Tri-objective optimization of a waste-to-energy plant with super critical carbon dioxide and multi-effect water desalination for building application based on biomass fuels.

In the present research, an innovative biomass-based energy system for the production of electricity and desalinated water for building application is proposed. The main subsystems of this power plant include gasification cycle, gas turbine (GT), supercritical carbon dioxide cycle (s-CO2), two-stage organic Rankine cycle (ORC) and MED water desalination unit with thermal ejector. A comprehensive thermodynamic and thermoeconomic evaluation is performed on the proposed system. For the analysis, first the system is modeled and analyzed from the energy point of view, then it is examined similarly from the exergy point of view, and then an economic analysis (exergy-economic analysis) is performed on the system. Then, we repeat the mentioned cases for several types of biomasses and compare them with each other. Grossman diagram will be presented to better understand the exergy of each point and its destruction in each component of the system. After energy, exergy and economic modeling and analysis, the system is analyzed and modeled using artificial intelligence to help the system optimization process, and the model obtained with genetic algorithm (GA) to maximize the output power of the system, minimize the cost system and maximizing the rate of water desalination is optimized. The basic analysis of the system is analyzed inside the EES software, then it is transferred to the MATLAB software to optimize and check the effect of operational parameters on the thermodynamic performance and the total cost rate (TCR). It is analyzed and modeled artificially and this model is used for optimization. The obtained result will be three-dimensional Pareto front for single-objective and double-objective optimization, for work-output-cost functions and sweetening-cost rate with the specified value of the design parameters. In the single-objective optimization, the maximum work output, the maximum rate of water desalination, and the minimum TCR will be 55,306.89 kW, 17216.86 m3/day, and $0.3760/s, respectively.

Optimization Method for Energy Saving of Rural Architectures in Hot Summer and Cold Winter Areas Based on Artificial Neural Network.

With the phased spatial planning of the rural revitalization strategy, the proportion of architecture energy consumption in the overall social energy consumption is also increasing year by year. Considering the hot summer and cold winter areas, the proportion of architecture energy consumption in the total energy consumption is very large. The ecological environment and natural resources have been greatly threatened, and the issue of energy conservation and environmental protection is imminent. Energy consumption prediction and analysis is an important branch of building energy conservation in the field of building technology and science. Aiming at the energy consumption characteristics of rural architectures in areas with hot summer and cold winter, this paper proposes a method for constructing a neural network model. When building a neural network, the dataset is called and the function is applied randomly to training samples. The data are used for simulation tests to analyze the fit between the predicted results and the calculated results. Flexible forecasting of specific target building energy consumption is achieved, which can provide optimization strategies for updating and adjusting architecture energy efficiency design. The experimental analysis benchmark parameters and the output value in the dataset are compared with the target simulation value. The relative error is less than 4%, and the average relative error value (mean) and the root mean square error (RMSE) value are both controlled within 2%. It is proved that the method in this paper can directly reflect the evaluation of energy consumption by the neural network and realize the high-speed conversion of the generalized model to the concrete goal, which has a certain value and research significance.

Evaluation and Analysis of Quantitative Architectural Space Index Based on Analytic Hierarchy Process.

With the continuous development of the social economy, the urban residential structure is also changing, and people have higher and higher requirements for the living environment. Moreover, the landscape construction of public spaces in cities is an important part of the city. It is easy to neglect the comprehensive consideration of historical development and regional culture in architectural projects. The overall lack of individuality in urban design, the lack of characteristics of adapting measures to local conditions, and the blind emphasis on architectural landscaping have led to a serious lack of regional cultural characteristics and spiritual culture in public places. Therefore, in terms of the problems of insufficient landscape construction quality and green concepts being insufficient in the construction environment of cities, an evaluation method system is established in the paper to further study the shortcomings of the scenic area architecture. What is more, relying on the personal experience of the users in the scenic spot and understanding the real needs of the public space landscape environment around the scenic spot, scientific methods and a complete system are applied to make an overall assessment of the public space in the built residential area. Besides, according to the data analysis of the simulation experiment, the advantages and disadvantages of the public space in the residential area are extracted. Combined with the current research status, the green concept design strategy of the public space landscape environment in the scenic spot is summarized. Lastly, according to the data analysis of the simulation experiment, the evaluation satisfaction of the activity atmosphere, plant configuration, and overall layout is improved by 4.2%, 3.7%, and 3.1% compared with other methods, which proves that this study has a more reasonable planning program to meet the various needs of public open space. The development of urban landscape design provides a valuable reference.