Economics of a small renewable generation system

2011 ◽  
Author(s):  
T Knutson
Keyword(s):  
Renewable Generation ◽  
Generation System

Multi-objective design optimization of hybrid renewable systems using UGF

2015 ◽  
Vol 34 (6) ◽  
pp. 1825-1844 ◽  
Author(s):  
Carmen Delgado ◽  
José Antonio Domínguez-Navarro
Keyword(s):  
State Model ◽  
Computational Time ◽  
Renewable Generation ◽  
Multi Objective Optimization ◽  
Generation System ◽  
Hybrid Generation ◽  
Content Type ◽  
Multi Objective ◽  
The Cost ◽  
The Impact

Purpose – Renewable generation is a main component of most hybrid generation systems. However, randomness on its generation is a characteristic to be considered due to its direct impact on reliability and performance of these systems. For this reason, renewable generation usually is accompanied with other generation elements to improve their general performance. The purpose of this paper is to analyze the power generation system, composed of solar, wind and diesel generation and power outsourcing option from the grid as means of reserve source. A multi-objective optimization for the design of hybrid generation system is proposed, particularly using the cost of energy, two different reliability indexes and the percentage of renewable energy as objectives. Further, the uncertainty of renewable sources and demand is modeled with a new technique that permits to evaluate the reliability quickly. Design/methodology/approach – The multi-state model of the generators and the load is modeled with the Universal Generating Function (UGF) to estimate the reliability indexes for the whole system. Then an evolutionary algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm) is used to solve the multi-objective optimization model. Findings – The use of UGF methodology reduces the computation time, providing effective results. The validation of reliability assessment of hybrid generation systems using the UGF is carried out taking as a benchmark the results obtained with the Monte Carlo simulation. The proposed multi-objective algorithm gives as a result different generators combinations that outline hybrid systems, where some of them could be preferred over others depending on its results for each independent objective. Also it allows us to observe the changes produced on the resulting solutions due to the impact of the power fluctuation of the renewable generators. Originality/value – The main contributions of this paper are: an extended multi state model that includes different types of renewable energies, with emphasis on modeling of solar energy; demonstrate the performance improvement of UGF against SMC regarding the computational time required for this case; test the impact of different multi-states numbers for the representation of the elements; depict through multi-objective optimization, the impact of combining different energies on the cost and reliability of the resultant systems.

A Passive Islanding Detection Method for Grid-Connected Renewable Generation System

2013 ◽  
Vol 284-287 ◽  
pp. 1182-1186 ◽  
Author(s):  
Wen Yeau Chang
Keyword(s):  
Detection Method ◽  
Threshold Value ◽  
Islanding Detection ◽  
Test Results ◽  
Renewable Generation ◽  
Threshold Values ◽  
Generation System ◽  
Detection Systems ◽  
Terminal Voltage ◽  
Grid Connected Inverter

This study proposes an islanding detection method for use of grid-connected inverter of renewable generation system. The proposed method is based on an index: the change of power factor (COPF). When an inverter is grid-connected, the COPF is lower than the threshold values. In contrast, as an islanding occurs, the COPF becomes much higher than the threshold value. Detection systems monitor the terminal voltage and load current at the grid-connected point to calculate COPF, and issue an operating signal when the value of COPF exceeds a given threshold. In this study, experiments are conducted to illustrate the principles of the proposed technique for a prototype grid-connected inverter. The test results show that the proposed method is reliable, economical, and easy to implement for islanding detection of grid-connected inverter.

scholarly journals A Novel Approach Using Adaptive Neuro Fuzzy Based Droop Control Standalone Microgrid In Presences of Multiple Sources

2019 ◽  
Vol 9 (1) ◽  
pp. 43-51
Author(s):  
Srinivas Singirikonda ◽  
Y.P. Obulesu
Keyword(s):  
Control Strategy ◽  
Reactive Power ◽  
Voltage Control ◽  
Synchronous Generator ◽  
Droop Control ◽  
Renewable Generation ◽  
Generation System ◽  
Voltage Control Strategy ◽  
Neuro Fuzzy ◽  
Micro Grid

In this paper, a novel Q/P droop control strategy for regulating the voltage and frequency in Standalone micro grid with multiple renewable sources like solar and wind is presented. The frequency and voltage control strategy is applied to a Standalone micro grid with high penetration of intermittent renewable generation system. Adaptive Neuro-Fuzzy logic Interface system (ANFIS) controller is used for frequency and voltage control for Renewable generation system. Battery energy storage system (BESS) is used to generate nominal system frequency instead of using the synchronous generator for frequency control strategy. A synchronous generator is used to maintain the state of charge (SOC) of the BESS, but it has limited capacity. For Voltage control strategy, we proposed reactive power/active power (Q/P) droop control to the conventional reactive power controller which provides voltage damping effect. The induced voltage fluctuations are reduced to get nominal output power. The proposed model is tested on different cases and results show that the proposed method is capable of compensating voltage and frequency variations occurring in the micro grid with minimal rated synchronous generator. ©2020. CBIORE-IJRED. All rights reserved

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