A critical analysis on hybrid renewable energy modeling tools: An emerging opportunity to include social indicators to optimise systems in small communities

Abstract The arrival of different renewable energy and storage technologies with lower costs is helping smaller communities to gain access to affordable electricity resources through energy systems fed from heterogeneous generation resources. With the growing popularity of Hybrid Renewable Energy Systems (HRES), a novel kind of end-user software tool has also emerged to help planners optimize such energy installations. At the same time, there is an increase in the number of research articles that warn about the need for considering social indicators such as job creation and social acceptance when designing HRESs in addition to the usual considerations of economical, technical, and environmental criteria. Consequently, the design of HRESs could also be optimized by adding such new social parameters. Mainly, this article presents a complete review of the most popular tools for designing HRESs, and the main conclusion of this survey is that these tools do not consider social factors which is a real opportunity to boost the capabilities of such software packages. Also, this research provides valuable information for the developers of HRES optimization tools, providing them, on the one hand, with insights about the advantages of including social parameters during technology assessment and, on the other hand, with a guide to help them with selecting the most pertinent tool at each case, allowing designers to make the most of the socio-demographic structures and obtain more advantages from local renewable resources.

[1]  Aie World Energy Outlook 2017 , 2017 .

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

[3]  Paul Breeze,et al.  Power Generation Technologies , 2005 .

[4]  Paul Gerard Tuohy,et al.  A modelling tool selection process for planning of community scale energy systems including storage and demand side management , 2018 .

[5]  Maurizio Cellura,et al.  Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology , 2003 .

[6]  Jukka Paatero,et al.  Evaluation of choices for sustainable rural electrification in developing countries: A multicriteria approach , 2013 .

[7]  Dundar F. Kocaoglu,et al.  Social and Political Impacts of Renewable Energy: Literature Review , 2016 .

[8]  Simon Hilpert,et al.  A qualitative evaluation approach for energy system modelling frameworks , 2018 .

[9]  Carlos Silva,et al.  Design and implementation of hybrid renewable energy systems on micro-communities: A review on case studies , 2014 .

[10]  Mahendra Pal Sharma,et al.  A review on configurations, control and sizing methodologies of hybrid energy systems , 2014 .

[11]  E. Tolosana,et al.  Does forest biomass harvesting for energy reduce fire hazard in the Mediterranean basin? a case study in the Caroig Massif (Eastern Spain) , 2017, European Journal of Forest Research.

[12]  Vijay Modi,et al.  Measuring energy poverty: Focusing on what matters , 2012 .

[13]  Adam Hawkes,et al.  Energy systems modeling for twenty-first century energy challenges , 2014 .

[14]  Ozan Erdinc,et al.  Optimum design of hybrid renewable energy systems: Overview of different approaches , 2012 .

[15]  Jose M. Yusta,et al.  Optimisation of PV-wind-diesel-battery stand-alone systems to minimise cost and maximise human development index and job creation , 2016 .

[16]  Arvind R. Singh,et al.  A review of multi criteria decision making (MCDM) towards sustainable renewable energy development , 2017 .

[17]  Daren Watson,et al.  Photurgen: The open source software for the analysis and design of hybrid solar wind energy systems in the Caribbean region: A brief introduction to its development policy , 2017 .

[18]  Anis Omri,et al.  Modeling the causal linkages between nuclear energy, renewable energy and economic growth in developed and developing countries , 2015 .

[19]  Uwe Krien,et al.  Addressing Energy System Modelling Challenges: The Contribution of the Open Energy Modelling Framework (oemof) , 2017 .

[20]  Gade Pandu Rangaiah,et al.  Application and Analysis of Methods for Selecting an Optimal Solution from the Pareto-Optimal Front obtained by Multiobjective Optimization , 2017 .

[21]  Yanfeng Liu,et al.  Modeling, planning, application and management of energy systems for isolated areas: A review , 2018 .

[22]  Hussain A. Samad,et al.  Energy poverty in rural Bangladesh , 2011 .

[23]  Gang Liu,et al.  Development of a general sustainability indicator for renewable energy systems: A review , 2014 .

