Agent-based simulation for renewable energy incentive design

In this thesis, we propose a novel approach to model the diffusion of residential PV systems. For this purpose, we use an agent-based model where agents are the families living in the area of interest. The case study is the Emilia-Romagna Regional Energy plan, which aims to increase the produc- tion of electricity from renewable energy. So, we study the microdata from the Survey on Household Income and Wealth (SHIW) provided by Bank of Italy in order to obtain the characteristics of families living in Emilia-Romagna. These data have allowed us to artificial generate families and reproduce the socio-economic aspects of the region. The families generated by means of a software are placed on the virtual world by associating them with the buildings. These buildings are acquired by analysing the vector data of regional buildings made available by the region. Each year, the model determines the level of diffusion by simulating the installed capacity. The adoption behaviour is influenced by social interactions, household’s economic situation, the environmental benefits arising from the adoption and the payback period of the investment.

Design of a wearable platform for PPG analysis with multicore low-power processor

Photoplethysmography (PPG) sensors allow for noninvasive and comfortable heart-rate (HR) monitoring, suitable for compact wearable devices. However, PPG signals collected from such devices often suffer from corruption caused by motion artifacts. This is typically addressed by combining the PPG signal with acceleration measurements from an inertial sensor. Recently, different energy-efficient deep learning approaches for heart rate estimation have been proposed. To test these new solutions, in this work, we developed a highly wearable platform (42mm x 48 mm x 1.2mm) for PPG signal acquisition and processing, based on GAP9, a parallel ultra low power system-on-chip featuring nine cores RISC-V compute cluster with neural network accelerator and 1 core RISC-V controller. The hardware platform also integrates a commercial complete Optical Biosensing Module and an ARM-Cortex M4 microcontroller unit (MCU) with Bluetooth low-energy connectivity. To demonstrate the capabilities of the system, a deep learning-based approach for PPG-based HR estimation has been deployed. Thanks to the reduced power consumption of the digital computational platform, the total power budget is just 2.67 mW providing up to 5 days of operation (105 mAh battery).

Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

Design and optimization of turbo-expanders for organic rankine cycles

In a world focused on the need to produce energy for a growing population, while reducing atmospheric emissions of carbon dioxide, organic Rankine cycles represent a solution to fulfil this goal. This study focuses on the design and optimization of axial-flow turbines for organic Rankine cycles. From the turbine designer point of view, most of this fluids exhibit some peculiar characteristics, such as small enthalpy drop, low speed of sound, large expansion ratio. A computational model for the prediction of axial-flow turbine performance is developed and validated against experimental data. The model allows to calculate turbine performance within a range of accuracy of ±3%. The design procedure is coupled with an optimization process, performed using a genetic algorithm where the turbine total-to-static efficiency represents the objective function. The computational model is integrated in a wider analysis of thermodynamic cycle units, by providing the turbine optimal design. First, the calculation routine is applied in the context of the Draugen offshore platform, where three heat recovery systems are compared. The turbine performance is investigated for three competing bottoming cycles: organic Rankine cycle (operating cyclopentane), steam Rankine cycle and air bottoming cycle. Findings indicate the air turbine as the most efficient solution (total-to-static efficiency = 0.89), while the cyclopentane turbine results as the most flexible and compact technology (2.45 ton/MW and 0.63 m3/MW). Furthermore, the study shows that, for organic and steam Rankine cycles, the optimal design configurations for the expanders do not coincide with those of the thermodynamic cycles. This suggests the possibility to obtain a more accurate analysis by including the computational model in the simulations of the thermodynamic cycles. Afterwards, the performance analysis is carried out by comparing three organic fluids: cyclopentane, MDM and R245fa. Results suggest MDM as the most effective fluid from the turbine performance viewpoint (total-to-total efficiency = 0.89). On the other hand, cyclopentane guarantees a greater net power output of the organic Rankine cycle (P = 5.35 MW), while R245fa represents the most compact solution (1.63 ton/MW and 0.20 m3/MW). Finally, the influence of the composition of an isopentane/isobutane mixture on both the thermodynamic cycle performance and the expander isentropic efficiency is investigated. Findings show how the mixture composition affects the turbine efficiency and so the cycle performance. Moreover, the analysis demonstrates that the use of binary mixtures leads to an enhancement of the thermodynamic cycle performance.

