Search Results (6)

This paper introduces a novel five-port, three-input, dual-output isolated bidirectional dc-dc converter (FPIBC) topology with an effective controller for power-sharing and voltage-balancing in bipolar dc microgrids (BPDCMGs). The proposed converter acts as the interface for the integration of a hybrid generation system comprising a solid oxide fuel cell (SOFC), a photovoltaic (PV) system, and a battery into BPDCMGs. It employs a reduced number of circuit elements compared with similar multiport converter topologies suggested for BPDCMG applications. Symmetrical bipolar output voltages are ensured by a voltage-balancing circuit composed of a fully controlled switch and four diodes. The FPIBC is equipped with different controllers for output voltage regulation and balancing, power sharing, maximum power point tracking of the PV, the optimum operating region of the SOFC, and constant-current, constant-voltage charging of the battery. To verify the viability and effectiveness of the proposed system, a simulation model was developed with a 4.2 kW SOFC, a 3.7 kW PV, and a 140 V 10.8 Ah battery in MATLAB/Simulink. The performance of the FPIBC was evaluated through extensive case studies with different operational modes, including battery charge/discharge states and SOFC and PV parameter changes under varying load conditions. In addition, the proposed system was examined using a daily dynamic load profile. According to the simulation results, a peak efficiency of 97.28% is achieved and the voltage imbalance between the output ports is maintained below 0.5%. It is shown that the FPIBC has advantages over previous converters in terms of the number of ports, number of circuit elements, bipolar output voltage, bidirectional power flow, and efficiency. Full article

Hydrogen (H₂) energy is an ideal non-polluting renewable energy and can achieve long-term energy storage, which can effectively regulate the intermittence and seasonal fluctuation of solar energy. Solid oxide fuel cells (SOFC) can generate electricity from H₂ with only outputs of water, waste heat, and almost no pollution. To solve the power generation instability and discontinuity of solar photovoltaic (PV) systems, a hybrid PV-SOFC power generation system has become one feasible solution. The “digital twin”, which integrates physical systems and information technology, offers a new view to deal with the current problems encountered during smart energy development. In particular, an accurate and reliable system model is the basis for achieving this vision. As core components, the reliable modelling of the PV cells and fuel cells (FCs) is crucial to the whole hybrid PV-SOFC power generation system’s optimal and reliable operation, which is based on the reliable identification of unknown model parameters. Hence, in this study, an artificial rabbits optimization (ARO)-based parameter identification strategy was proposed for the accurate modelling of PV cells and SOFCs, which was then validated on the PV double diode model (DDM) and SOFC electrochemical model under various operation scenarios. The simulation results demonstrated that ARO shows a more desirable performance in optimization accuracy and stability compared to other algorithms. For instance, the root mean square error (RMSE) obtained by ARO are 1.81% and 13.11% smaller than that obtained by ABC and WOA algorithms under the DDM of a PV cell. Meanwhile, for SOFC electrochemical model parameter identification under the 5 kW cell stack dataset, the RMSE obtained by ARO was only 2.72% and 4.88% to that of PSO for the (1 atm, 1173 K) and (3 atm, 1273 K) conditions, respectively. By establishing a digital twin model for PV cells and SOFCs, intelligent operation and management of both can be further achieved. Full article

Renewable energy sources based on solar and wind energy provide clean and efficient energy. The intermittent behaviour of these sources is challenging. At the same time, the needs for efficient, continuous and clean energy sources are increased for serving both electricity and thermal demands for residential buildings. Consequently, complimentary systems are essential in order to ensure a continuous power generation. One of the promising energy sources that helps in reducing CO₂ emissions, in addition to providing electrical and thermal energy efficiently, is a Solid Oxide Fuel Cell (SOFC) system operated in a combined heat and power (CHP) mode, due to high electrical efficiencies (in full and part load) and the fuel flexibility. Currently, most studies tend to focus on fuel cell model details with basic information about the building’s energy requirements. Nevertheless, a deep understanding of integrating fuel cell micro-CHP systems with renewable energy systems for the residential sector is required. Moreover, it is important to define an operating strategy for the system with a specific controlling method. This helps in evaluating the performance and the efficiency of the building energy system. In this study, an investigation of different configurations of a hybrid power system (HPS) was carried out. The intended aim of this investigation was to optimize a HPS with minimal CO₂ emissions, serving the energy demands for a single-family house efficiently and continuously. As a result of this study, a photovoltaic (PV)/SOFC micro-CHP system has satisfied the intended goal, where the CO₂ emissions are significantly reduced by 88.6% compared to conventional systems. The SOFC micro-CHP plant operated as a complimentary back-up generator that serves the energy demands during the absence of the solar energy. Integrating the Power to Gas (PtG) technology leads to a similar emission reduction, while the PtG plant provided a seasonal energy storage. The excess energy produced during summer by the PV system is stored in the fuel storage for a later use (during winter). This SOFC micro-CHP configuration is recommended from an energy and environmental perspective. In terms of feasibility, the costs of SOFC based micro-CHP systems are significantly higher than traditional technologies. However, further technology developments and the effect of economy of scale may cause a substantial drop in costs and the micro-CHP shall become economically competitive and available for residential users; thus, enabling a self-sufficient and efficient energy production on site. Full article

