Regenerative city design is an ambitious but crucial goal to improve the sustainability, efficiency, and resilience of urban areas. Buildings and urban environments exhibit complex patterns of energy consumption. Smart grids for renewable energy sources play a fundamental role in this context. However, energy production from these sources is variable and unpredictable, requiring the joint use of fuzzy logic and dynamic systems to adapt these uncertainties to changing environmental conditions. To manage energy flows from renewable sources and manage consumption due to loads, we need stand-alone DC microgrids whose energy management systems reduce both the use of batteries and fuel consumption in fuel cells. However, the amount of data to be processed in real time, together with their intrinsic uncertainties and/or inaccuracies, make the use of control devices based on fuzzy logic necessary. Here, proposes the performance comparison of two energy management systems based on Takagi-Sugeno fuzzy systems with fuzzy rule banks extracted directly from real data and using fuzzy membership functions of Type-1 and Type-2, respectively. The results obtained highlight, in both cases, excellent coverage of the required load but with better adaptability of the Type-2 system.
Stand-Alone DC-MSs & TS Fuzzy Systems for Regenerative Urban Design / Versaci, Mario; LA FORESTA, Fabio; Laganà, Filippo; Morabito, Francesco Carlo. - (2024). [10.1007/978-3-031-74723-6_4]
Stand-Alone DC-MSs & TS Fuzzy Systems for Regenerative Urban Design
Mario Versaci
;Fabio La Foresta;Francesco Carlo Morabito
2024-01-01
Abstract
Regenerative city design is an ambitious but crucial goal to improve the sustainability, efficiency, and resilience of urban areas. Buildings and urban environments exhibit complex patterns of energy consumption. Smart grids for renewable energy sources play a fundamental role in this context. However, energy production from these sources is variable and unpredictable, requiring the joint use of fuzzy logic and dynamic systems to adapt these uncertainties to changing environmental conditions. To manage energy flows from renewable sources and manage consumption due to loads, we need stand-alone DC microgrids whose energy management systems reduce both the use of batteries and fuel consumption in fuel cells. However, the amount of data to be processed in real time, together with their intrinsic uncertainties and/or inaccuracies, make the use of control devices based on fuzzy logic necessary. Here, proposes the performance comparison of two energy management systems based on Takagi-Sugeno fuzzy systems with fuzzy rule banks extracted directly from real data and using fuzzy membership functions of Type-1 and Type-2, respectively. The results obtained highlight, in both cases, excellent coverage of the required load but with better adaptability of the Type-2 system.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.