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ردیف | عنوان | نوع |
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1 |
Optimal energy management for a grid connected PV-battery system
مدیریت بهینه انرژی برای سیستم باتری PV متصل به شبکه-2020 The increase demand for electricity and the non-renewable nature of fossil energy makes the move towards renewable
energies required. However, the common problem of renewable sources, which is the intermittence, is overcome by the
hybridization of complementary sources. Thus, whenever the load demand is not fully covered by the primary source, the
second one will absolutely support it.
Furthermore, the production, the interaction with the grid and the storage system must be managed by the grid-connected
hybrid renewable energy system, which is the main objective of this paper. Indeed, we propose a new system of a grid-connected
PV-battery, which can manage its energy flows via an optimal management algorithm. The DC bus source connection topology
in our proposed hybrid architecture tackles the synchronization issues between sources when the load is powered. We consider
in this work that choosing a battery discharge and charge limiting power provides an extension of the battery life. On the other
hand, we simulated the dynamic behavior of the architecture’s various components according to their mathematical modeling.
Following this, an energy management algorithm was proposed, and simulated using MATLAB/SIMULINK to serve the load.
The results have shown that the load was served in all cases, taking into account the electrical behavior of the inhabitants as
well as the weather changes on a typical day. Indeed, the load was served either by instant solar production between sunrise
and sunset, or the recovery from sunset to 10pm, which could be a stored or injected energy without exceeding the 1000W
per hour Keywords: Renewable energy | PV-battery | Hybrid renewable system | Energy management | Hybrid architecture |
مقاله انگلیسی |
2 |
A new Exponentially Expanded Robust Random Vector Functional Link Network based MPPT model for Local Energy Management of PV-Battery Energy Storage Integrated Microgrid
یک مدل جدید MPPT مبتنی بر شبکه پیوندی کاربردی وکتور قدرتمند و توسعه یافته با استفاده از نمادهای جدید ، برای مدیریت انرژی محلی با استفاده از PV باتری ذخیره سازی میکروگرید یکپارچه-2020 In this paper a new Maximum Power Point Tracking (MPPT) model is presented for Local Energy Management
(LEM) of a multiple Photovoltaic (PV) based microgrid. To detect accurate MPP references under local
uncertainties, a non-iterative Linear Recurrence Relationship (LRR) based PV model is incorporated with PV
penetration index. A robust, accurate and fast Exponentially Expanded Robust Random Vector Functional Link
network (EE-RRVFLN) based MPPT algorithm is constructed with an exponentially expansion unit to address
positive dynamic volatility and a direct link relationship to address null vs. positive volatility in PV data. The
robustness is further incorporated by a maximum likelihood estimator using Huber’s cost function, where both
input and output weights are optimally estimated by targeting reduction in MPP tracking error. An Assessment
Index (i.e. MPPT error related) based Distributed Adaptive Droop (DAD) mechanism is suggested as Primary
Controller (PC) for effective power sharing among multiple PVs. A detailed case study is presented to evaluate
the accuracy of the proposed model in MATLAB simulation, as well as in dSPACE 1104 based Hardware-in-
Loop (HIL) platform. Historical data for different intervals/ seasons, partial shading, improved LEM validations
(simulation and HIL) are considered as different cases to establish the excellence of the proposed approach,
as compared with conventional Functional Link Neural Network (FLNN) and Random Vector Functional Link
Neural Network (RVFLNN). Keywords: Distributed adaptive droop | Exponentially Expanded Robust Random | Vector functional Link Network | Local Energy Management | Maximum power point tracking | Photovoltaic systems |
مقاله انگلیسی |