• Energy Research

The present work aims to suggest an innovative solution for seismic monitoring stations’ endurance. These stations are characterized by many different problems, such as lightning vulnerability, energy independence and noises disturbance. The suggested technology, for this type of application, is an improved bladeless turbo-expander patented by Nikola Tesla in the early 20th century, the Tesla turbine.

This paper presents a dynamic simulation of a heat pump using butane refrigerant for the purpose of integration with a combined cycle power system and thermal energy storage to enhance flexibility. A dynamic model of a heat pump system is developed using the Amesim software and the simulation result in the case of changing the heat source and heat sink conditions is shown to validate the simulation performance.

Fuel cells own the potential for significant environmental improvements both in terms of air quality and climate protection. Through the use of renewable primary energies, local pollutant and greenhouse gas emissions can be significantly minimized over the full life cycle of the electricity generation process, so that marine industry accounts renewable energy as its future energy source. The aim of this paper is to evaluate the use of methanol in Solid Oxide Fuel Cells (SOFC), as auxiliary power systems for commercial vessels, through Life Cycle Assessment (LCA). The LCA methodology allows the assessment of the potential environmental impact along the whole life cycle of the process. The unit considered is a 20 kWel fuel cell system. In a first part of the study different fuel options have been compared (methanol, bio-methanol, natural gas, hydrogen from cracking, electrolysis and reforming), then the operation of the cell fed with methanol has been compared with the traditional auxiliary power system, i.e. a diesel engine. The environmental benefits of the use of fuel cells have been assessed considering different impact categories. The results of the analysis show that fuel production phase has a strong influence on the life cycle impacts and highlight that feeding with bio-methanol represents a highly attractive solution from a life cycle point of view. The comparison with the conventional auxiliary power system shows extremely lower impacts for SOFCs.

Abstract Economic dispatch for micro-grids and district energy systems presents a highly constrained non-linear, mixed-integer optimization problem that scales exponentially with the number of systems. Energy storage technologies compound the mixed-integer or unit-commitment problem by necessitating simultaneous optimization over the applicable time horizon of the energy storage. The dispatch problem must be solved repeatedly and reliably to effectively minimize costs in real-world operation. This paper outlines a method that greatly reduces, and under some conditions eliminates, the mixed-integer aspect of the problem using complementary convex quadratic optimizations. The generalized method applies to grid-connected or islanded district energy systems comprised of any variety of electric or combined heat and power generators, electric chillers, heaters, and all varieties of energy storage systems. It incorporates constraints for generator operating bounds, ramping limitations, and energy storage inefficiencies. An open-source platform, EAGERS, implements and investigates this optimization method. Results demonstrate a >99% reduction in computational effort when comparing the newly minted optimization strategy against a benchmark commercial mixed-integer solver applied to the same combined cooling, heating, and power problem.

Abstract The current study aims to perform a stochastic analysis on microturbine compact recuperators to evaluate the impact of uncertainties in design parameters on their cost and volume, by using two different probabilistic approaches: Monte Carlo (MC) and Response Sensitivity Analysis (RSA). These two methods have been developed in Matlab® and then coupled with CHEOPE (Compact Heat Exchanger Optimisation and Performance Evaluation) software, which allows to analyze two different types of recuperators, used in microturbine applications: the furnace-brazed plate-fin type and the welded primary surface type. This paper focuses on an analysis of plate-fin type recuperators, for which the cost function adopted was tuned and verified in a previous study. Three main parameters of the recuperator have been considered as uncertain: effectiveness, hot side and cold side pressure drops. The uncertainties associated with these three parameters are based on industrial knowledge. The aforementioned stochastic methods have been used to propagate such uncertainties on the relevant outputs, such as cost and volume, allowing us to evaluate the least expensive and the most compact recuperator among those analysed.

