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To promote the continuous operating of solar energy systems and increase the proportion of renewable energy consumption, solar devices are often integrated with conventional energy systems to reduce greenhouse gas emissions. In this study, a solar-natural gas coupling system is constructed, utilizing solar photovoltaics, thermal collectors, and high-efficiency energy conversion devices. After modelling the energy system, the operating modes are illustrated considering working sequences of water-cooled devices. A modified genetic algorithm, which incorporates reverse learning, controlled elite, and dynamic crowding distance theory, is constructed to optimize the configurations of the proposed energy system, with the aim of minimizing carbon and economic prices of the products. The performance of the energy system is compared with different algorithms and cases, and the results demonstrate that the proposed algorithm addresses the limitations of conventional methods, albeit with increased optimization times. Moreover, the proposed operating mode (Case 1) exhibits a stable performance, leading to a higher environmental and economic performance compared to conventional modes, with carbon and economic prices of 0.242 kg/kWh and 0.067 $/kWh, respectively. This study provides new insights into carbon footprints and economic performance evaluation of high-efficiency energy systems, offering valuable directions for future research in this field. [Display omitted] • A solar-natural gas coupling system to fulfill building multiple demands. • Comparisons of fours cases considering operating sequences of two types of chillers. • Modified genetic algorithm using reverse learning, elite controlled, dynamic crowding distance theory. • Carbon and economic prices of the products are illustrated. [ABSTRACT FROM AUTHOR]

[Display omitted] • Cascading utilization of solar full-spectrum irradiance. • Solar-wind-gas system to fulfill heat and power demands. • Carbon trading and demand response methods in a system view. • Carbon footprint analysis from an ecological perspective. • Sensitivity analysis among ratios of replaceable/price-type demand and specific carbon cost. The integration of solar full-spectrum and wind devices into district energy systems presents a promising avenue for reducing fuel consumption and advancing renewable energy utilization. To meet the heat and power demands of an industrial park, a solar-wind-gas coupling system is proposed, leveraging an organic Rankine cycle for efficient utilization of renewable and waste heat. Through the optimization of profit maximization via integrated demand response and carbon trading mechanisms, the specific carbon footprint in an ecological perspective considering both direct and indirect emissions is estimated. The findings reveal significant cost savings for users exceeding $400 through the demand response method, alongside a 5% reduction in operating costs for the system through carbon trading, albeit with elevated carbon footprints in energy and exergy domains. Moreover, higher carbon prices are shown to enhance profits due to increased award costs in carbon trading, while concurrently resulting in heightened ecological carbon emissions. This research extends traditional dispatching methods by integrating ecological carbon footprint analysis, offering valuable insights for sustainable energy management strategies. [ABSTRACT FROM AUTHOR]

Introducing renewable and high-efficiency devices into conventional cogeneration systems has the potentials to reduce fossil fuel consumption and mitigate environmental issues. This study aims to incorporate solar power and thermal energy into the power and waste heat generated by the gas turbine, respectively, while utilizing a double-effect absorption heat pump to meet the total heat demands. Following the creation of thermodynamic models, a trading mechanism is introduced involving an operating participant known as the product seller, which is analogous to electricity companies in power trading models. To maximize the interests of the participants with different confidence levels, the master-slave game is employed, using Genetic and Quadratic programming algorithms. The hourly outputs of devices and responded demands are evaluated based on the dynamic purchasing and selling price of products. The results indicate that the optimal interest of the cogeneration system is the lowest among all the participants. The power proportions from gas turbine and power grid exceed 60 %, while the contribution of gas turbine decreases by 11.0 % due to the lower heat demands caused by reduced confidence level. Overall, this study offers valuable insights into the market-oriented development of solar assisted cogeneration systems. [ABSTRACT FROM AUTHOR]

