Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability

In rural areas or in isolated communities in developing countries it is increasingly common to install micro-renewable sources, such as photovoltaic (PV) systems, by residential consumers without access to the utility distribution network. The reliability of the supply provided by these stand-alone generators is a key issue when designing the PV system. The proper system sizing for a minimum level of reliability avoids unacceptable continuity of supply (undersized system) and unnecessary costs (oversized system). This paper presents a method for the accurate sizing of stand-alone photovoltaic (SAPV) residential generation systems for a pre-established reliability level. The proposed method is based on the application of a sequential random Monte Carlo simulation to the system model. Uncertainties of solar radiation, energy demand, and component failures are simultaneously considered. The results of the case study facilitate the sizing of the main energy elements (solar panels and battery) depending on the required level of reliability, taking into account the uncertainties that affect this type of facility. The analysis carried out demonstrates that deterministic designs of SAPV systems based on average demand and radiation values or the average number of consecutive cloudy days can lead to inadequate levels of continuity of supply.

[1]  Guillermo Escrivá-Escrivá,et al.  Optimal Energy Management of an Academic Building with Distributed Generation and Energy Storage Systems , 2017 .

[2]  Carlos Álvarez-Bel,et al.  An optimisation algorithm for distributed energy resources management in micro-scale energy hubs , 2017 .

[3]  Zhengming Zhao,et al.  Grid-connected photovoltaic power systems: Technical and potential problems—A review , 2010 .

[4]  F. Cucchiella,et al.  Solar Photovoltaic Panels Combined with Energy Storage in a Residential Building: An Economic Analysis , 2018, Sustainability.

[5]  Guillermo Escrivá-Escrivá,et al.  Experimental verification of hybrid renewable systems as feasible energy sources , 2016 .

[6]  Konstantinos P. Tsagarakis,et al.  A Techno-Economic Analysis of a PV-Battery System in Greece , 2019, Energies.

[7]  Sunliang Cao,et al.  Impact of simulation time-resolution on the matching of PV production and household electric demand , 2014 .

[8]  Krzysztof Koszela,et al.  Short-term forecast of generation of electric energy in photovoltaic systems , 2018 .

[9]  Wei Zhou,et al.  Current status of research on optimum sizing of stand-alone hybrid solar–wind power generation systems , 2010 .

[10]  C. G. Ozoegwu,et al.  Artificial neural network forecast of monthly mean daily global solar radiation of selected locations based on time series and month number , 2019, Journal of Cleaner Production.

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

[12]  Amit Kumar Yadav,et al.  Solar radiation prediction using Artificial Neural Network techniques: A review , 2014 .

[13]  Guillermo Escrivá-Escrivá,et al.  Improving the benefits of demand response participation in facilities with distributed energy resources , 2019, Energy.

[14]  Hamidreza Zareipour,et al.  Performance assessment of photovoltaic modules based on daily energy generation estimation , 2018, Energy.

[15]  G. Escrivá-Escrivá,et al.  Improving the Sustainability of Self-Consumption with Cooperative DC Microgrids , 2019, Sustainability.

[16]  Curran Crawford,et al.  Implications of temporal resolution for modeling renewables-based power systems , 2012 .

[17]  D. M. L. H. Dissawa,et al.  Cross-correlation based cloud motion estimation for short-term solar irradiation predictions , 2017, International Conference on Industrial and Information Systems.

[18]  Hongbo Ren,et al.  Optimal operation of a grid-connected hybrid PV/fuel cell/battery energy system for residential applications , 2016 .

[19]  Makbul A.M. Ramli,et al.  A review of optimization approaches for hybrid distributed energy generation systems: Off-grid and grid-connected systems , 2018 .

[20]  Eleni Kaplani,et al.  A stochastic simulation model for reliable PV system sizing providing for solar radiation fluctuations , 2012 .

[21]  Vladimir Strezov,et al.  Assessment of utility energy storage options for increased renewable energy penetration , 2012 .

[22]  Anjum Munir,et al.  Design and economics analysis of an off-grid PV system for household electrification , 2015 .

[23]  Daniel Nilsson,et al.  Photovoltaic self-consumption in buildings : A review , 2015 .

[24]  Renu Sharma,et al.  Performance evaluation of stand alone, grid connected and hybrid renewable energy systems for rural application: A comparative review , 2017 .

[25]  Volker Quaschning,et al.  Sizing of Residential PV Battery Systems , 2014 .

[26]  Yuansheng Huang,et al.  Cooperation between Two Micro-Grids Considering Power Exchange: An Optimal Sizing Approach Based on Collaborative Operation , 2018, Sustainability.

[27]  Akbar Maleki,et al.  Modeling and optimal design of an off-grid hybrid system for electricity generation using various biodiesel fuels: a case study for Davarzan, Iran , 2016 .

[28]  Akbar Maleki,et al.  Optimal Operation of a Grid-Connected Hybrid Renewable Energy System for Residential Applications , 2017 .

[29]  Roy Billinton,et al.  Application of sequential Monte Carlo simulation to evaluation of distributions of composite system indices , 1997 .

[30]  E. Caamaño-Martín,et al.  PV self-consumption optimization with storage and Active DSM for the residential sector , 2011 .

[31]  Brian K. Johnson,et al.  Design and Test of a Combined PV and Battery System Under Multiple Load and Irradiation Conditions , 2019, 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT).

[32]  Wenyuan Li,et al.  Reliability assessment of photovoltaic power systems: Review of current status and future perspectives , 2013 .

[33]  Carmen L. T. Borges,et al.  An overview of reliability models and methods for distribution systems with renewable energy distributed generation , 2012 .

[34]  Peter Palensky,et al.  Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads , 2011, IEEE Transactions on Industrial Informatics.

[35]  Ala Hasan,et al.  Matching analysis for on-site hybrid renewable energy systems of office buildings with extended indices , 2014 .

[36]  Ayman Faza A probabilistic model for estimating the effects of photovoltaic sources on the power systems reliability , 2018, Reliab. Eng. Syst. Saf..

[37]  R. Moharil,et al.  Reliability analysis of solar photovoltaic system using hourly mean solar radiation data , 2010 .

[38]  Ali Cheknane,et al.  Classification of hourly solar radiation using fuzzy c-means algorithm for optimal stand-alone PV system sizing , 2016 .