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•Simulation of energy system of the separation process in ethylene plant and model validation•Exergy analysis and diagnosis of the energy system of the separation process in ethylene ...plant•Dephlegmator No.1 has the highest exergy destruction•Avoidable/unavoidable exergy destructions of different units in separation process calculated•Multi-objective optimization performed to balance exergy efficiency and operational cost
In chemical industry, most processes face the challenge of high energy consumption. The approach presented in this study can reduce the energy footprint and increase efficiency. The energy system of a separation process in ethylene manufacturing is used to demonstrate the effectiveness of the approach. The chilling train system of the separation process in a typical ethylene plant consumes most cooling and provides appropriate feed for distillation columns. The steady state simulation of system was presented and the simulation results were proved accurate. The conventional exergy analysis identifies that Dephlegmator No.1 (a heat exchange and mass transfer device) has the highest exergy destruction (1401.28kW). Based on advanced exergy analysis, Dephlegmator No.1 has the highest rate of avoidable exergy destruction (89.04 %). Finally, a multi-objective optimisation aiming to maximise system exergy efficiency and to minimise operational cost was performed and the Pareto frontier was obtained. The multi-objective optimized exergy efficiency is 79.53 % (improved by 0.61 %) and the operational cost is 0.02031 yuan/kg (saved by 11.19 %). This study will guide future research to reduce energy consumption in process manufacturing.
The high‐order nonlinear complex characteristics of traditional static wake model (SWM) restrict the fast optimization of wake effect. Therefore, this paper introduces a dynamic wake model (DWM) to ...describe the time‐varying wake characteristics of wind turbines (WTs) with low computational cost. The traditional SWM is linearized to derive the wake wind speed sensitivity coefficients, which represents the sensitivity of wake wind speed deficit with respect to the active power reference. Considering the natural propagation characteristics of wake effect, a wake delay function is added to realize the future wind speed prediction of different locations of the wind farm. And a joint control strategy of wake and active power based on model predictive control (MPC) is proposed to optimize the power contribution of each WT to minimize wake effects, and maximize total available power. Thus, the increased available power is able to satisfy the power demand from Transmission System Operator (TSO) for ancillary services and enhance power support capability. The control performance of the proposed control strategy is evaluated by simulations under constant and varying incoming wind speed.
A dynamic wake model is proposed to describe the time‐varying wake characteristic and reduce computational complexity. And an MPC‐based control scheme is used to achieve maximum available power of wind farm by reducing the wind speed deficit caused by wake effect. The increased available power is able to satisfy the power demand from Transmission System Operator for ancillary services and enhance power support capability.
Wind power prediction holds significant value for the stability of the electrical grid when wind power is connected to the grid. Using neural networks for wind power prediction may have some ...limitations, such as slow speed and low accuracy. This paper proposes to enhance the power prediction accuracy and speed by optimizing the neural network through health assessment wind turbines. Firstly, based on wind turbine actual operating data, a health assessment is conducted to obtain a health matrix of wind turbine. Then, by calculating the weights of the matrix, the power prediction strategy of the network is optimized. Following that, matrix approximation hyperparameters are utilized to expedite the optimization process. Finally, some tests are conducted on neural network power prediction, act as optimized back propagation (BP) neural network and whale swarm algorithm–support vector regression (WSA-SVR) neural networks are employed for wind power prediction. Results show noticeable optimization: after optimizing the BP network, power prediction accuracy increased by about 40%, and prediction speed rose by about 20%; after optimizing the WSA-SVR network, power prediction accuracy improved by 10%, and prediction speed surged by about 45%. Further analysis shows that this method can improve the accuracy and speed of most neural network wind power prediction algorithms.
Abstract
Red Mud(RM), a kind of hazardous solid wastes produced during the process of alumina production, is disadvantageous for our environments owning to its characters of strong alkali and rich ...salt. It is essential to conduct innocent treatment. Summarizing the hazards of RM and methods of its comprehensive utilization, A reference for the deeper comprehensive utilization of RM in the future in this review was provided.
Transient stability assessment (TSA) plays a pivotal role in guiding power grid risk control strategies. However, it faces challenges when dealing with complex multi-graph inputs generated by ...pre-fault, fault occurrence, and post-fault states. Meanwhile, most previous research studies neglected the assessment of the transient stability level. To address this, we propose a multi-task transient stability assessment (MTTSA) approach. In MTTSA, we introduce a multi-graph sample and aggregate-attention network (GraphSAGE-A) designed to capture stability features even amidst topology changes. A multi-head attention mechanism and local normalization method are adopted for a better extraction of the global and contextual information. Additionally, we introduce a quantified transient stability risk index considering the transient stability boundary and incorporate a multi-task dense structure to enhance MTTSA’s performance. Empirical tests, under changing operating conditions, conducted on the IEEE 39-bus system showcase a significant performance improvement with the proposed MTTSA method.
