Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions

Sundareswaran, K.; Kumar, Vikash; Palani, S.

doi:10.1016/j.renene.2014.09.044

Cited by 196 publications

(115 citation statements)

References 17 publications

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“…control, Particle swarm optimization… [15]- [18] However, in the second category we find: Incremental Conductance Perturbation , Fractional Open-Circuit Voltage, and the most widely used technique is Perturb and Observe (P&O) algorithms due to its simplicity and fast response [13], [14], [19]. In addition, a comparison between conventional and intelligent MPPT techniques are investigated in [20], [21]. For more investigation, some interesting papers review nearly all known MPPT techniques and give a comparative between their advantages and disadvantages are in [22]- [24] …”

Section: Pv System With Mppt Controlmentioning

confidence: 99%

A technological review on electric vehicle DC charging stations using photovoltaic sources

Cheddadi

Errahimi

Es-Sbai

et al. 2018

IOP Conf. Ser.: Mater. Sci. Eng.

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Abstract.Within the next few years, Electrified vehicles are destined to become the essential component of the transport field. Consequently, the charging infrastructure should be developed in the same time. Among this substructure, Charging stations photovoltaic-assisted are attracting a substantial interest due to increased environmental awareness, cost reduction and rise in efficiency of the PV modules. The intention of this paper is to review the technological status of Photovoltaic-Electric vehicle (PV-EV) charging stations during the last decade. The PV-EV charging station is divided into two categories, which are PV-grid and PVstandalone charging systems. From a practical point view, the distinction between the two architectures is the bidirectional inverter, which is added to link the station to the smart grid. The technological infrastructure includes the common hardware components of every station, namely: PV array, dc-dc converter provided with MPPT control, energy storage unit, bidirectional dc charger and inverter. We investigate, compare and evaluate many valuable researches that contain the design and control of PV-EV charging system. Additionally, this concise overview reports the studies that include charging standards, the power converters topologies that focus on the adoption of Vehicle-to grid technology and the control for both PV-grid and PV standalone DC charging systems.

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Section: Pv System With Mppt Controlmentioning

confidence: 99%

A technological review on electric vehicle DC charging stations using photovoltaic sources

Cheddadi

Errahimi

Es-Sbai

et al. 2018

IOP Conf. Ser.: Mater. Sci. Eng.

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show abstract

“…They found that SOA is more effective than either BFO or GA in finding the optimal transient performance [7]. Swarm intelligence with PO algorithm was proposed and analyized oscillations in the output power, voltage and current of the PV system [8]. Perturbation and observation (P&O) method was proposed to track the MPPT of PV system for getting maximum system efficiency and obtained maximum power of PV system when compare with traditional P & O [9].…”

Section: Introductionmentioning

confidence: 99%

Optimization of photovoltaic power system: a comparative study

Дабра

Paliwal

Sharma

et al. 2017

Prot Control Mod Power Syst

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This paper presents a comparative study of P&O, fuzzy P&O and BPSO fuzzy P&O control methods by using MATLAB software for optimizing the power output of the solar PV grid array. The voltage, power output and the duty cycle of the solar PV array are well presented and analyzed with an algorithm. The model consists of 66 PV Cells connected parallel and 5 PV cells connected in series to make solar PV array. The BPSO Fuzzy method generates 43.4820 MW output power more than P&O method and 150 KW more than P&O fuzzy method. This also shows that the time response of the photovoltaic system reduces to perturbations and insures the continuity of the operation at the time in response to the continued maximum power point. It also eliminates the fluctuations around MPPT. Simulation results also revealed that BPSO fuzzy P&O controller is more effective as compare with P&O and fuzzy P&O models.

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“…In the last decade, several researchers have compared various MPPT techniques [9,10], focusing on the P-V characteristics [11][12][13][14][15], models [16][17][18][19], and methods [20][21][22][23][24][25][26][27][28][29][30][31][32][33] to track the maximum power of PV modules/arrays under partial shading conditions (PSC). The research on the PV output characteristics is mainly focused on the analysis of failure, power loss, and voltage variations in the MPPT method under the PSC.…”

Section: Introductionmentioning

confidence: 99%

“…Then, the traditional method is used to track the MPP [23][24][25][26]. The advantage of the methods in this category is that they can reduce the traversal region; however, they have a higher dependency on the analysis of the local shadow models and output characteristics, which means that the determination of the MPP region is difficult and the robustness is poor.…”

Section: Introductionmentioning

confidence: 99%

Analysis of MPPT Failure and Development of an Augmented Nonlinear Controller for MPPT of Photovoltaic Systems under Partial Shading Conditions

Chen¹,

Ma²,

Wu³

et al. 2017

Applied Sciences

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Abstract:The output-voltage-power curves of photovoltaic (PV) arrays exhibit complex multi-peak shapes when local shading occurs. The existing maximum power point tracking (MPPT) algorithms to solve this multi-peak problem do not consider the possibility of tracking failures due to the time of the irradiance change. In this study, first, the reason for the failure of the global MPPT (GMPPT) algorithm is analyzed based on the PV array mathematical model and its output characteristics under partial shading conditions; then, in order to estimate the MPP voltage, an artificial neural network (ANN) is trained using environmental information such as irradiance. A hybrid MPPT method using an augmented state feedback precise linearization (AFL) controller combined with an ANN is proposed to solve problems such as the shift of the static operating point of the DC/DC boost converter. Finally, numerical simulations are conducted to validate the proposed method and eliminate the possibility of MPPT failure. The proposed hybrid MPPT method is compared with the conventional perturb and observe (P & O) method and the improved P & O method through simulations. Using the proposed neural network and nonlinear control strategy, the MPP can be tracked rapidly, accurately, and statically, proving that the method is feasible and effective.

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Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions

Cited by 196 publications

References 17 publications

A technological review on electric vehicle DC charging stations using photovoltaic sources

A technological review on electric vehicle DC charging stations using photovoltaic sources

Optimization of photovoltaic power system: a comparative study

Analysis of MPPT Failure and Development of an Augmented Nonlinear Controller for MPPT of Photovoltaic Systems under Partial Shading Conditions

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