This study involves the application of artificial neural network (ANN) as an intelligent approach to predict the output power of one alpha-type Stirling engine under some operating conditions. One ANN model had been developed based on experimental data from published literature. Output power as one of the performance indicators, was chosen as a response to input parameters, heat source temperature, engine speed and charging pressure. A multi-layer feed-forward network with a back-propagation algorithm had been proposed for such a prediction. The ANN model had been proven to be desirable in accuracy for predicting the output power by comparing the model results with experimental ones under the same operating conditions. This work would provide an effective approach based on ANN technique for solving complex design problems either with linear or nonlinear nature.
This study is part of an investigation on the influences of future energy demand and increased application of renewable resources on production planning of a regional energy system in the central part of Sweden. The study addresses the impacts of power supply from rooftop solar cells, increased application of heat pumps and penetration of electric passenger cars. Optimization results imply that use of heat pumps to replace district heating affects the demand side and reduces the heat production from energy plants. However, the power imports increase by 22%, compared with the reference system. By contrast, 100% penetration of electric vehicles in the transportation system only increases the power imports, without substantial effects on the energy plants performance.
In this work, aqueous pentaethylenehexamine (PEHA) was studied as a solvent for CO2 removal to produce purified bio-syngas from biomass gasification, but also as a first step towards negative carbon emissions applying carbon capture and storage (CCS) technologies. Capture of CO2 was tested both with synthetic gas (labscale) and real syngases from the pilot-scale gasifier fed with a wide range of forest-based biomasses. The results showed that the effects of the components other than CO2 and the impurities from the real syngas on the performance of PEHA for CO2 removal are negligible. Combined with previous research results from labtesting with pure CO2 absorption, the aqueous PEHA was shown to be a promising solvent for CO2 removal from syngas. PEHA was also tested as a biomass pre-treatment agent to improve gasification behavior, however, no significant improvement could be identified during the tests performed in this study.
Promoting clean heating in winter in the northern region is related to the warmth of the masses in the northern region and whether fog and haze can be reduced. On the basis of summarizing the current situation of heating in rural areas of northern China, this paper expounds the practical problems and basic needs of clean heating. Taking Shandong as the research object, this paper studies the applicability of different modes of clean heating technology in rural areas of North China.The author calculates the heat load demand during heating period, screens the suitable clean heating technology in Shandong area, and obtains the suitable technical path and application mode for rural clean heating in Shandong area.The technical feasibility, economic feasibility and environmental impact of different modes of clean heating, such as solar heating, gas heating and biomass pyrolysis multi-generation heating, are analyzed. The results show that under the existing economic and technological conditions, biomass pyrolysis polygeneration is suitable for clean heating in rural areas of Shandong Province, especially for demonstration and promotion of small centralized or decentralized heating in natural villages or new rural communities. This study provides a new way to solve the problem of clean heating in rural areas of northern China.
Hourly energy readings from heat billing meters are valuable data source for energy performance assessment of district heating substations and the buildings they serve. The quality of such analyses is bounded by the accuracy of the hourly readings. Thus, assessing the accuracy of the hourly heat meter readings is a necessary (but often overlooked) first step to ensure qualitative subsequent analyses. Due to often limited bandwidth capacity hourly readings are quantized before transmission, which can cause severe information loss. In this paper we study 266 Swedish heat meters and assess the quantization effect by information entropy ranking. Further, a detailed comparison is conducted with three heat meters with typically occurring quantization errors. Uncertainty due to the quantization effect is compared with the uncertainty due to typical accuracy of the meter instrumentation. A method to conflate information from both energy readings and energy calculated from flow and temperature readings is developed. The developed conflation method is shown to be able to decrease uncertainty for heat meters with severely quantized energy readings. However, it is concluded that a preferable approach is to work with the heat meter infrastructure to ensure future recorded readings holds high enough quality to be useful for energy performance assessments with hourly or subhourly readings.
Optical fiber daylighting system is a promising alternative for indoor illumination, which provides not only comfortable and safe lighting but also environmental benefits. Economic analysis results show that, total cost of traditional fluorescent lighting system is higher than that of hybrid optical fiber daylighting system after 7 years of operation. In addition, results of environmental benefits for the studied case show that, an annual average 39410kg of CO2 emission can be reduced when traditional lighting system is replaced by the hybrid daylight system. The potential of applying the hybrid optical fiber daylighting system to save energy and protect environment is promising.
In this study the performance characteristic of a CO2 ejector-expansion system applied for battery pack cooling is investigated. An experimental bench is set up and the performance of the system is experimentally studied under different working conditions. The cooling capacity and COP of the system decrease with the increasing of gas cooler outlet temperature. There is an optimal opening degree of EEV for both the capacity and COP to get a maximum value. The entrainment ratio of the ejector is improved by introducing an IHX. Compared with the basic cycle, ejector-expansion system can improve both the cooling capacity and COP significantly, around 21.7% increment in cooling capacity and 28.0% increment in COP, respectively.
With the large-scale penetration of electric vehicles, the research on the influence factors of energy consumption of electric vehicles has become an important requirement for the estimation of energy efficiency, energy-saving route planning and the optimal design of power system structure. In this paper, the real-world driving data of 59 electric taxis in Beijing are obtained and divided into three-level driving fragments. The influence factors of energy consumption, including vehicle-related factors (velocity, acceleration and kinematic states), environment-related factors (ambient temperature and traffic condition) as well as driver-related factors are extracted and studied. Results show that the energy consumption of electric vehicle is significantly influenced by velocity, acceleration and kinematic states. Benefit from the energy-saving at idling state and the braking energy regeneration technology, traffic congestion has a slighter influence on energy consumption. Besides, the appropriate ambient temperature around 19.5℃ and moderate driving pattern can help reduce energy consumption to a certain extent. This work builds an essential foundation for accurate estimation and prediction of energy consumption of electric vehicles.
The hybrid wind-based pumped hydro storage system that absorbs the wind curtailment due to grid limitations is considered to be a solution to improve wind energy penetration and the cost-effectiveness of wind farms. An offshore wind-pumped hydro storage hybrid power system connected to thermal supplied main grid is proposed in this paper. The contribution of this paper can be summarized as follows: (1) a multi-objective dynamic economic optimization model for the proposed system based on evolutionary algorithms is established to optimize size for offshore wind-based pumped hydro storage system; (2) design parameters include the capacity of pump, turbine and reservoirs, and the key financial parameters such as wind power feed-in tariff and capacitor price of pumped hydro storage power station are also taken into account; and (3) examine the attainability of various objectives to analyze the influence on the operation and economic effectiveness. The results show that the optimizing size study is importance to test the economic feasibility of the system. The case study presented in this paper provides decision makers with the flexibility to choose the appropriate capacity installation under different expectations.
Liquid air energy storage system using Kapitza cycle is thermodynamically optimized with selected critical process variables by partial enumeration. With this method, the contour maps for the independent variables are illustrated, that give intuition to the behavior of the LAES systems. The Interaction between the variables can be found and thermodynamically analyzed. The optimized thermodynamic efficiency 40.0%, 48.8%, and 51.2% when compression pressure is set at 40 bar, 80 bar, and 120 bar, respectively.