相关论文: A Rprop-Neural-Network-Based PV Maximum Power Poin…

This paper proposes a computationally efficient, real-time maximum power point tracking (MPPT) algorithm tailored for low-power photovoltaic (PV) systems operating under fast-changing irradiance and partial shading conditions (PSC). The…

P-V characteristic of photovoltaic (PV) arrays under partially shaded conditions (PSC) has multiple peaks, and conventional maximum power point tracking (MPPT) algorithms may fail to track the global maximum power point (GMPP) because of…

A revised Incremental Conductance (IncCond) maximum power point tracking (MPPT) algorithm for PV generation systems is proposed in this paper. The commonly adopted traditional IncCond method uses a constant step size for voltage adjustment…

This paper presents a fast power-setpoint tracking algorithm to enable utility-scale photovoltaic (PV) systems to provide high quality grid services such as power reserves and fast frequency response. The algorithm unites maximum…

This paper proposes a novel topology for grid connected photovoltaic (PV) system based on modular multilevel converter (MMC). In this topology, a PV array is connected to capacitors of each submodule (SM) of the MMC through a DC-DC boost…

The performance of a photovoltaic system is subject to varying environmental conditions, and it becomes more challenging to track the maximum power point (MPP) and maintain the optimal performance when partial shading occurs. In this paper,…

One of the most important issues in the operation of a photovoltaic (PV) system is extracting maximum power from the PV array, especially in partial shading condition (PSC). Under PSC, P-V characteristic of PV arrays will have multiple peak…

The increasing electricity demand and the need for clean and renewable energy resources to satisfy this demand in a cost-effective manner, imposes new challenges on researchers and developers to maximize the output of these renewable…

This paper presents an algorithm for power curtail-ment of photovoltaic (PV) systems under fast solar irradiance intermittency. Based on the Perturb and Observe (P&O) technique, the method contains an adaptive gain that is compensated in…

In this paper, we proposed a method using supervised ML in solar PV system for MPPT analysis. For this purpose, an overall schematic diagram of a PV system is designed and simulated to create a dataset in MATLAB/ Simulink. Thus, by…

Solar energy utilization in places like Nepal, is often obstructed by unpredicted environmental factors and existing technological barriers. The challenges encountered often result in fluctuating energy outputs, hindering the transition to…

We present a nonlinear equivalent resistance tracking method to optimize the power output for solar arrays. Tracking an equivalent resistance results in nonlinear voltage step sizes in the gradient descent search loop. We introduce a new…

Using Photovoltaic systems is gradually expanded by increasing energy demand. Abundance and availability of this energy, has turned to one of the most important sources of renewable energy. Unfortunately, photovoltaic systems have two big…

Introduction. This article deals with the optimization of the energy conversion of a grid-connected photovoltaic system. The novelty is to develop an intelligent maximum power point tracking technique using artificial neural network…

Extracting maximum power available from photovoltaic arrays requires the system operating at the maximum power point (MPP). Therefore, finding the MPP is necessary for efficient operation of PV arrays. The MPP changes with multiple…

This article presents a study on the application of artificial neural networks (ANNs) for maximum power point tracking (MPPT) in photovoltaic (PV) systems using low-cost pyranometer sensors. The proposed approach integrates pyranometers,…

This paper presents design of a Maximum Power Point Tracking (MPPT) circuit and its functionality for tuning the maximum power transfer from an energy harvester (EH) unit. Simple and practical Perturb and Observe algorithm is investigated…

In this paper, a neural-network (NN)-based online optimal control method (NN-OPT) is proposed for ultra-capacitors (UCs) energy storage system (ESS) in hybrid AC/DC microgrids involving multiple distributed generations (e.g., Photovoltaic…

This paper proposes an improved deep learning based maximum power point tracking (MPPT) in solar photovoltaic cells considering various time series based environmental inputs. Generally, artificial neural network based MPPT algorithms use…

Under Partial shading conditions (PSC), traditional MPPT methods such as, P&O, IncCon and SMC, cannot track down the Global MPP. Thus, the energy conversion of the PV modules will decrease. To overcome this drawback, two evolutionary…