•Modeling of heat and mass transfer in an air dehumidification system is performed.•Energy efficiency and performance of the system are calculated.•Effects of operating, structural, and transport ...parameters are analyzed.•Operating parameters are optimized by the energy efficiency and performance.•Backpropagation neural network and genetic algorithm are used for the optimization.
In air dehumidification systems, the optimization of operating conditions is as important as the improvement of the dehumidifier itself under varying loads. Therefore, a comprehensive parameter analysis and optimization study of a novel air dehumidification system, which consists of a multilayer fixed-bed binder-free desiccant dehumidifier and a water cooling and heating device, is proposed herein. First, a mathematical model to predict the transient heat and mass transfer in the air dehumidification system is established and validated by comparing with the experimental results. Second, the cyclic performance of the system is analyzed and the influences of each parameter, including operating, structural, and adsorption and transport parameters, are analyzed. Third, the optimization of operating parameters is conducted based on the combination of a backpropagation (BP) neural network and genetic algorithms (GAs). The operating parameters are optimized by maximizing the energy efficiency and dehumidification performance and a trade-off relation is identified between them. For three typical load conditions, it is successfully demonstrated that the optimum energy efficiency and dehumidification performance can be determined from the Pareto front obtained by an elitist non-dominated sorting GA (NSGA Ⅱ) within the requirement specifications and the optimum operating parameters can also be determined by the combination of a BP neural network and a NSGA Ⅱ.
The paper is devoted to the main results of the development and application of a multilevel approach to mathematical and computer modeling of large-scale pipeline systems. The approach is intended to ...overcome the problems of dimension of such systems, as well as fragmentation of information and methodological support of modeling tasks that are dealt with at different departmental, regional, organizational and temporal levels of decision-making on the control of pipeline system expansion and operation. The principles and experience of the implementation of a computer platform for the automation of customization and use of multilevel information and computational models of pipeline systems of various purposes are characterized. Heating systems are used as an example to set forth the mechanisms for implementing the multilevel approach to calculate and analyze operating conditions in the design, operation and dispatch control. The formalization of the hydraulic planning task is presented as a discrete-continuous optimization problem of large dimension with multiple criteria. A new procedure for hierarchical optimization of hydraulic conditions and new methods to solve the problems of optimization of different hierarchical levels and coordination of solutions are presented. This approach could be useful in calculation of energy systems (heat, gas, water, electricity, etc.).
The operation of complex energy systems for the supply of heat and electricity leads to several questions regarding their optimal control, e.g. when to use which generator, when to load or unload ...energy storages or when to buy or sell energy. Usually it is a complex task to answer these questions with the aim of optimizing a specific objective and respecting all arising physical, technical and economic constraints.
Since 25 years we are solving this problem for an energy provider of a medium-sized city with the aim of minimizing the operational costs. For this purpose, an own modelled mixed-integer linear optimization problem (MILP) has to be solved in association to the continuous operation of the energy system. The model includes but is not limited to several combined heat and power generators, heat accumulators, steam generators and auxiliary coolers.
In this presentation we will give an outline about the wide range of given conditions that are successfully implemented for this application. Further we show our approach to generate realistic heat demand and power consumption forecasts which are both essential preconditions for obtaining reliable optimization results.
In addition to the well – established MILP model in this specific use case we will outline some further promising applications of mathematical optimization in the context of energy systems. This includes the more precise modelling of energy storages, the computation of the optimal design of energy systems and the consideration of different or multiple targets in optimization. Moreover, we outline the problem of uncertain boundary conditions due to the growing amount of temporally hard to predict energy production and demand.
Given the increasing capacity of distributed generation and renewable resources, how to use this capacity and proper energy management will be a major challenge for low-capacity networks such as ...microgrids. With the help of peripherals tools, an arrangement can be made to achieve a more desirable result in the energy management system (EMS). Storage resources and at a higher level, the storage module is used as one of these tools in the subsystems of the EMS. In this article, in addition to taking advantage of the connection of several microgrids to each other and reducing interactions with the main network, by using the storage module and other related tools, the cost of providing energy to a cluster of microgrids is reduced to the lowest possible value. By implementing a mathematical model based on mixed-integer linear programming, the best program for generation resources obtains in such a way that the cost of energy supply reduces to the minimum value. The study results have been analyzed in two case studies; a modified laboratory microgrid and the IEEE 33-bus distribution network. Although different solvers in Gams will provide almost similar answers, the optimal answer was found by the Cplex solver.