Land is not only a basic factor of production and an important space carrier, but also a key tool to control the development of urban economy. While the phenomenon of land participation in regulation ...exists generally in China, the theory of supporting regulation and the effect of regulation are still unclear. In the study, we intend to analyse the relationship between location of construction land supply and regional economic growth. By constructing indexes of construction land supply structure and a theoretical model based on the Solow model, we explore the relationship between the location of construction land supply and economic growth in the Tianjin Binhai New Area (TBNA). We find that the location of construction land supply significantly impacts economic growth. The circle-layers dimension has a hop about the influence of construction land supply on economic growth. The orientation dimension has superiority in some regions, especially the southwest and northwest. To realise sustainable urban development, construction land supply should focus on the lag and location difference of its economic driving effect and actively promote the redevelopment of stock construction land not only in the TBNA but also other rapidly developing cities.
The energy system of industrial process, particularly in the petrochemical industry, consumes most of the utility cost. In this paper, a superstructure of a large-scale industrial ethylene plant ...energy system including fuel, steam, electricity and water was studied. In this system, multitype energy is transferred by water, as the working medium, which makes it feasible for the multitype energy to be synthesized according to the heating, cooling, and phase changes of water. The unit models were developed by hybrid modeling method combining thermodynamics and least-square method (LSM). The seasonal energy system optimization based on typical day method was formulated as an mixed-integer nonlinear programming (MINLP) problem. Then, an efficient decomposition-based model solving strategy was proposed for solving this difficult problem, in which the fuel, steam, electricity, and water consumption were simultaneously optimized. The optimal operational solution was obtained by the following strategies: (1) regulating the steam flow rate in letdown valves, the condensing steam flow rate extracted from turbines, and selections of power sources for low demand mechanical users synergistically; (2) determining the cooling water temperature to balance the turbine efficiency and the electricity and water consumption; and (3) employing different numbers of cooling towers according to the seasons. The flow rate-related decisions are sensitive to uncertainty in the measurement, while the temperature-related and pressure-related ones are relatively more stable. The results showed that the total energy consumption was reduced by 14.42% in spring–autumn and 13.92% in summer, which were 1.44 and 0.89% better than these using the two-type energy optimization method in literature, respectively. Further energy structure analysis exhibiting consumption proportion of different types of energy showed that part of the fuel consumption was replaced by cheaper steam and electricity to reduce total energy cost. Finally, energy management strategies were formed on the basis of the above results.
Because wind direction has the trait of time varying, yaw is a common state of wind turbine (WT). To improve the energy capture and reduce the yaw actuator usage time, a Model Predictive Control ...(MPC) method based on the Fuzzy Deduction Weight Coefficient Evaluator (FDWE) is proposed. Specifically, in view of the two contradictory control objectives of energy capture loss ratio and yaw actuator usage ratio in MPC, FDWE is designed to dynamically adjusts the weight coefficient connecting the two objectives according to the predicted wind direction. On this basis, to fully exert the advantage of FDWE, the fuzzy rule and membership function (MF) are tried to be simultaneously optimized. For this complex optimization problem involving different types of multiple design variables, three different solving strategies are proposed: fuzzy rule-MF ordered optimization, mixed integer optimization, and association optimization. Finally, an improved Adaptive Grid Algorithm Multi-Objective Particle Swarm Optimization is presented to solve the formulated optimization problems. The results indicate that the optimized FDWE-MPC using the three strategies not only improves the energy capture of the WT, but also reduces the use of yaw actuator compared to the baseline MPC. Consequently, the proposed method is promising in reducing the production cost for the WTs.
•There is a substitution relationship between regulatory and payment tools in agricultural land preservation of China.•A theoretical framework from the perspective of nonmarket value is established ...to evaluate policy tools.•We empirically verify that payment tools can partly substitute for regulatory tools.•The payment-regulation substitution may provide inspiration for policy innovation.
As policies of agricultural land preservation, regulatory tools and payment ones usually operate independently or complementarily. However, under the policy of the dynamic balance of total cultivated land and taxes/fees of agricultural land conversion in China, there is a substitution relationship between the regulatory and payment tools. This article reviews this substitution mechanism, theoretically evaluates the policy system of Chinese agricultural land preservation from the perspective of nonmarket value and then estimates the public preference for those policy tools and agricultural land types using the choice experiment method. The results show that first, the effects of the regulatory and payment tools are different. While the regulatory tools preserve current agricultural land, the payment ones tend to improve cultivated land for the function of food security. Second, in the choice experiment, respondents support the hybrid tools combing the regulatory and payment tools, regulatory ones and payment ones from high to low, which means that the substitution relationship is reasonable to some extent. These suggest that the interaction of policies needs to be identified in the policy system of agricultural land preservation, and the theory of nonmarket value and choice experiment can be effectively used to evaluate the policy and provide references for the improvement of the policy system.
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