Design of UPQC with Solar PV and Battery Storage Systems for Power Quality Improvement

Srilakshmi, Koganti; Jyothi, K. Krishna; Kalyani, Gade; Goud, Y. Sai Prakash

doi:10.1080/01969722.2023.2175144

Cited by 4 publications

(4 citation statements)

References 31 publications

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“…However, the hybrid fuzzy-sliding mode control (HFSMC) based maximum-power-point tracking system (MPPTs) is adopted for solar PV system to extract maximum output (Srilakshmi et al, 2023). Besides, the design of Unified Power Quality Conditioner (UPQC) through the optimal selection of the active filter and PID Controller parameters using the enhanced most valuable player algorithm (EMVPA) was suggested to handle PQ issues (SrilakshmiKoganti et al, 2024).…”

Section: Modes Of Operation Action Takenmentioning

confidence: 99%

Simulation of grid/standalone solar energy supplied reduced switch converter with optimal fuzzy logic controller using golden BallAlgorithm

Srilakshmi,

Sundaragiri,

Gaddameedhi

et al. 2024

Front. Energy Res.

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This article presents the utilization of a shunt active power filter (SHAPF) in combination with an Energy Storage System (ESS) and a Solar Energy System (SES). Voltage source converters (VSC) are connected in parallel to a direct current (DC) bus. The membership function (MSF) of fuzzy logic controller (FLC) for the shunt control system is optimally adjusted using the golden balloptimization algorithm (GBOA). The present effort aims to achieve the following primary objectives: 1) Quick implementation to stabilize the voltage of the DC Link capacitor (DCLCV); 2) Mitigation of harmonics and improvement of power factor (PF); 3) Satisfactory performance under load as well as solar power varying conditions. The effectiveness of the optimally designed controller is evaluated by studying four test scenarios with grid and standalone conditions. The results are then compared to the existing sliding mode (SMC) and fuzzy logic controllers (FLC).

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Section: Modes Of Operation Action Takenmentioning

confidence: 99%

Simulation of grid/standalone solar energy supplied reduced switch converter with optimal fuzzy logic controller using golden BallAlgorithm

Srilakshmi,

Sundaragiri,

Gaddameedhi

et al. 2024

Front. Energy Res.

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“…Moreover, the fuzzy-based hybrid technique was adopted to achieve the maximum out of the photovoltaics (PVs). However, to reduce complexity, the ANN was considered for UPQC reference signal generation to solve PQ issues (Srilakshmi et al, 2023). To reduce the current total harmonic distortion (THD), the intelligent fuzzy-tuned PIC was created for the hybrid shunt active and passive filters.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Figure 3 illustrates the PV cell properties for a fixed temperature and changing irradiance. The incremental conductance-based MPPT is adopted to extract the maximum output from the PV system (Srilakshmi et al, 2023):…”

Section: External Support For 5l-mupqc At the DC Linkmentioning

confidence: 99%

Green energy-sourced AI-controlled multilevel UPQC parameter selection using football game optimization

Srilakshmi,

Rao,

Balachandran

et al. 2024

Front. Energy Res.

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The power quality (PQ) has been significantly affected by the integration of intermittent non-conventional sources (NCS) into the local distribution system in addition to the adoption of power electronic technologies to regulate non-linear loads. This article combines the H-bridge cascade five-level unified power quality conditioner (5L-UPQC) with the wind power generation system (WPGS), solar photovoltaic power generation system (SPVGS), and battery storage system (BSS) as an effective approach to address PQ problems. The utilization of the Levenberg–Marquardt backpropagation (LMBP)-trained Artificial neural network controller (ANNC) in the UPQC is recommended for generating appropriate reference signals for the converters. This eliminates the requirement for conventional complex conversions, such as abc, dq0, and αβ. Moreover, the artificial neuro-fuzzy interface system (ANFIS) is recommended for achieving a DC-link balance. Football game optimization (FBGO) is utilized to determine the optimal shunt and series filter characteristics. The major objectives of the proposed system are to reduce the current waveform irregularities, resulting in a decrease in the total harmonic distortion (THD), an enhancement in the power factor (PF), the mitigation of supply voltage imbalances and disturbances, and the maintenance of a steady direct-current link capacitor voltage (DLCV), despite the variations in the load, solar irradiation, and wind velocity. The efficiency of the suggested strategy is assessed using four case studies that involve different loads, variable wind velocities, and source voltage balancing conditions. Based on the simulation studies and obtained results, the suggested method significantly decreases the THD to values of 2.91%, 3.63%, 3.75%, and 3.50%. Additionally, it achieves a power factor of unity, which is considerably lower compared to other multilevel schemes that use the traditional symmetrical reference frame (SRF) and instantaneous reactive power (pq) methods. This design has been executed using the MATLAB/Simulink program.