In this study, the optimization of nitrate removal from wastewater with a low C/N ratio using solid-phase denitrification was investigated. Biodegradable polymer, an attractive alternative to liquid ...carbon sources for biological denitrification, was used as a carbon source and biofilm support for nitrate removal. An experiment was conducted based on a central composite design (CCD) with response surface methodology (RSM). A secondary polynomial regression with nitrate removal efficiency as response value was developed. Based on statistical analysis, the nitrate removal model was highly significant with very low probability values (<0.0001). At the optimal conditions for nitrate removal (hydraulic retention time (HRT), 3.5 h; influent NO₃ ⁻-N concentration, 14.73 mg/L; and influent CODCᵣ concentration, 15.00 mg/L), the nitrate removal efficiency was 99.23 %. The results of an ANOVA and response surface analysis showed that HRT, influent NO₃ ⁻-N concentration, influent CODCᵣ concentration, and the interaction between the HRT and influent CODCᵣ concentration significantly affected the nitrate removal efficiency (P < 0.05). In solid-phase denitrification process, electron donor for denitrification could be obtained by biological degradation of biodegradable polymer. Therefore, the influent CODCᵣ concentration has no major effect on nitrate removal efficiency compared with that of HRT and influent NO₃ ⁻-N concentration.
To reduce energy use for space heating, the optimization of operation of heating system has always been a key issue in north China. In this study, on the basis of field survey results, one existing ...regulation mode of supply water temperature and its effects on indoor environment and energy use were analyzed. Then the simulation-based optimization method of supply water temperature was pointed out by comparing the relationship among outdoor temperature, indoor temperature, room base temperature and supply water temperature. The optimization effects were presented by comparing room indoor temperatures and energy consumption before and after optimization. As a result, the simulation-based method proposed in this study was proved to be an effective way to optimize the operation of heating system, by which “excessive heating” can be significantly decreased, and average daily indoor temperature can basically be kept at its set point.
The possibility of using vibroacoustic signals for monitoring the efficiency of discharge pulses during electrical discharge machining is examined. Data on the effect of the variable dynamic ...characteristics of billets and background noise for electrical discharge machining in different frequency ranges on the parameters of vibroacoustic signals are presented.
Ice storage system can be used to shift electrical load from on-peak hours to off-peak hours, which can bring mutual benefits to power supplier and consumers. But if it does not operate properly the ...economic benefit will not be achieved. There is an ice storage system with flake ice maker that have been installed in Donghua University. In this paper, the characteristics of phase-change heat transfer of flake ice maker is studied. According to the different temperature of water washing the plate of evaporator and air conditioning load characteristic, the operation parameters are optimized. The optimized operation strategy of this ice storage system is presented according to its heat transfer characteristic.
This paper adopts GIS to conduct in-depth research and analysis on the planning and optimal operation of power distribution networks. Based on WebGL client-side development programming technology, ...the system platform designs and implements functional modules for 3D scene roaming and 2D map linkage to facilitate the precise presentation of specific locations in the roaming route for users. In this paper, we propose an iterative method of cluster dynamic division and net source storage planning considering source load uncertainty. In the iterative method, the net source storage planning is divided into the out-of-cluster network planning and the in-cluster net source storage planning steps. And the box uncertainty set is used to describe the uncertainty of PV, wind, and load in cluster division and planning respectively. The proposed planning model is applied to the modified IEEE 33 node case, and the economics and flexibility of the case with different combinations of dispatching strategies and planning schemes are compared to verify the dual advantages of the hybrid AC-DC distribution network structure in terms of economics and flexibility in accepting DG power and EV load. The effectiveness of the iterative method of cluster dynamic division and network source storage planning for new distribution zones is verified using arithmetic examples, and the economic efficiency of the robust optimization model accounting for uncertainty is compared with that of the deterministic optimization model, as well as the impact of uncertainty on the economic efficiency of the planning scheme.
Passenger flow and the growth period of passenger flow of the intercity railway will change with time, so it is necessary to evaluate and optimize the existing operation plan based on the actual ...passenger flow on a regular or irregular basis. The thesis proposes the definition and calculation method of passenger flow deviation coefficient, which is used to evaluate the matching degree between the operation plan and the actual passenger flow. On this basis, the thesis established an optimization model for intercity railway operation plan by minimizing passenger travel time and minimizing enterprise operating costs, and designs a specific genetic algorithm to solve the model. Finally, an example of an intercity railway line is used to verify the effectiveness of the model and algorithm. The research results of the thesis can provide a basis for the periodic evaluation and optimization of the development plan of the intercity railway in the growth period of passenger flow in China.
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