Techno-economic performance analysis in a nanogrid with Hybrid Renewable Energy Sources using classical optimization technique

Various renewable energy sources such as wind power and photovoltaic (PV) have been increasingly integrated into the power system through power electronic converters in recent years. However, power electronic converter-driven stability issues under specific circumstances, for instance, modal resonances might deteriorate the dynamic performance of the power systems or even threaten the overall stability. In this paper, the integration impact of a hybrid renewable energy source (HRES) system on modal interaction and converter-driven stability is investigated in an IEEE 16-machine 68-bus power system. Firstly, an HRES system is introduced, which consists of full converter-based wind power generation (FCWG) and full converter-based photovoltaic generation (FCPV). The equivalent dynamic models of FCWG and FCPV are then established, followed by the linearized state-space modeling. On this basis, converter-driven stability analyses are performed to reveal the modal resonance mechanisms of the interconnected power systems and the modal interaction phenomenon. Additionally, time-domain simulations are conducted to verify effectiveness of dynamic models and support the converter-driven stability analysis results. To avoid detrimental modal resonances, an optimization strategy is further proposed by retuning the controller parameters of the HRES system. The overall results demonstrate the modal interaction effect between external AC power system and the HRES system and its various impacts on converter-driven stability.

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A XGBOOST‐MRFO control scheme for power quality improvement in grid integrated hybrid renewable energy sources using STATCOM

International Transactions on Electrical Energy Systems ◽

10.1002/2050-7038.13181 ◽

2021 ◽

Author(s):

Parag Vijay Datar ◽

Deepak Balkrishna Kulkarni

Keyword(s):

Renewable Energy ◽

Quality Improvement ◽

Power Quality ◽

Renewable Energy Sources ◽

Energy Sources ◽

Control Scheme ◽

Power Quality Improvement ◽

Hybrid Renewable Energy

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Optimum utilization of grid connected hybrid renewable energy sources using hybrid algorithm

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331220913740 ◽

2020 ◽

pp. 014233122091374

Author(s):

M. Suresh ◽

R. Meenakumari

Keyword(s):

Renewable Energy ◽

Tabu Search ◽

Smart Grid ◽

Optimization Algorithm ◽

Renewable Energy Sources ◽

Whale Optimization Algorithm ◽

Computational Time ◽

Energy Sources ◽

Whale Optimization ◽

Hybrid Renewable Energy

An optimal utilization of smart grid connected hybrid renewable energy sources is proposed in this paper. The hybrid technique is the combination of recurrent neural network and adaptive whale optimization algorithm plus tabu search, called AWOTS. The main objective is the RES optimum operation for decreasing the electricity production cost by hourly day-ahead and real time scheduling. Here, the load demands are predicted using AWOTS to develop the correct control signals based on power difference between source and load side. Adaptive whale optimization algorithm searching behaviour is adjusted by tabu search. The proposed technique is executed in the MATLAB/Simulink working platform. To test the performance of the proposed method, the load demand for the 24-hour time period is demonstrated. By then the power generated in the sources, such as photovoltaic, wind turbine, micro turbine and battery by the proposed technique, is analyzed and compared with existing techniques, such as genetic algorithm, particle swarm optimization and whale optimization algorithm. Furthermore, the state of charge of the battery for the 24-hour period is compared with existing techniques. Likewise, the cost of the system is compared and error in the sources also compared. The comparison results affirm that the proposed technique has less computational time (35.001703) than the existing techniques. Moreover, the proposed method is cost-effective power production of smart grid and effective utilization of renewable energy sources without wasting the available energy.

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An efficient optimal power flow management based microgrid in hybrid renewable energy system using hybrid technique

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331220961687 ◽

2020 ◽

pp. 014233122096168

Author(s):

P Annapandi ◽

R Banumathi ◽

NS Pratheeba ◽

A Amala Manuela

Keyword(s):

Renewable Energy ◽

Power Flow ◽

Optimal Power Flow ◽

Renewable Energy Sources ◽

Energy Sources ◽

Spotted Hyena ◽

Flow Management ◽

Control Signals ◽

Optimal Power ◽

Hybrid Renewable Energy

In this paper, the optimal power flow management-based microgrid in hybrid renewable energy sources with hybrid proposed technique is presented. The photovoltaic, wind turbine, fuel cell and battery are also presented. The proposed technique is the combined execution of both spotted hyena optimization and elephant herding optimization. Spotted hyena optimization is utilized to optimize the combination of controller parameters based on the voltage variation. In the proposed technique, the spotted hyena optimization combined with elephant herding optimization plays out the assessment procedure to establish the exact control signals for the system and builds up the control signals for offline way in light of the power variety between source side and load side. The objective function is defined by the system data subject to equality and inequality constraints such as real and reactive power limits, power loss limit, and power balance of the system and so on. The constraint is the availability of the renewable energy sources and power demand from the load side in which the battery is used only for lighting load. By utilizing the proposed method, the power flow constraints are restored into secure limits with the reduced cost. At that point, the proposed model is executed in the Matrix Laboratory/Simulink working platform and the execution is assessed with the existing techniques. In this article, the performance analysis of proposed and existing techniques such as elephant herding optimization, particle swarm optimization, and bat algorithm are evaluated. Furthermore, the statistical analysis is also performed. The result reveals that the power flow of the hybrid renewable energy sources by the proposed method is effectively managed when compared with existing techniques.

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