HYRES: A Multi-Objective Optimization Tool for Proper Configuration of Renewable Hybrid Energy Systems

This paper presents the Hybrid Renewable Energy System (HYRES), a powerful tool to contribute to the viability analysis of energy systems involving renewable generators. HYRES considers various input parameters related to climatic conditions, statistical reliability, and economic views; in addition to offering multi-objective optimizations using Genetic Algorithms (GAs) that have a better cost-benefit ratio than mono-objective optimization, which is the technique used in several commercial systems like HOMER, a worldwide leader in microgrid modeling. The use of intelligent techniques in HYRES allows optimal sizing of hybrid renewable systems with wind and solar energy generators adapted to different conditions and case studies. The elements that affect the system design like buying and selling energy from/to the grid and the use of storage units can be included in system configuration according to the need. Optimization approaches are selectable and include Initial Cost, Life Cycle Cost, Loss of Power Probability, and Loss of Power Supply Probability.

[1]  E. S. Karapidakis,et al.  Hybrid Simulated Annealing–Tabu Search Method for Optimal Sizing of Autonomous Power Systems With Renewables , 2012, IEEE Transactions on Sustainable Energy.

[2]  B. Ould Bilal,et al.  Multi-objective design of PV-wind-batteries hybrid systems by minimizing the annualized cost system and the loss of power supply probability (LPSP) , 2013, 2013 IEEE International Conference on Industrial Technology (ICIT).

[3]  Temitope Raphael Ayodele,et al.  Optimal allocation and sizing of PV/Wind/Split-diesel/Battery hybrid energy system for minimizing life cycle cost, carbon emission and dump energy of remote residential building , 2016 .

[4]  Akbar Maleki,et al.  A novel framework for optimal design of hybrid renewable energy-based autonomous energy systems: A case study for Namin, Iran , 2016 .

[5]  Tarek Y. ElMekkawy,et al.  Optimal design of hybrid renewable energy systems in buildings with low to high renewable energy ratio , 2015 .

[6]  R. P. Saini,et al.  A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications , 2016 .

[7]  Xinbo Ruan,et al.  An Improved Optimal Sizing Method for Wind-Solar-Battery Hybrid Power System , 2013, IEEE Transactions on Sustainable Energy.

[8]  H.W. Ngan,et al.  Operational optimization of a stand-alone hybrid renewable energy generation system based on an improved genetic algorithm , 2010, IEEE PES General Meeting.

[9]  Mohamed Haouari,et al.  Review of optimization techniques applied for the integration of distributed generation from renewable energy sources , 2017 .

[10]  Sunanda Sinha,et al.  Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems , 2015 .

[11]  G. Scelba,et al.  Multicriteria Optimal Sizing of Photovoltaic-Wind Turbine Grid Connected Systems , 2013, IEEE Transactions on Energy Conversion.

[12]  Abdullah Al-Badi,et al.  A review of optimum sizing of hybrid PV–Wind renewable energy systems in oman , 2016 .

[13]  Giovanni Lutzemberger,et al.  Multi-Objective Optimization of Off-Grid Hybrid Renewable Energy Systems in Buildings with Prior Design-Variable Screening , 2019, Energies.

[14]  Hocine Belmili,et al.  A Computer Program Development for Sizing Stand-alone Photovoltaic-Wind Hybrid Systems , 2013 .

[15]  Mauro Gamberi,et al.  State-of-art review of the optimization methods to design the configuration of hybrid renewable energy systems (HRESs) , 2018, Frontiers in Energy.

[16]  Rita Puig,et al.  Optimal sizing of a hybrid grid-connected photovoltaic and wind power system , 2015 .

[17]  X. Xia,et al.  Demand side management of photovoltaic-battery hybrid system , 2015 .

[18]  Tao Zhang,et al.  Multi-objective optimal design of hybrid renewable energy systems using preference-inspired coevolutionary approach , 2015 .

[19]  Enzo Sauma,et al.  Business optimal design of a grid-connected hybrid PV (photovoltaic)-wind energy system without energy storage for an Easter Island's block , 2013 .

[20]  Ramin Hosseinalizadeh,et al.  Economic sizing of a hybrid (PV–WT–FC) renewable energy system (HRES) for stand-alone usages by an optimization-simulation model: Case study of Iran , 2016 .

[21]  Hongxing Yang,et al.  A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island , 2014 .

[22]  Prashant Baredar,et al.  Solar–wind hybrid renewable energy system: A review , 2016 .

[23]  Zaheeruddin,et al.  Optimal sizing and cost assesment of hybrid Renewable Energy Systems for Assam Engineering College , 2015, 2015 Annual IEEE India Conference (INDICON).

[24]  Amaya Martínez-Gracia,et al.  Sizing criteria of hybrid photovoltaic–wind systems with battery storage and self-consumption considering interaction with the grid , 2013 .

[25]  M. Venkata Kirthiga,et al.  Optimal sizing of hybrid generators for autonomous operation of a micro-grid , 2010, 2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel.

[26]  Jan Carmeliet,et al.  Building energy optimization: An extensive benchmark of global search algorithms , 2019, Energy and Buildings.