A novel software package for the robust design of off-grid power systems

Abstract Off-grid power systems represent one of the key solutions for rural electrification. Most of the analyses or tools already present in literature do not consider the final users' energy needs as the starting point of the process nor they consider the inherent uncertainties about loads and resources. Comprehensive stochastic procedures that look at the atypical features of rural contexts and include estimation errors into the design phase are strongly required. In this paper, we present Poli. NRG (POLItecnico di Milano - Network Robust desiGn): a novel software package for the robust design of off-grid electric power systems. Poli. NRG is composed of four blocks which separately face the different design phases: (i) the data inputs gathering block provides a methodology to collect field data as regards weather condition and load demand; (ii) the inputs processing block elaborates the inputs to obtain load and sources profiles over the entire lifetime of the plant; (iii) the system modelling and simulation block simulates different off-grid system configurations and evaluates the related techno-economic performances; (iv) the output formulation block finds the most robust design for the targeted context through specific optimization methods. After a comprehensive description of the software, we have applied it to size a PV + BESS microgrid system to supply power to a peri-urban area of Uganda. The results confirm that parameters' uncertainties deeply affect the design of the system and motivate the robust design approach proposed. Poli. NRG is devoted to map those uncertainties and provide information for decision makers.

[1]  Subhes C. Bhattacharyya,et al.  Review of Alternative Methodologies for Analysing Off-Grid Electricity Supply , 2011 .

[2]  Hasimah Abdul Rahman,et al.  A novel optimization method for designing stand alone photovoltaic system , 2016 .

[3]  Emanuela Colombo,et al.  A sizing methodology based on Levelized Cost of Supplied and Lost Energy for off-grid rural electrification systems , 2016 .

[4]  Agence pour l'Energie Nucléaire.  Projected Costs of Generating Electricity 2010 , 2010 .

[5]  M. Ali Asgar,et al.  Sizing of a stand-alone photovoltaic power system at Dhaka , 2003 .

[6]  T. Huld,et al.  Energy solutions in rural Africa: mapping electrification costs of distributed solar and diesel generation versus grid extension , 2011 .

[7]  Emanuela Colombo,et al.  Novel procedure to formulate load profiles for off-grid rural areas , 2016 .

[8]  Ali Naci Celik,et al.  Effect of different load profiles on the loss-of-load probability of stand-alone photovoltaic systems , 2007 .

[9]  Kamaruzzaman Sopian,et al.  A New Approach for Optimal Sizing of Standalone Photovoltaic Systems , 2012 .

[10]  Al-Khalid Othman,et al.  A novel analytical model for optimal sizing of standalone photovoltaic systems , 2012 .

[11]  Jie Chen,et al.  Energy management and power control for a stand-alone wind energy conversion system , 2012, IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society.

[12]  Getachew Bekele,et al.  Feasibility Study of Small Hydro/PV/Wind Hybrid System for off Grid Rural Electrification in Ethiopia , 2012 .

[13]  Aie,et al.  World Energy Outlook 2011 , 2001 .

[14]  Sunanda Sinha,et al.  Review of software tools for hybrid renewable energy systems , 2014 .

[15]  Emanuela Colombo,et al.  Off-grid systems for rural electrification in developing countries: Definitions, classification and a comprehensive literature review , 2016 .

[16]  Emanuela Colombo,et al.  A Methodology to Develop Design Support Tools for Stand-alone Photovoltaic Systems in Developing Countries , 2014 .

[17]  Felix A. Farret,et al.  Micropower System Modeling with Homer , 2006 .

[18]  Ernst Worrell,et al.  Analyzing grid extension and stand-alone photovoltaic systems for the cost-effective electrification of Kenya , 2015 .

[19]  M. Mauri,et al.  Hybrid micro-grid experimental application in Tanzania , 2015, 2015 International Conference on Clean Electrical Power (ICCEP).

[20]  Caro Lucas,et al.  Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition , 2007, 2007 IEEE Congress on Evolutionary Computation.

[21]  José L. Bernal-Agustín,et al.  Simulation and optimization of stand-alone hybrid renewable energy systems , 2009 .

[22]  Wei Zhou,et al.  A novel optimization sizing model for hybrid solar-wind power generation system , 2007 .

[23]  K. Hollands,et al.  A method to generate synthetic hourly solar radiation globally , 1990 .

[24]  Pr Djamila Rekioua,et al.  Optimization of a photovoltaic pumping system in Bejaia (Algeria) climate , 2015 .

[25]  Djamila Diaf,et al.  A methodology for optimal sizing of autonomous hybrid PV/wind system , 2007 .

[26]  Weixiang Shen,et al.  Optimally sizing of solar array and battery in a standalone photovoltaic system in Malaysia , 2009 .

[27]  José L. Bernal-Agustín,et al.  Comparison of different lead–acid battery lifetime prediction models for use in simulation of stand-alone photovoltaic systems , 2014 .

[28]  Dolf Gielen,et al.  Smart and Just Grids for sub-Saharan Africa : Exploring options , 2013 .

[29]  Shashank Mohan,et al.  National electricity planning in settings with low pre-existing grid coverage: Development of a spatial model and case study of Kenya , 2009 .

[30]  Jose M. Yusta,et al.  Methodologies, technologies and applications for electric supply planning in rural remote areas , 2014 .

[31]  Azah Mohamed,et al.  A review on sizing methodologies of photovoltaic array and storage battery in a standalone photovoltaic system , 2016 .

[32]  Mohamed Machmoum,et al.  Safe sizing methodology applied to a standalone photovoltaic system , 2015 .

[33]  P Balachandra,et al.  Grid-connected versus stand-alone energy systems for decentralized power—A review of literature , 2009 .