A weather-based energy system consisting of a tri-generation unit, photovoltaics, and water-cooled chiller is proposed here for improving the energy and environmental performance. Together with capacities of other devices, the cooling ratio, and capacities of different types of chiller are optimized to find the ideal system configuration setting the energy and cost savings and renewable energy use as the objectives. In addition, daily and monthly operating modes with the optimal system composition are analyzed followed by a sensitivity analysis. The results show that increasing energy saving ratio improves the cost saving benefits, but the renewable energy penetration rate would decrease due to lower grid electricity consumption. The ideal system configuration in ratio optimization process has a higher gas turbine and chiller capacity resulting in higher performance than the system with capacity optimization process, or 2.7%, 1.6%, and 0.2%-unit higher of the considered indices. When increasing the specific cost of the chiller, cost saving ratio of the ideal system decreases, while the impacts on the energy savings and renewable energy use are lower. The analysis indicates that the price of grid electricity is the most sensitive factor, while the influence of carbon cost is slight. • Weather-based energy system with PV and water-cooled chiller. • Capacity and ratio optimization processes with three types of chiller. • Ideal energy, cost, and renewable benefits are 51.9%, 55.6% and 25.0%, with a cooling ratio of 69.1%. • The chiller reaches a yearly average COP of 7.5. [ABSTRACT FROM AUTHOR]

Advanced solar driven tri-generation systems are highly relevant to reduce emissions and increase energy security. Here, solar collectors and photovoltaics are coupled to a tri-generation system to produce multiple final energy forms simultaneously for an office building. The excess solar electricity is employed for cooling/heating through a power-to-heat conversion employing thermal energy storage. Comprehensive optimization is performed to maximize the energy, environmental, and economic benefits, and the carbon tax is included to monetize the emissions. A coupled decision-making method is then used to choose the ideal scheme from the optimized sets of system configuration accompanied with a sensitivity analysis against key parameters. Compared to the conventional system, the proposed system improves the energy performance by 41.4% and the environmental benefits by 41.7% with the highest solar energy utilization rate. The economic performance improves in the best case by 14.4% only, but with the lowest utilization rate of solar energy. The ideal solution covers 30%, 54%, and 62% of the electricity, cooling, and heating loads, respectively, and the corresponded energy, environmental, and economic performance improves by 29.1%, 34.6%, and 7.7%, respectively. The sensitivity analysis shows that the economic performance is more sensitive to the electricity price than to the carbon tax. • A novel solar powered trigeneration system considering excess PV power to heat storage. • Equivalent coal consumption and carbon tax in energy and economic performance. • Coupling decision-making method after multi-objective optimization. • Solar energy covers 30% of electric, 54% of cooling and 62% of heating loads. • Sensitivity analysis against key parameters. [ABSTRACT FROM AUTHOR]

Under the dual background of global climate change and regional air pollution, the emission reduction effect of renewable energy has received increasing attention worldwide. However, few studies have evaluated the nonlinear effects and spillover effects of renewable energy consumption (REC) on economy and environment over space and time. In this study, we select panel data from 30 Chinese provinces from 2005 to 2017 and construct multiple models to quantitatively evaluate the nonlinear effects, spatial spillover effects, and spatio-temporal heterogeneity effects of REC on China's economy and the environment. The results show that REC has an N-shaped curve relationship with economic growth and has an inverted N-shaped curve relationship with haze pollution and carbon emissions. Furthermore, we find that the spatial spillover effect of REC is larger than the local effect. Interestingly, REC has a negative impact on economic growth in 40% of provinces, increases haze pollution in 30% of provinces, and increases carbon emission in 60% of provinces. It is worth noting that the current impact of REC on carbon emissions in China is at a stage of switching from negative to positive effects (60% of provinces have a positive impact). • REC has an inverted N-shaped curve relationship with environmental pollution. • REC has an N-shaped curve relationship with economic growth. • The spatial spillover effect of REC is larger than the local effect. • REC can decrease economic growth in 40% of China's provinces. • REC can increase haze pollution and carbon emission in 30% and 60% of provinces. [ABSTRACT FROM AUTHOR]