[24]  Alfredo Nicolas Erlwein-Vicuna Bioenergy resources from waste, energy crops and forest in Los Ríos Region (southern Chile) - A systemic approach based on sustainability on designing a bioenergy area , 2016 .

[25]  Zenonas Turskis,et al.  Multi-criteria analysis of electricity generation technologies in Lithuania , 2016 .

[26]  Jose M. Yusta,et al.  Application of multicriteria decision methods for electric supply planning in rural and remote areas , 2015 .

[27]  Shantha Gamini Jayasinghe,et al.  A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system , 2017 .

[28]  Jiangjiang Wang,et al.  Review on multi-criteria decision analysis aid in sustainable energy decision-making , 2009 .

[29]  Rohan P Fisher,et al.  Free and simple GIS as appropriate for health mapping in a low resource setting: a case study in eastern Indonesia , 2011, International journal of health geographics.

[30]  A. K. Akella,et al.  Social, economical and environmental impacts of renewable energy systems , 2009 .

[31]  Benjamin Sovacool,et al.  Electricity market design for the prosumer era , 2016, Nature Energy.

[32]  Pendo Kivyiro,et al.  Carbon dioxide emissions, energy consumption, economic growth, and foreign direct investment: Causality analysis for Sub-Saharan Africa , 2014 .

[33]  Gustavo Migoni,et al.  Efficient simulation of Hybrid Renewable Energy Systems , 2016 .

[34]  Daniel M. Kammen,et al.  Putting renewables and energy efficiency to work: How many jobs can the clean energy industry generate in the US? , 2010 .

[35]  P. Mancarella,et al.  Modelling of integrated multi-energy systems: Drivers, requirements, and opportunities , 2016, 2016 Power Systems Computation Conference (PSCC).

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

[37]  Tarek Y. ElMekkawy,et al.  Stochastic optimization of hybrid renewable energy systems using sampling average method , 2015 .

[38]  Sulayman K. Sowe,et al.  Analysis of open source biotechnology in developing countries: An emerging framework for sustainable agriculture , 2012 .

[39]  I. Ozturk,et al.  The effect of renewable energy consumption on economic growth: Evidence from top 38 countries , 2016 .

[40]  Dongxiao Niu,et al.  A NOVEL SOCIAL-ENVIRONMENTAL-ECONOMIC DISPATCH MODEL FOR THERMAL / WIND POWER GENERATION AND APPLICATION , 2013 .

[41]  Brian Vad Mathiesen,et al.  A review of computer tools for analysing the integration of renewable energy into various energy systems , 2010 .

[42]  Ramazan Yaman,et al.  Evaluation of approaches used for optimization of stand-alone hybrid renewable energy systems , 2017 .

[43]  M. Wolsink The research agenda on social acceptance of distributed generation in smart grids: Renewable as common pool resources , 2012 .

[44]  Sandip Deshmukh,et al.  Modeling of hybrid renewable energy systems , 2008 .

[45]  Adrian Pop,et al.  OpenModelica - A free open-source environment for system modeling, simulation, and teaching , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

[46]  Naruemon Wattanapongsakorn,et al.  Post Pareto-optimal pruning algorithm for multiple objective optimization using specific extended angle dominance , 2015, Eng. Appl. Artif. Intell..

[47]  Gang Liu,et al.  Techno-economic evaluation for hybrid renewable energy system: Application and merits , 2018, Energy.

[48]  Shahid H. Bokhari,et al.  Linux and the Developing World , 1999, IEEE Softw..

[49]  K. Palanisamy,et al.  Optimization in microgrids with hybrid energy systems – A review , 2015 .

[50]  Cruz E. Borges,et al.  A case study comparison between photovoltaic and fossil generation based on direct current hybrid microgrids to power a service building , 2020 .

[51]  Xiangning Lin,et al.  Hybrid renewable microgrid optimization techniques: A review , 2018 .

[52]  Konstantinos Aravossis,et al.  Decision making in renewable energy investments: A review , 2016 .

[53]  Peter M. Haugan,et al.  A review of modelling tools for energy and electricity systems with large shares of variable renewables , 2018, Renewable and Sustainable Energy Reviews.

[54]  Sebastian Spaeth,et al.  The open source software phenomenon: Characteristics that promote research , 2007, J. Strateg. Inf. Syst..