of the tramway in the catenary-less zone. A sizing analysis is done taking as optimization variables the BT and SC sizing to evaluate the impact on the daily operating cost. A comparison between the optimal solutions and a base scenario is presented.

This paper is focused on a series hybrid electric bus (SHEB). A rule-based energy management strategy is proposed by controlling the state of charge (SOC) of the battery (BT) and a variable output control for the auxiliary power unit (APU). Furthermore, a power splitter control is developed to split the power among BT and supercapacitor (SC). The optimization to obtain the values for the control levels is carried out with multi-objective genetic algorithm (GA). The aim of the optimization is to minimize the daily operating cost of the bus. The objective functions are the costs related to fuel and energy (BT and SC degradation by cycling cost, recharge from the grid cost) consumption. The results are given in a Pareto front with a set of optimal solutions, the optimal one will depend of an analysis on which objective has priority to be minimized and what are the consequences of this decision on the other one.

Energy management in hybrid and electric vehicles is a key factor to improve the operational performance and meet the efficiency objectives defined in the transport sector. Thus, optimized energy management strategies (EMS), before being integrated in a real system, need to be experimentally validated in test-bench platforms in order to identify the possible deviations from the expected simulation-based performance. This way, minimizing the time needed for implementation and field-test on the real application. An economical and flexible mean of validating these strategies is the Hardware-in-the-loop (HIL) simulation. Therefore, this work aims to present the design approach and comparison, by means of experimental tests, of two optimized (simulation-based) EMSs proposed for a hybrid electric bus (HEB) focusing on the real-time operational performance. Both EMSs handle the proper power split behaviour of the vehicle demand among a genset (internal combustion engine + electric generator) and a hybrid energy storage system (combining Li-ion batteries with super-capacitors). The experimental platform consists in a scaled test-bench emulating the electrical DC grid of a HEB. This test-bench, combined with software models to control the power electronic devices, allows to emulate the real behaviour of the genset, battery, super-capacitor, traction and auxiliary loads.