Design of an indirectly fired gas turbine integrated with an organic rankine cycle unit for combined heat and power production

In the last years, the European countries have paid increasing attention to renewable sources and greenhouse emissions. The Council of the European Union and the European Parliament have established ambitious targets for the next years. In this scenario, biomass plays a prominent role since its life cycle produces a zero net carbon dioxide emission. Additionally, biomass can ensure plant operation continuity thanks to its availability and storage ability. Several conventional systems running on biomass are available at the moment. Most of them are performant either in the large-scale or in the small power range. The absence of an efficient system on the small-middle scale inspired this thesis project. The object is an innovative plant based on a wet indirectly fired gas turbine (WIFGT) integrated with an organic Rankine cycle (ORC) unit for combined heat and power production. The WIFGT is a performant system in the small-middle power range; the ORC cycle is capable of giving value to low-temperature heat sources. Their integration is investigated in this thesis with the aim of carrying out a preliminary design of the components. The targeted plant output is around 200 kW in order not to need a wide cultivation area and to avoid biomass shipping. Existing in-house simulation tools are used: They are adapted to this purpose. Firstly the WIFGT + ORC model is built; Zero-dimensional models of heat exchangers, compressor, turbines, furnace, dryer and pump are used. Different fluids are selected but toluene and benzene turn out to be the most suitable. In the indirectly fired gas turbine a pressure ratio around 4 leads to the highest efficiency. From the thermodynamic analysis the system shows an electric efficiency of 38%, outdoing other conventional plants in the same power range. The combined plant is designed to recover thermal energy: Water is used as coolant in the condenser. It is heated from 60°C up to 90°C, ensuring the possibility of space heating. Mono-dimensional models are used to design the heat exchange equipment. Different types of heat exchangers are chosen depending on the working temperature. A finned-plate heat exchanger is selected for the WIFGT heat transfer equipment due to the high temperature, oxidizing and corrosive environment. A once-through boiler with finned tubes is chosen to vaporize the organic fluid in the ORC. A plate heat exchanger is chosen for the condenser and recuperator. A quasi-monodimensional model for single-stage axial turbine is implemented to design both the WIFGT and the ORC turbine. The system simulation after the components design shows an electric efficiency around 34% with a decrease by 10% compared to the zero-dimensional analysis. The work exhibits the system potentiality compared to the existing plants from both technical and economic point of view.

Fatigue Design Challenges of Transition Pieces from Decommissioned Platforms for Offshore Wind Energy

All structures are subjected to various loading conditions and combinations. For offshore structures, these loads include permanent loads, hydrostatic pressure, wave, current, and wind loads. Typically, sea environments in different geographical regions are characterized by the 100-year wave height, surface currents, and velocity speeds. The main problems associated with the commonly used, deterministic method is the fact that not all waves have the same period, and that the actual stochastic nature of the marine environment is not taken into account. Offshore steel structure fatigue design is done using the DNVGL-RP-0005:2016 standard which takes precedence over the DNV-RP-C203 standard (2012). Fatigue analysis is necessary for oil and gas producing offshore steel structures which were first constructed in the Gulf of Mexico North Sea (the 1930s) and later in the North Sea (1960s). Fatigue strength is commonly described by S-N curves which have been obtained by laboratory experiments. The rapid development of the Offshore wind industry has caused the exploration into deeper ocean areas and the adoption of new support structural concepts such as full lattice tower systems amongst others. The optimal design of offshore wind support structures including foundation, turbine towers, and transition piece components putting into consideration, economy, safety, and even the environment is a critical challenge. In this study, fatigue design challenges of transition pieces from decommissioned platforms for offshore wind energy are proposed to be discussed. The fatigue resistance of the material and structural components under uniaxial and multiaxial loading is introduced with the new fatigue design rules whilst considering the combination of global and local modeling using finite element analysis software programs.

Design and Implementation of Single phase 230V to Three Phase Inverter Based on the Embedded System STM-32 Applied to motor control

In the field of Power Electronics, several types of motor control systems have been developed using STM microcontroller and power boards. In both industrial power applications and domestic appliances, power electronic inverters are widely used. Inverters are used to control the torque, speed, and position of the rotor in AC motor drives. An inverter delivers constant-voltage and constant-frequency power in uninterruptible power sources. Because inverter power supplies have a high-power consumption and low transfer efficiency rate, a three-phase sine wave AC power supply was created using the embedded system STM32, which has low power consumption and efficient speed. It has the capacity of output frequency of 50 Hz and the RMS of line voltage. STM32 embedded based Inverter is a power supply that integrates, reduced, and optimized the power electronics application that require hardware system, software, and application solution, including power architecture, techniques, and tools, approaches capable of performance on devices and equipment. Power inverters are currently used and implemented in green energy power system with low energy system such as sensors or microcontroller to perform the operating function of motors and pumps. STM based power inverter is efficient, less cost and reliable. My thesis work was based on STM motor drives and control system which can be implemented in a gas analyser for operating the pumps and motors. It has been widely applied in various engineering sectors due to its ability to respond to adverse structural changes and improved structural reliability. The present research was designed to use STM Inverter board on low power MCU such as NUCLEO with some practical examples such as Blinking LED, and PWM. Then we have implemented a three phase Inverter model with Steval-IPM08B board, which converter single phase 230V AC input to three phase 380 V AC output, the output will be useful for operating the induction motor.