Solar PV integration in commercial buildings for self-consumption based on life-cycle economic/environmental multi-objective optimization

Abstract In this study, a new multi-objective optimization approach is introduced to optimize economically and environmentally the implementation of solar photovoltaic systems for self-consumption under the scenario of zero export injection. Such a scenario is encountered in several developing countries, but up to the author’s knowledge, no previous study dealt with its detailed assessment and optimization. The problem formulation considers using the levelized cost of electricity (LCOE) and the cumulative environmental benefit (CEB) as two life-cycle conflicting objective functions. First, a multiple linear regression technique was developed to predict accurately the PV power generation under a time resolution of 15 min as recommended for PV-self consumption studies. A new mathematical expression was as well derived to calculate more accurately the CEB considering both the degradation of the PV productivity over the project lifetime and the dynamic evolution of the electricity mix of the country with respect to time. A Genetic algorithm (GA) is used to identify Pareto frontiers and Technique for Order Preference by Similarity to Ideal Solution “TOPSIS” decision-making method is employed to select the final optimum. The followed approach was applied for a large Moroccan commercial structure with an annual electric load of 2.932 GWh. It was found that the recommended optimum PV installed capacity is 847.4 kWp. This optimized design leads to the best compromise between economic and environmental aspects and the LCOE is 15.12 c$/kWh while the CEB is 7.89 tonnes CO2. The corresponding self-sufficiency and self-consumption ratios were estimated at 41.41% and 79.14%, respectively.

[1]  Mahmoud Moghavvemi,et al.  Energy management strategies in hybrid renewable energy systems: A review , 2016 .

[2]  A. Allouhi.  Advances on solar thermal cogeneration processes based on thermoelectric devices: A review , 2019, Solar Energy Materials and Solar Cells.

[3]  Ching-Lai Hwang,et al.  Methods for Multiple Attribute Decision Making , 1981 .

[4]  A. Allouhi.  Energetic, exergetic, economic and environmental (4 E) assessment process of wind power generation , 2019, Journal of Cleaner Production.

[5]  Martin János Mayer,et al.  Techno-economic optimization of grid-connected, ground-mounted photovoltaic power plants by genetic algorithm based on a comprehensive mathematical model , 2020 .

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

[7]  Italo Meroni,et al.  A review of performance of zero energy buildings and energy efficiency solutions , 2019, Journal of Building Engineering.

[8]  Christine L. Crago,et al.  Drivers of growth in commercial-scale solar PV capacity , 2018, Energy Policy.

[9]  A. Hasan,et al.  Biogas potential from municipal and agricultural residual biomass for power generation in Hazaribagh, Bangladesh – A strategy to improve the energy system , 2019, Renewable Energy Focus.

[10]  B. Rezaie,et al.  Geothermal technology: Trends and potential role in a sustainable future , 2019, Applied Energy.

[11]  Joaquín Alonso-Montesinos,et al.  Hourly PV production estimation by means of an exportable multiple linear regression model , 2019, Renewable Energy.

[12]  Jiaming Li,et al.  Optimal sizing of grid-connected photovoltaic battery systems for residential houses in Australia , 2019, Renewable Energy.

[13]  H. El-houari,et al.  PV water pumping systems for domestic uses in remote areas: Sizing process, simulation and economic evaluation , 2019, Renewable Energy.

[15]  Nitin Padhiyar,et al.  Optimal grade transition of a non-isothermal continuous reactor with multi-objective dynamic optimization approach , 2019, Chemical Engineering Research and Design.

[16]  K. Hawboldt,et al.  Multi-objective optimization of simultaneous saccharification and fermentation for cellulosic ethanol production , 2018, Renewable Energy.

[17]  Faa-Jeng Lin,et al.  Novel Control Method for Multimodule PV Microinverter With Multiple Functions , 2018, IEEE Transactions on Power Electronics.

[18]  Dirk Uwe Sauer,et al.  Analysis of the maximal possible grid relief from PV-peak-power impacts by using storage systems for increased self-consumption , 2015 .

[19]  M. Green,et al.  Energy conversion approaches and materials for high-efficiency photovoltaics. , 2016, Nature materials.

