Optimal Energy Management in a Standalone Microgrid, with Photovoltaic Generation, Short-Term Storage, and Hydrogen Production

This paper addresses the energy management of a standalone renewable energy system. The system is configured as a microgrid, including photovoltaic generation, a lead-acid battery as a short term energy storage system, hydrogen production, and several loads. In this microgrid, an energy management strategy has been incorporated that pursues several objectives. On the one hand, it aims to minimize the amount of energy cycled in the battery, in order to reduce the associated losses and battery size. On the other hand, it seeks to take advantage of the long-term surplus energy, producing hydrogen and extracting it from the system, to be used in a fuel cell hybrid electric vehicle. A crucial factor in this approach is to accommodate the energy consumption to the energy demand and to achieve this, a model predictive control (MPC) scheme is proposed. In this context, proper models for solar estimation, hydrogen production, and battery energy storage will be presented. Moreover, the controller is capable of advancing or delaying the deferrable loads from its prescheduled time. As a result, a stable and efficient supply with a relatively small battery is obtained. Finally, the proposed control scheme has been validated on a real case scenario.

[1]  Rodolfo Dufo-López,et al.  Standalone Renewable Energy and Hydrogen in an Agricultural Context: A Demonstrative Case , 2019, Sustainability.

[2]  Mahmoud F. Elmorshedy,et al.  Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control , 2020, IEEE Access.

[3]  N. El‐Farra,et al.  Optimization and control of offshore wind systems with energy storage , 2018, Energy Conversion and Management.

[4]  Merlinde Kay,et al.  Battery energy storage system size determination in renewable energy systems: A review , 2018, Renewable and Sustainable Energy Reviews.

[5]  P. I. Cooper,et al.  Some factors affecting the absorption of solar radiation in solar stills , 1972 .

[6]  José L. Bernal-Agustín,et al.  Sizing of off-grid renewable energy systems for drip irrigation in Mediterranean crops. , 2015 .

[7]  Julien Eynard,et al.  A new approach to the real-time assessment and intraday forecasting of clear-sky direct normal irradiance , 2018, Solar Energy.

[8]  Giorgio Rizzoni,et al.  A Novel Model-Based Algorithm for Battery Prognosis , 2009 .

[9]  M. Ceraolo,et al.  High fidelity electrical model with thermal dependence for characterization and simulation of high power lithium battery cells , 2012, 2012 IEEE International Electric Vehicle Conference.

[10]  Zonghai Chen,et al.  A new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries , 2013 .

[11]  Xiaosong Hu,et al.  A comparative study of equivalent circuit models for Li-ion batteries , 2012 .

[12]  Angelika Bayer,et al.  Solar Engineering Of Thermal Processes , 2016 .

[13]  Mohamed Benbouzid,et al.  Microgrids energy management systems: A critical review on methods, solutions, and prospects , 2018, Applied Energy.

[14]  Vasilis Fthenakis,et al.  Life-cycle analysis of flow-assisted nickel zinc-, manganese dioxide-, and valve-regulated lead-acid batteries designed for demand-charge reduction , 2015 .

[15]  Oleg Wasynczuk,et al.  Applicability of available Li-ion battery degradation models for system and control algorithm design , 2018 .

[16]  F. Barreras,et al.  Combined production of electricity and hydrogen from solar energy and its use in the wine sector , 2018, Renewable Energy.

[17]  R. Barreto,et al.  Fossil fuels, alternative energy and economic growth , 2018, Economic Modelling.

[18]  David Muñoz de la Peña,et al.  Periodic Economic Control of a Nonisolated Microgrid , 2015, IEEE Transactions on Industrial Electronics.

[19]  Ahmad Ghasemi,et al.  Optimal energy management of a renewable-based isolated microgrid with pumped-storage unit and demand response , 2018, Renewable Energy.

[20]  Peter Lund,et al.  Review of energy system flexibility measures to enable high levels of variable renewable electricity , 2015 .

[21]  Joohyung Lee,et al.  Energy independence of energy trading system in microgrid , 2017, 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia).

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

[23]  Simona Onori,et al.  Optimal energy management of hybrid electric vehicles including battery aging , 2011, Proceedings of the 2011 American Control Conference.

[24]  Mariagrazia Dotoli,et al.  Energy scheduling of a smart home under nonlinear pricing , 2014, 53rd IEEE Conference on Decision and Control.

[25]  J. C. van den Bergh,et al.  Monetary valuation of the social cost of CO2 emissions: A critical survey , 2015 .

[26]  M. Verbrugge,et al.  Cycle-life model for graphite-LiFePO 4 cells , 2011 .

[27]  R. P. Saini,et al.  A review on Integrated Renewable Energy System based power generation for stand-alone applications: Configurations, storage options, sizing methodologies and control , 2014 .

[28]  Greg Kopp,et al.  An assessment of the solar irradiance record for climate studies , 2014 .

[29]  Trudie Wang,et al.  Control and Optimization of Grid-Tied Photovoltaic Storage Systems Using Model Predictive Control , 2014, IEEE Transactions on Smart Grid.

[30]  Christian A. Gueymard,et al.  Critical analysis and performance assessment of clear sky solar irradiance models using theoretical and measured data , 1993 .

[31]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[32]  P. Ineichen,et al.  A new airmass independent formulation for the Linke turbidity coefficient , 2002 .

[33]  Ahmad Zahedi,et al.  Review of control strategies for voltage regulation of the smart distribution network with high penetration of renewable distributed generation , 2016 .

[34]  P. Cooper.  The absorption of radiation in solar stills , 1969 .

[35]  Juan S. Giraldo,et al.  Microgrids Energy Management Using Robust Convex Programming , 2019, IEEE Transactions on Smart Grid.

[36]  R. Inman,et al.  Impact of local broadband turbidity estimation on forecasting of clear sky direct normal irradiance , 2015 .

[37]  Josep M. Guerrero,et al.  A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions , 2018, Applied Energy.

[38]  Mariagrazia Dotoli,et al.  Energy scheduling of a smart microgrid with shared photovoltaic panels and storage: The case of the Ballen marina in Samsø , 2020, Energy.

[39]  J. A. Ruiz-Arias,et al.  Validation of direct normal irradiance predictions under arid conditions: A review of radiative models and their turbidity-dependent performance , 2015 .

[40]  C. Gueymard.  REST2: High-performance solar radiation model for cloudless-sky irradiance, illuminance, and photosynthetically active radiation – Validation with a benchmark dataset , 2008 .

[41]  Félix Barreras,et al.  Remodeling of a commercial plug-in battery electric vehicle to a hybrid configuration with a PEM fuel cell , 2018, International Journal of Hydrogen Energy.

[42]  Mariagrazia Dotoli,et al.  A Residential Demand-Side Management Strategy under Nonlinear Pricing Based on Robust Model Predictive Control , 2019, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC).