Development of a Fuzzy Logic Controller for Small-Scale Solar Organic Rankine Cycle Cogeneration Plants

first_pagesettings Open AccessArticle Development of a Fuzzy Logic Controller for Small-Scale Solar Organic Rankine Cycle Cogeneration Plants by Luca Cioccolanti 1,*OrcID,Simone De Grandis 2,Roberto Tascioni 1,Matteo Pirro 3 andAlessandro Freddi 2OrcID 1 CREAT, Centro di Ricerca per l’Energia l’Ambiente e il Territorio, Università eCampus, 22060 Novedrate, Italy 2 Department of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, Italy 3 Società di Trasferimento Tecnologico e Guida all’Innovation Engineering, S.TRA.TE.G.I.E. srl, 60131 Ancona, Italy * Author to whom correspondence should be addressed. Academic Editors: Seongsoo Cho and Sang-Hyun Lee Appl. Sci. 2021, 11(12), 5491; https://doi.org/10.3390/app11125491 Received: 7 May 2021 / Revised: 9 June 2021 / Accepted: 11 June 2021 / Published: 13 June 2021 (This article belongs to the Special Issue The Development and Application of Fuzzy Logic) Download PDF Browse Figures Citation Export Abstract Solar energy is widely recognized as one of the most attractive renewable energy sources to support the transition toward a decarbonized society. Use of low- and medium-temperature concentrated solar technologies makes decentralized power production of combined heating and power (CHP) an alternative to conventional energy conversion systems. However, because of the changes in solar radiation and the inertia of the different subsystems, the operation control of concentrated solar power (CSP) plants is fundamental to increasing their overall conversion efficiency and improving reliability. Therefore, in this study, the operation control of a micro-scale CHP plant consisting of a linear Fresnel reflector solar field, an organic Rankine cycle unit, and a phase change material thermal energy storage tank, as designed and built under the EU-funded Innova Microsolar project by a consortium of universities and companies, is investigated. In particular, a fuzzy logic control is developed in MATLAB/Simulink by the authors in order to (i) initially recognize the type of user according to the related energy consumption profile by means of a neural network and (ii) optimize the thermal-load-following approach by introducing a set of fuzzy rules to switch among the different operation modes. Annual simulations are performed by combining the plant with different thermal load profiles. In general, the analysis shows that that the proposed fuzzy logic control increases the contribution of the TES unit in supplying the ORC unit, while reducing the number of switches between the different OMs. Furthermore, when connected with a residential user load profile, the overall electrical and thermal energy production of the plant increases. Hence, the developed control logic proves to have good potential in increasing the energy efficiency of low- and medium-temperature concentrated solar ORC systems when integrated into the built environment.