• Energy Research

Abstract Combined cooling, heating, and power systems have been studied extensively because of their great potentials. Accordingly, in the present study, an innovative trigeneration system including a gas turbine cycle, a gasification unit, a heating unit, alongside a single effect absorption refrigeration cycle is proposed. The system operates on natural gas and municipal solid waste (MSW) for cooling, heating, and power generation. The designed system was simulated using Engineering Equation Solver (EES) software through two scenarios; constant power output and constant biomass feed rate, considering seasonal and annual periods. In the first scenario, considering the constant power capacity, the basic design state was considered with the biomass mixing ratio of 50%, and the results of the seasonal study showed that the system capacity is 30 MW , 41.9 MW , and 39.24 MW in terms of electricity, heating, and cooling, respectively. The exergy analysis revealed that the combustion chamber, the evaporator of Heat Recovery Steam Generator (HRSG), and the gasifier in both hot and cold seasons have the highest exergy destruction rate, while the economizers and the evaporators of both HRSGs have the lowest exergy efficiency. The constant mass flow rate of MSW was assumed to be 1.5 kg / s and accordingly, the feed rate of natural gas was also 1.5 kg / s for the mixing ratio of 50% in basic design state of the second scenario, and the results indicated that the annual average capacity of the system for electricity, heating, and cooling generation is 27.43 MW , 40 MW , and 34.15 MW , respectively. Furthermore, the system was capable of providing the domestic hot water supply of end-user with an average capacity of 7.5 MW during a year. The annual Energy Utilization Factor (EUF) and the annual exergy efficiency of the overall system were shown to be 71.25% and 30.79%, respectively.

To enable net zero sustainable thermal building energy, this study develops an open-source thermal house model to couple solar photovoltaic (PV) and heat pumps (HPs) for grid-connected residential housing. The calculation of both space heating and cooling thermal loads and the selection of HP is accomplished with a validated Python model for air-source heat pumps. The capacity of PV required to supply the HPs is calculated using a System Advisor Model integrated Python model. Self-sufficiency and self-consumption of PV and the energy imported/exported to the grid for a case study are provided, which shows that simulations based on the monthly load profile have a significant reduction of 43% for energy sent to/from the grid compared to the detailed hourly simulation and an increase from 30% to 60% for self-consumption and self-sufficiency. These results show the importance of more granular modeling and also indicate mismatches of PV generation and HP load based on hourly simulation datasets. The back-calculation PV sizing algorithm combined with HP and thermal loads presented in this study exhibited robust performance. The results indicate this approach can be used to accelerate the solar electrification of heating and cooling to offset the use of fossil fuels in northern climates.

Abstract Waste heat recovery (WHR) of internal combustion engines (ICEs) is a subject of study for researchers concerned with energy conservation. For this purpose, various bottoming cycles, along with the influences of Steam-Assisted Turbocharger (SAT) on diesel engines' performances, have sufficiently been investigated. In this paper, a cogeneration system powered by a steam-assisted turbocharged marine Diesel engine and an organic Rankine cycle (ORC) is thermodynamically evaluated. Seawater is desalinated by a Reverse-Osmosis (RO) module to provide freshwater for heating units and engine's cooling jacket. Exergy analysis reveals that the condenser, the RO module, the heat exchanger 1, and the oil cooler are the devices with the lowest exergy efficiencies. Furthermore, the genetic algorithm is used to optimize the system parameters and determine the best combination of the proposed system. Results indicate that the combination of SAT with other components can negatively affect the cogeneration system's overall efficiency. On the optimal state, the system exhibits cogeneration energy and exergy efficiencies of 82.82% and 54.10%, respectively, being 2.18 and 1.54 times higher than the sole engine. The optimized system offers a net electrical power of 668 kW and a heating capacity of 646.3 kW through supplying process steam and domestic hot water (DHW).

To control the volatility and reduce the electricity costs for indoor farming, the agrivoltaics agrotunnel introduced here uses: 1) high insulation for a building dedicated to vertical growing, 2) high-efficiency LED lighting, 3) heat pumps (HPs), and 4), solar photovoltaics (PV) provide known electric costs for 25 years. In order to size the PV array, this study develops a thermal model for agrotunnel load calculations and validates it using the Hourly Analysis Program and measured data so the effect of plants’ evapotranspiration can be included. HPs are sized, plug loads (i.e., water pump energy needed to provide for the hybrid aeroponics/hydroponics system, DC power running the LEDs hung on grow walls, and dehumidifier assisting in moisture condensation in summer) are measured/modeled. Ultimately, all models are combined to establish an annual load profile for an agrotunnel that is then used to model the necessary PV to power the system throughout the year. The results find that agrivoltaics to power an agrotunnel range from 40 to 50kW and make up an areas from 3.2 to 10.48 m²/m² of an agrotunnel footprint. Net zero agrotunnels are technically viable although future work is needed to deeply explore the economics of localized vertical food growing systems.

Greenhouses extend growing seasons in upper latitudes to provide fresh, healthy food. Costs associated with carbon-emission-intensive natural gas heating, however, limit greenhouse applications and scaling. One approach to reducing greenhouse heating costs is electrification by using waste heat from cryptocurrency miners. To probe this potential, a new quasi-steady state thermal model is developed to simulate the thermal interaction between a greenhouse and the environment, thereby estimating the heating and cooling demands of the greenhouse. A cryptocurrency mining system was experimentally evaluated for heating potential. Using these experimental values, the new thermal model was applied to the waste heat of the three cryptocurrency mining systems (1, 50, and 408 miners) for optimally sized greenhouses in six locations in Canada and the U.S.: Alberta, Ontario, Quebec, California, Texas, and New York. A comprehensive parametric study was then used to analyze the effect of various parameters (air exchange rate, planting area, lighting allowance factor, and photoperiod) on the thermal demands and optimal sizing of greenhouses. Using waste heat from cryptocurrency mining was found to be economically profitable to offset natural gas heating depending on the utility rates and Bitcoin value in a wide range of scenarios.