A new strategy of energy management between battery and supercapacitors for an urban electric vehicle is suggested in this paper. These two sources are connected in parallel to the DC bus through two bidirectional DC-DC converters enabling separate control over the power flow of each source. Vehicle dynamics with load torque applied on the shaft motor is to be considered. This strategy of energy management permits dividing energy between the two sources depending on the state of charge of each source as well as on the vehicle displacement state such as stopping, acceleration, cruising down and uphill, and deceleration. The aim of the proposed strategy is the best use of energy through maximizing the use of SCs by transferring energy from batteries to SCs during the standstill phase or when the load applied to the vehicle is small; supercapacitors will then be ready in critical situations such as rapid acceleration or in high hills climbing. In order to validate the control design and evaluate our energy management strategy performance, a simulation of an urban hybrid electric vehicle movement with the Matlab/Simulink software is implemented.
In this study, an Autoregressive with eXogenous input (ARX) model and an Autoregressive Moving Average with eXogenous input (ARMAX) model are developed to predict the overhead temperature of a distillation column. The model parameters are estimated using the recursive algorithms. In order to select an optimal model for the process, different performance measures, such as Aikeke's Information Criterion (AIC), Root Mean Square Error (RMSE), and Nash–Sutcliffe Efficiency (NSE), are calculated.
Purpose. In last decade the problem of energy management system (EMS) for electric network has received special attention from academic researchers and electricity companies. In this paper, a new algorithm for EMS of a photovoltaic (PV) grid connected system, combined to an storage system is proposed for reducing the character of intermittence of PVs power which infect the stability of electric grid. In simulation model, the PV system and the energy storage system are connected to the same DC bus, whereas EMS controls the power flow from the PV generator to the grid based on the predetermined level of PV power. In the case where the PV power is less than the predefined threshold, energy is stored in the batteries banc which will be employed in the peak energy demand (PED) times. Otherwise, it continues to feed the principal grid. The novelty of the proposed work lies in a new algorithm (smart algorithm) able to determine the most suitable (optimal) hours to switching between battery, Solar PVs, and principal grid based on historical consumption data and also determine the optimal amount of storage energy that be injected during the peak demand. Methods. The solution of the problem was implemented in the Matlab R2010a Platform and the simulation conducted on Laptop with a 2.5 GHz processor and 4 GB RAM. Results. Simulation results show that the proposed model schedules the time ON/OFF of the switch in the most optimal way, resulting in absolute control of power electric path, i.e. precise adaptation at the peak without compromising consumers comfort. In addition, other useful results can be directly obtained from the developed scheme. Thus, the results confirm the superiority of the proposed strategy compared to other improved techniques.
This paper aims to elaborate a local energy management and coordinated control of a 15 kW Standalone Active PV Generator (SAAPG), dedicated to the electrical supply of a remote farm in southern Algeria. The SAAPG is composed of four sources: Photovoltaics, Lead Acid Batteries, Ultra-capacitors, and Diesel generators (DGs); all these sources are coupled together in the DC-link (VDC-ref = 700 V). This agricultural area is mainly equipped with unpredictable high dynamic (transient) loads composed of two cold room compressors, an immersed pump and a watering pump. Unlike usual, a DC side coupling structure of the DG is proposed in this paper in order to ensure two dominant advantages: the first one is to slow the dynamics of the DG output power, which will be imposed by the DG boost converter instead of the load (like AC side coupling), allowing a low maintenance frequency in the diesel engine by reducing thermo-mechanical stresses in diesel engine cylinder heads due to transients. The second one guarantees both efficiency and cost effectiveness of the system by operating the DG near to its rated power in either transient or steady state conditions, and thus, such an oversizing of the DG will be avoided unlike the AC coupling case. The four power sources are managed in coordination, according to their dynamics, to maintain the DC-link voltage value regulated around its reference. A three-phase DC-AC PWM converter operates independently considering the DC link as a fixed DC source voltage in order to power supply AC loads.
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