Abstract This paper proposes a time-dependent, thermo-economic hierarchical approach for the analysis of energy districts and smart poly-generation microgrids, in order to determine the optimal size of different prime movers, required to meet the energy demand of a generic user. This approach allows for determining the optimal size for each component of the energy district, as well as defining its most efficient operation management for the entire year, taking into proper account the time-dependent nature of the electrical, thermal and cooling demands, which are the main constraints of the optimisation problem. Additionally, the proposed method takes into consideration both energy performance and operation costs. A specific case study is developed around the smart poly-generation microgrid at the University of Genoa, Savona Campus (Italy), which has been operational since 2013. In the original design, the microgrid includes different co-generative prime movers, renewable generators and a thermal storage system. In a second design an absorption chiller is included to supply the campus' energy cooling demand. Obtained results allowed identifying the best operation configuration, from a thermo-economic standpoint, for the considered scenario. The proposed method can be easily replicated in different applications and configurations of different smart poly-generative grids.

Abstract The purpose of this paper regards the design and testing of control systems for a 30-kW turbocharged solid oxide fuel cell system fuelled with biogas. The adoption of a turbocharger, instead of a micro gas turbine, for the fuel cell stack pressurisation, is an innovative solution that is expected to decrease the capital cost of such systems and to facilitate their penetration into the energy market. However, not being connected to an electric generator, the turbocharger rotational speed, and thus the air mass flow, cannot be directly controlled as in microturbines. The control of turbocharged solid oxide fuel cell systems is a novel topic, characterised by many technical challenges that have not been addressed before. To regulate the stack temperature, a cold bypass valve is included, connecting the compressor outlet to the turbine inlet. A dynamic model of this system was developed in Matlab-Simulink® to analyse the response of the turbocharged solid oxide fuel cell system to a cold bypass valve opening step change. System information obtained from this analysis was used to design and tune four controllers: a conventional proportional integral controller and three different cascade controllers. The controller performance was evaluated under two different scenarios, considering quite aggressive power ramps. The best results were obtained with a cascade controller, where the feedback loop was complemented by a feed-forward contribution based on power demand. This analysis demonstrated that such a control system effectively tracks the fuel cell maximum temperature target, complying with all the system operative constraints.

AbstractThis paper presents the development of a control approach for a smart polygeneration microgrid using the Model Predictive Control (MPC) paradigm. The importance of distributed generation systems has increased through recent years and questions of grid stability have emerged in the face of high concentrations of non-dispatchable power sources. Numerous proposals for “smart” distribution systems have emerged, including an architecture called the Energy Hub (E-Hub), which is a smart microgrid where both thermal and electrical power are supplied to customers by a mix of generator systems. The problem deals with a constrained Multi-Input Multi-Output (MIMO) optimization problem. This paper describes work underway on a real E-Hub located at the laboratories of the Thermochemical Power Group (TPG) of the University of Genoa (UNIGE), Italy. The TPG E-Hub is being integrated into a larger smart polygeneration grid under construction on the Savona campus of UNIGE as part of the European Union Resilient project. The proposed control approach aims to optimize the loading of various resources of the E-Hub in response to changing electrical and thermal demands from the campus-wide smart grid. This paper presents some of the results from initial testing of this approach to E-Hub control.

This paper presents the development, implementation and validation of a simplified dynamic modeling approach to describe SOFC/GT hybrid systems in three real emulator test-rigs installed at University of Genoa (UNIGE, Italy), German Aerospace Center (DLR, Germany) and National Energy Technology Laboratory (NETL, USA), respectively. The proposed modeling approach is based on an experience-based simplification of the physical problem to reduce model computational efforts with minimal expense of accuracy. Traditional high fidelity dynamic modelling requires specialized skills and significant computational resources. This innovative approach, on the other hand, can be easily adapted to different plant configurations, predicting the most relevant dynamic phenomena with a reduced number of states: such a feature will allow, in the near future, the model deployment for monitoring purposes or advanced control scheme applications (e.g. model predictive control). The three target systems are briefly introduced and dynamic situations analyzed for model tuning, first, and validation, then. Relevance is given to peculiar transients where the model shows its reliability and its weakness. Assumptions introduced during model definition for the three different test-rigs are discussed and compared. The model captured significant dynamic behavior in all analyzed systems (in particular those regarding the GT) and showed influence of signal noise on some of the SOFC computed outputs.