Citation: Kamjoo, Azadeh, Maheri, Alireza, Dizqah, Arash and Putrus, Ghanim (2016) Multiobjective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming. International Journal of Electrical Power & Energy Systems, Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Due to substantial generation and demand fluctuations in standalone green microgrids, energy management strategies are becoming essential for the power sharing and voltage regulation purposes. The classical energy management strategies employ the maximum power point tracking (MPPT) algorithms and rely on batteries in case of possible excess or deficit of energy. However, in order to realize constant current-constant voltage (IU) charging regime and increase the life span of batteries, energy management strategies require being more flexible with the power curtailment feature. In this paper, a coordinated and multivariable energy management strategy is proposed that employs a wind turbine and a photovoltaic array of a standalone DC microgrid as controllable generators by adjusting the pitch angle and the switching duty cycles. The proposed strategy is developed as an online nonlinear model predictive control (NMPC) algorithm. Applying to a sample standalone dc microgrid, the developed controller realizes the IU regime for charging the battery bank. The variable load demands are also shared accurately between generators in proportion to their ratings. Moreover, the DC bus voltage is regulated within a predefined range, as a design parameter.

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Abstract-Uncertainties in renewable energy resources are the main challenges in maintaining a high quality of supply in stand-alone Hybrid Renewable Energy Systems (HRES). Conventionally, a battery bank is used as an auxiliary source to reduce the vulnerability of HRES to the climate changes and maintain the desired quality of supply. Considering the uncertainties at the design stage would ensure appropriate sizing of the HRESs in order to improve their reliability under different operating conditions. This paper proposes a method in optimal sizing of a stand-alone wind turbine/PV/battery system considering uncertainties in renewable energy resources. The wind speed and solar irradiance variations are modelled by using time series analysis method. Performance of the design candidates is evaluated by using the Monte-Carlo simulation method. The analysis presented is supported by a case study for a typical household in the UK.

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