A small-scale, decentralized hybrid system is proposed for autonomous operation in a commercial building (small hotel). The study attempts to provide a potential solution, which will be attractive both in terms of efficiency and economics. The proposed configuration consists of the photovoltaic (PV) and solid oxide fuel cell (SOFC) subsystems. The fuel cell subsystem is fueled with natural gas. The SOFC stack model is validated using literature data. A thermoeconomic optimization strategy, based on a genetic algorithm approach, is applied to the developed model to minimize the system lifecycle cost (LCC). Four decision variables are identified and chosen for the thermoeconomic optimization: temperature at anode inlet, temperature at cathode inlet, temperature at combustor exit, and steam-to-carbon ratio. The total capacity at design conditions is 70 and 137.5 kWe, for the PV and SOFC subsystems, respectively. After the application of the optimization process, the LCC is reduced from 1,203,266 to 1,049,984 USD. This improvement is due to the reduction of fuel consumed by the system, which also results in an increase of the average net electrical efficiency from 29.2 to 35.4%. The thermoeconomic optimization of the system increases its future viability and energy market penetration potential. Full article

New energy solutions are needed to decrease the currently high electricity costs from conventional electricity-only central power plants in Cyprus. A promising solution is a decentralized, hybrid photovoltaic-solid oxide fuel cell (PV-SOFC) system. In this study a decentralized, hybrid PV-SOFC system is investigated as a solution for useful energy supply to a commercial building (small hotel). An actual load profile and solar/weather data are fed to the system model to determine the thermoeconomic characteristics of the proposed system. The maximum power outputs for the PV and SOFC subsystems are 70 and 152 kWe, respectively. The average net electrical and total efficiencies for the SOFC subsystem are 0.303 and 0.700, respectively. Maximum net electrical and total efficiencies reach up to 0.375 and 0.756, respectively. The lifecycle cost for the system is 1.24 million USD, with a unit cost of electricity at 0.1057 USD/kWh. In comparison to the conventional case, the unit cost of electricity is about 50% lower, while the reduction in CO₂ emissions is about 36%. The proposed system is capable of power and heat generation at a lower cost, owing to the recent progress in both PV and fuel cell technologies, namely longer lifetime and lower specific cost. Full article

Solar power generation is intermittent in nature. It is nearly impossible for a photovoltaic (PV) system to supply power continuously and consistently to a varying load. Operating a controllable source like a fuel cell in parallel with PV can be a solution to supply power to variable loads. In order to coordinate the power supply from fuel cells and PVs, a power management system needs to be designed for the microgrid system. This paper presents a power management system for a grid-connected PV and solid oxide fuel cell (SOFC), considering variation in the load and solar radiation. The objective of the proposed system is to minimize the power drawn from the grid and operate the SOFC within a specific power range. Since the PV is operated at the maximum power point, the power management involves the control of SOFC active power where a proportional and integral (PI) controller is used. The control parameters of the PI controller K_p (proportional constant) and T_i (integral time constant) are determined by the genetic algorithm (GA) and simplex method. In addition, a fuzzy logic controller is also developed to generate appropriate control parameters for the PI controller. The performance of the controllers is evaluated by minimizing the integral of time multiplied by absolute error (ITAE) criterion. Simulation results showed that the fuzzy-based PI controller outperforms the PI controller tuned by the GA and simplex method in managing the power from the hybrid source effectively under variations of load and solar radiation. Full article