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“…A feed-forward ANN was created for the wind system and solar PV systems of UPQC to maintain the DLCV steady and regulate the electricity [11]. To solve PQ issues, a novel neural network signal production method was proposed for the fuzzy controller-operated MPPT for PV-connected UPQC [12]. In order to efectively handle PQ difculties, a UPQC custom device with a multilevel converter was connected to the fuel cell combined PV and wind systems based microgrid in the near future [13].…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Neuro-Fuzzy Controller Design and Selection of Filter Parameters of UPQC Using Predator Prey Firefly and Enhanced Harmony Search Optimization

Srilakshmi,

Rao,

Swarnasri

et al. 2024

International Transactions on Electrical Energy Systems

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This research introduces a unified power quality conditioner (UPQC) that integrates solar photovoltaic (PV) system and battery energy systems (SBES) to address power quality (PQ) issues. The reference signals for voltage source converters of UPQC are produced by the Levenberg–Marquardt back propagation (LMBP) trained artificial neural network control (ANNC). This method removes the necessity for conventional dq0, abc complex shifting. Moreover, the optimal choice of parameters for the adaptive neuro-fuzzy inference system (ANFIS) was achieved through the integration of the enhanced harmony search algorithm (EHSA) and the predator-prey-based firefly algorithm (PPFA) in the form of the hybrid metaheuristic algorithm (PPF-EHSA). In addition, the algorithm is employed to optimize the selection of resistance and inductance values for the filters in UPQC. The primary objective of the ANNC with predator-prey-based firefly algorithm and enhanced harmony search algorithm (PPF-EHSA) is to enhance the stability of the DC-link capacitor voltage (DLCV) with reduced settling time amid changes in load, solar irradiation (G), and temperature (T). Moreover, the algorithm seeks to achieve a reduction in total harmonic distortion (THD) and enhance power factor (PF). The method also focuses on mitigating fluctuations such as swell, harmonics, and sag and also unbalances at the grid voltage. The proposed approach is examined through four distinct cases involving various permutations of loads and sun irradiation (G). However, in order to demonstrate the performance of the suggested approach, a comparison is conducted with the ant colony and genetic algorithms, i.e., (ACA) (GA), as well as the standard methods of synchronous reference frame (SRF) and instantaneous active and reactive power theory (p-q). The results clearly demonstrate that the proposed method exhibits a reduced mean square error (MSE) of 0.02107 and a lower total harmonic distortion (THD) of 2.06% compared to alternative methods.

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Design of UPQC with Solar PV and Battery Storage Systems for Power Quality Improvement

Cited by 4 publications

References 31 publications

Simulation of grid/standalone solar energy supplied reduced switch converter with optimal fuzzy logic controller using golden BallAlgorithm

Simulation of grid/standalone solar energy supplied reduced switch converter with optimal fuzzy logic controller using golden BallAlgorithm

Green energy-sourced AI-controlled multilevel UPQC parameter selection using football game optimization

Multiobjective Neuro-Fuzzy Controller Design and Selection of Filter Parameters of UPQC Using Predator Prey Firefly and Enhanced Harmony Search Optimization

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