中国电力中长期市场分时段交易价格形成机制及模型

电力中长期市场分时段交易是中国电力市场改革的重要举措之一。针对当前电力中长期市场分时段交易价格形成机制不合理、不完善的问题,提出了中国电力中长期市场分时段交易价格形成机制及其模型。首先,分析影响中国电力中长期分时段交易价格形成的因素,提出电力中长期交易的4种典型场景;然后,综合考虑生产成本和用户效用,探索性地提出适用于中长期分时段交易的系统平均成本定价、用户失负荷价值定价、系统边际成本定价和发电企业失负荷价值定价4种成本定价机制,构建了基于成本定价的分时段交易定价模型;最后,以某省实际数据为例进行测算,验证了模型的有效性。     

Formation Theory and Printability of Photocurable Hydrogel for 3D Bioprinting

Bio-ink has gradually transited from ionic-crosslinking to photocrosslinking due to photocurable bio-hydrogel having good formability and biocompatibility. It is very important to understand and quantify the crosslinking process of photocurable hydrogels, otherwise, bioprinting cannot be standardized and scalable. However, there are few studies on hydrogel formation process and its photocrosslinking behavior which cannot be accurately predicted. Herein, the photoinitiated radical polymerized bio-hydrogels are taken as an example to establish the formation theory. Three typical crosslinking reactions are first distinguished. It is further proposed that not all double-bonds consumed during crosslinking contributeequally to polymerization. Then the concept of effective double-bond conversion (EDBC) is elicited. Deriving from EDBC, several important formation indices are defined. According to theory, it is predicted that slow crosslinking can improve the crosslinking degree. Furthermore, based on the slow crosslinking effect, a new strategy of projection-based 3D printing (PBP) is proposed, which significantly improved printing quality and efficiency. Overall, this work will fill the gap in hydrogel's formation theory, making it possible to accurately quantify the formation process.     

Hybrid Recommender System Using Systolic Tree for Pattern Mining

A recommender system is an approach performed by e-commerce for increasing smooth users’ experience. Sequential pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of transactions. This work will present the implementation of sequence pattern mining for recommender systems within the domain of e-commerce. This work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender system. The feature selection's objective is to pick a feature subset having the least feature similarity as well as highest relevancy with the target class. This will mitigate the feature vector's dimensionality by eliminating redundant, irrelevant, or noisy data. This work presents a new hybrid recommender system based on optimized feature selection and systolic tree. The features were extracted using Term Frequency-Inverse Document Frequency (TF-IDF), feature selection with the utilization of River Formation Dynamics (RFD), and the Particle Swarm Optimization (PSO) algorithm. The systolic tree is used for pattern mining, and based on this, the recommendations are given. The proposed methods were evaluated using the MovieLens dataset, and the experimental outcomes confirmed the efficiency of the techniques. It was observed that the RFD feature selection with systolic tree frequent pattern mining with collaborative filtering, the precision of 0.89 was achieved.     

Event-triggered-based finite-time cooperative path following control for underactuated multiple marine surface vehicles

This paper develops an event-triggered-based finite-time cooperative path following (CPF) control scheme for underactuated marine surface vehicles (MSVs) with model parameter uncertainties and unknown ocean disturbances. First, a finite-time extended state observer (FTESO) is proposed, in which the FTESO can estimate the velocities and compound disturbances in finite time. Then, the finite-time LOS guidance law based on velocity estimation values is designed to obtain the desired surge velocity and the desired yaw rate. In order to realize the cooperative control of multiple paths in finite time, the cooperative control law for the path variable is designed. In addition, the relative threshold event-triggered control (ETC) mechanism is incorporated into the formation control algorithm, and an event-triggered-based finite-time CPF controller is designed, which not only effectively reduces the update frequency of controller and the mechanical loss of actuator but also improves the control performance of system. Furthermore, by using homogeneous method, Lyapunov theory, and finite-time stability theory, it is proved that under the proposed finite-time CPF control scheme, the formation errors can converge to a small neighborhood around origin in finite time. Finally, numerical simulation results illustrate the effectiveness of the proposed control scheme.     

Adaptive prescribed time control for quadrotor formation with stochastic links failure

The formation control for multiple quadrotors subject to maintaining the formation configuration and collision avoidance in the situation of stochastic links failure is investigated in this paper. First, the distributed formation controller is designed, the position controller is developed to manage the desired formation of position, and the attitude controller is developed to control the translation and rotation movements of the quadrotor. Then, in order to avoid the collisions between multiple quadrotors and the obstacles, a potential energy function method is introduced into the quadrotor formation control combined with the nest adaptive control. Inspired by the design of event trigger controller, a communication compensation controller is designed to ensure the stability of quadrotor formation under the condition of random communication interruption and recovery. Moreover, a prescribed time function is designed, which means the convergence time of the formation system can be set in advance. The prescribed time stability of the formation control system is proved by Lyapunov theory. Finally, the simulation results verify the effectiveness and superiority of this method.     

Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm

We consider a joint decision model of cell formation and task scheduling in cellular manufacturing system under dual-resource constrained (DRC) setting. On one hand, machines and workers are multi-functional and/or multi-skilled, and they are grouped into workstations and cells. On the other hand, there is a processing sequence among operations of the parts which needs to be dispatched to the desirable workstations for processing. Inter-cell movements of parts can reduce the processing times and the makespan but will increase the inter-cell material handling costs. The objective of the problem is to minimise the material handling costs as well as the fixed and operating costs of machines and workers. Due to the NP-hardness of the problem, we propose an efficient discrete bacteria foraging algorithm (DBFA) with elaborately designed solution representation and bacteria evolution operators to solve the proposed problem. We tested our algorithm using randomly generated instances with different sizes and settings by comparing with the original bacteria foraging algorithm and a genetic algorithm. Our results show that the proposed DBFA has better performance than the two compared algorithms with the same running time.     

Cellular manufacturing system design considering machines reliability and parts alternative process routings

Cell formation is an important problem in the design of cellular manufacturing systems (CMS). Most cell formation methods appeared in the literature assume that each part has one process plan, and all machines are 100% reliable with unlimited capacity. However, this is not realistic in manufacturing systems. Considering machines reliability in addition to machines capacity and machine duplicates during the part route selection process help to obtain better machine grouping and minimum total cost for CMS. Considering these factors in addition to operations sequence and production volumes makes the problem more complex but more realistic. Most of the methods appeared in the literature to solve such problems use mathematical programming procedures that take large amount of computational efforts. Procedures using similarity coefficient method are more flexible in incorporating various important production data and lend easily to computer applications. A new similarity coefficient equation that incorporates all these production factors is developed. Also, a procedure that captures the similarity between machine groups and minimises the total CMS cost is developed. The procedure utilises functional cells to eliminate intercellular moves and achieve ‘one-piece flow’ practise. The methodology is compared with other methods in the literature and found to be more effective.     

High throughput research and evaporation rate modeling for solvent screening for ethylcellulose barrier membranes in pharmaceutical applications

Context: Ethylcellulose is commonly dissolved in a solvent or formed into an aqueous dispersion and sprayed onto various dosage forms to form a barrier membrane to provide controlled release in pharmaceutical formulations. Due to the variety of solvents utilized in the pharmaceutical industry and the importance solvent can play on film formation and film strength it is critical to understand how solvent can influence these parameters.

Objective: To systematically study a variety of solvent blends and how these solvent blends influence ethylcellulose film formation, physical and mechanical film properties and solution properties such as clarity and viscosity.

Materials and methods: Using high throughput capabilities and evaporation rate modeling, thirty-one different solvent blends composed of ethanol, isopropanol, acetone, methanol, and/or water were formulated, analyzed for viscosity and clarity, and narrowed down to four solvent blends. Brookfield viscosity, film casting, mechanical film testing and water permeation were also completed.

Results and discussion: High throughput analysis identified isopropanol/water, ethanol, ethanol/water and methanol/acetone/water as solvent blends with unique clarity and viscosity values. Evaporation rate modeling further rank ordered these candidates from excellent to poor interaction with ethylcellulose. Isopropanol/water was identified as the most suitable solvent blend for ethylcellulose due to azeotrope formation during evaporation, which resulted in a solvent-rich phase allowing the ethylcellulose polymer chains to remain maximally extended during film formation. Consequently, the highest clarity and most ductile films were formed.

Conclusion: Employing high throughput capabilities paired with evaporation rate modeling allowed strong predictions between solvent interaction with ethylcellulose and mechanical film properties.     

不同形貌Ti-O基纳米结构的可控制备与形成机制探讨

利用碱辅助水热法实现了Ti-O基纳米管、纳米带和纳米结构微球的合成,通过TEM、SEM等手段对所制备的纳米结构进行表征。当采用商品级锐钛矿TiO2为原料,热水处理温度为180℃、碱的浓度为10mol/L,热处理48h时可以得到Ti-O基纳米带。纳米带宽度为50~200nm,长度达到几十微米甚至一百多微米;产物产率高,质量好,结晶良好,表面洁净,无缺陷。当热处理温度为120℃时,可以得到Ti-O基纳米管,纳米管的长度为200~500nm,外径在20~50nm之间。当所用前驱体的粒径较小时,容易形成较细或者较窄的纳米带或者纳米线,当在选用前驱体的粒径较大时,可以生成纳米结构微球。     

面向等离子体材料钨中氘/氦滞留行为的研究进展

作为面向等离子体材料,钨(W)在服役的过程中不仅受到等离子体造成的高能热负荷的作用,还受到高束流粒子如氘(D)、氚(T)、氦(He)等的轰击和D-T聚变反应产生的高能中子的影响。W中D、T、He的滞留和起泡,仍是聚变堆装置中有待解决的关键问题之一。综述了D、T和He的滞留行为及其气泡形成与辐照条件之间的关系,简要评述了W的服役性能和强化机理。通过降低W中D/He滞留量、抑制气泡的形成可有效改善W的服役性能。深入研究D/He滞留行为与辐照缺陷之间的相互作用关系,进而构建D/He的宏观热脱附行为与其微观状态之间的对应关系,为寻找合适途径来改善W的服役性能提供理论支撑。