[20]  Carlo Roselli,et al.  Integration of a Photovoltaic System with an Electric Heat Pump and Electrical Energy Storage Serving an Office Building , 2019, Journal of Sustainable Development of Energy, Water and Environment Systems.

[21]  Axel Gautier,et al.  Self-consumption choice of residential PV owners under net-metering , 2019, Energy Policy.

[22]  A. Awasthi,et al.  Optimal orientation angles for maximizing energy yield for solar PV in Saudi Arabia , 2019, Renewable Energy.

[23]  Tarik Kousksou,et al.  Energy consumption and efficiency in buildings: current status and future trends , 2015 .

[24]  Mustafa Inalli,et al.  Technoeconomic appraisal of a ground source heat pump system for a heating season in eastern Turkey , 2006 .

[25]  Dirk Uwe Sauer,et al.  Optimization of self-consumption and techno-economic analysis of PV-battery systems in commercial applications , 2016 .

[26]  Mahmoud Moghavvemi,et al.  Effective utilization of excess energy in standalone hybrid renewable energy systems for improving comfort ability and reducing cost of energy: A review and analysis , 2015 .

[27]  Giuseppe Marco Tina,et al.  Comparative assessments of the performances of PV/T and conventional solar plants , 2019, Journal of Cleaner Production.

[28]  Joshua M. Pearce,et al.  A Review of Solar Photovoltaic Levelized Cost of Electricity , 2011 .

[29]  Hongxing Yang,et al.  Energy optimization of high-rise commercial buildings integrated with photovoltaic facades in urban context , 2019, Energy.

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

[31]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

[32]  A. Allouhi,et al.  5.1 Energy Auditing , 2018 .

[33]  Makoto Kakinaka,et al.  Renewable energy consumption, carbon emissions, and development stages: Some evidence from panel cointegration analysis , 2019, Renewable Energy.

[34]  Shiming Deng,et al.  Application of TOPSIS method in evaluating the effects of supply vane angle of a task/ambient air conditioning system on energy utilization and thermal comfort , 2016 .

[35]  Yingjun Ruan,et al.  Performance investigation of grid-connected residential PV-battery system focusing on enhancing self-consumption and peak shaving in Kyushu, Japan , 2018, Renewable Energy.

[36]  Gianluca Fulli,et al.  Impact of solar PV self-consumption policies on distribution networks and regulatory implications , 2018, Solar Energy.

[37]  Tarik Kousksou,et al.  Solar domestic heating water systems in Morocco: An energy analysis , 2015 .

[38]  Mustafa Inalli,et al.  A techno-economic comparison of ground-coupled and air-coupled heat pump system for space cooling , 2007 .

[39]  E. Stanley Lee,et al.  An extension of TOPSIS for group decision making , 2007, Math. Comput. Model..

[40]  Alessandro Franco,et al.  Experimental analysis of a self consumption strategy for residential building: The integration of PV system and geothermal heat pump , 2016 .

[41]  D. Coko,et al.  Experimental study on a hybrid energy system with small- and medium-scale applications for mild climates , 2014 .

[42]  Veronica Campos-Guzman,et al.  Life Cycle Analysis with Multi-Criteria Decision Making: A review of approaches for the sustainability evaluation of renewable energy technologies , 2019, Renewable and Sustainable Energy Reviews.

[43]  A. Allouhi,et al.  Energetic, economic and environmental (3E) analyses and LCOE estimation of three technologies of PV grid-connected systems under different climates , 2019, Solar Energy.

[44]  Hoseyn Sayyaadi,et al.  Designing a solar powered Stirling heat engine based on multiple criteria: Maximized thermal efficiency and power , 2013 .

[45]  Ali Mohammad Ranjbar,et al.  Practical battery size optimization of a PV system by considering individual customer damage function , 2017 .

[46]  F. O'sullivan,et al.  A General Model for Estimating Emissions from Integrated Power Generation and Energy Storage. Case Study: Integration of Solar Photovoltaic Power and Wind Power with Batteries , 2018, Processes.

[47]  A. Allouhi,et al.  Energy and exergy analyses of a parabolic trough collector operated with nanofluids for medium and high temperature applications , 2018 .

[48]  Pietro Elia Campana,et al.  The potential of photovoltaic systems to reduce energy costs for office buildings in time-dependent and peak-load-dependent tariffs , 2019, Sustainable Cities and Society.