A Decision Method of Cogeneration Operation Schedule by Combining Use of SOFCs and PEFCs

In this paper, the authors propose a cogeneration system by combining two kinds of FCs （fuel cells） for a collective housing. The good points which each FC has are applied to the cogeneration operation schedule. In this study, some rooms interchange electric power and heat with each other for high efficiency and reduction of energy loss. The authors determine an operation schedule of FCs by multi-evaluation from viewpoints of energy cost and CO2 emissions.

Investigation on occupant presence and appliance operation schedules for university campus in south China sub-tropical area

Building occupant presence during varying periods is crucial to the performance studies of buildings and city regions.However,the understanding of the building occupancies on the university campus remains limited.To address this gap,our study employs field measurements,payment records,course arrangements,and building access systems to depict the occupancy patterns of the canteen,dormitory,library,and teaching and lab buildings during weekdays and weekends.We found that the occupancy rates across different buildings are somehow interrelated,given that the total number of occupants on campus is generally constant.Notably,dormitory occupancy rates tend to be low during the morning and afternoon course hours,which inversely correlates with the high occupancy rates in the teaching and lab buildings during these periods.Similarly,canteens experience surges in occupancy during meal times,which coincide with a decrease in library usage.Moreover,we established appliance operation schedules for dormitories through surveys and on-site investigations.Water dispensers and electronic devices were identified as the primary energy consumers for both male and female occupants,with desk-top fans and hairdryers being significant energy users for male and female occupants,respectively.These findings are essential for energy studies within a campus setting,underlining the importance of considering occupant behaviors on a regional scale.

A novel two-stage Lagrangian decomposition approach for refinery production scheduling with operational transitions in mode switching

To address large scale industrial processes,a novel Lagrangian scheme is proposed to decompose a refinery scheduling problem with operational transitions in mode switching into a production subproblem and a blending and delivery subproblem.To accelerate the convergence of Lagrange multipliers,some auxiliary constraints are added in the blending and delivery subproblem.A speed-up scheme is presented to increase the efficiency for solving the production subproblem.An initialization scheme of Lagrange multipliers and a heuristic algorithm to find feasible solutions are designed.Computational results on three cases with different lengths of time horizons and different numbers of orders show that the proposed Lagrangian scheme is effective and efficient.

Continuous query scheduler based on operators clustering

Data stream management system (DSMS) provides convenient solutions to the problem of processing continuous queries on data streams.Previous approaches for scheduling these queries and their operators assume that each operator runs in separate thread or all operators combine in one query plan and run in a single thread.Both approaches suffer from severe drawbacks concerning the thread overhead and the stalls due to expensive operators.To overcome these drawbacks,a novel approach called clustered operators scheduling (COS) is proposed that adaptively clusters operators of the query plan into a number of groups based on their selectivity and computing cost using S-mean clustering.Experimental evaluation is provided to demonstrate the potential benefits of COS scheduling over the other scheduling strategies.COS can provide adaptive,flexible,reliable,scalable and robust design for continuous query processor.

Evaluating Model and BeiDou Based Management System for Scale Operation of Cotton-Pickers

For scale cotton-picker operation, combination of production resources including field, machine, and drivers, should be organized reasonably both in temporal and spatial dimensions. Xinjian Agri. is such a scale cotton picking service company, which owns more than 400 cotton-pickers, hires nearly 1000 personnel, and works for more than ten big farms each season. The total operation area is about 90,000 ha. In this paper, a Cotton-picker Operation Scheduling & Monitoring System (CPOSMS) was developed for Xinjian Agri. CPOSMS is a WebGIS and BeiDou based management software, which includes four main function modules. Overall scheduling module aims to help the company to create machine fleets for the farms based on operation demands and operation capacity. A real-time evaluation model was studied to adjust the rationality. Local scheduling module is to dispatch machines and personnel to form machine unit. Central navigating module is to guide staff to specific field. Operation monitoring module is to monitor and analyze operation process. Experiments in 2015 showed that the CPOSMS is the necessary tool for the company, and the evaluation model and BeiDou based system can improve management efficiency.

Novel operating theatre scheduling method based on estimation of distribution algorithm

In order to improve the efficiency of operating rooms,reduce the costs for hospitals and improve the level of service qualities, a scheduling method was developed based on an estimation of distribution algorithm（ EDA）. First, a scheduling problem domain is described. Based on assignment constraints and resource capacity constraints, the mathematical programming models are set up with an objective function to minimize the system makespan. On the basis of the descriptions mentioned above, a solution policy of generating feasible scheduling solutions is established. Combined with the specific constraints of operating theatres, the EDA-based algorithm is put forward to solve scheduling problems. Finally, simulation experiments are designed to evaluate the scheduling method. The orthogonal table is chosen to determine the parameters in the proposed method. Then the genetic algorithm and the particle swarm optimization algorithm are chosen for comparison with the EDA-based algorithm, and the results indicate that the proposed method can decrease the makespan of the surgical system regardless of the size of operations. Moreover, the computation time of the EDA-based algorithm is only approximately 5 s when solving the large scale problems, which means that the proposed algorithm is suitable for carrying out an on-line scheduling optimization of the patients.

Effect of thermal storage performance of concrete radiant cooling room on indoor temperature

A building model with radiant cooling system was established and the cooling load, indoor temperature, surface temperature of the wails and other parameters in non-cooling and radiant cooling room were calculated by TRNSYS. The comparative analysis of the characteristics of attenuation and delay proves that the operation of radiant cooling system increases the degree of temperature attenuation of the room and reduces the inner surface temperature of the wall significantly, but has little effect on the attenuation coefficient and delay time of wall heat transfer. The simulation results also show that the inner surface temperature of the walls in the radiant cooling room is much lower than that in non-cooling room in the day with the maximum cooling load, which reduces the indoor operation temperature largely, and improves the thermal comfort. Finally, according to the analysis of indoor temperature of the rooms with different operation schedules of cooling system, it can be derived that the indoor mean temperature changes with the working time of radiant cooling system, and the operation schedule can be adjusted in practice according to the actual indoor temperature to achieve the integration of energy efficiency and thermal comfort.

Uncertain optimal model and solving method to platform scheduling problem in battlefield

The platform scheduling problem in battlefield is one of the important problems in military operational research.It needs to minimize mission completing time and meanwhile maximize the mission completing accuracy with a limited number of platforms.Though the traditional certain models obtain some good results,uncertain model is still needed to be introduced since the battlefield environment is complex and unstable.An uncertain model is prposed for the platform scheduling problem.Related parameters in this model are set to be fuzzy or stochastic.Due to the inherent disadvantage of the solving methods for traditional models,a new method is proposed to solve the uncertain model.Finally,the practicability and availability of the proposed method are demonstrated with a case of joint campaign.

Operations Scheduling for Rail Mounted Gantry Cranes in a Container Terminal Yard

Arranging the retrieving sequence and making the operational plans for gantry cranes to enhance port efficiency have become vital issues for the container terminals. In this paper, the problem of retrieving containers from a yard in a given sequence is discussed as an important part of the ship-loading process. This problem is divided into three categories according to its optimization complexity, i.e., the retrieval problem of a crane with a single spreader(ACSS), the retrieval problem of a crane with multiple spreaders(ACMS), and the retrieval problem of multiple cranes with a single spreader(MCSS). Firstly, heuristic algorithms are proposed to develop a retrieving sequence for ACSS to reduce the operational time. Then, optimizing the assignment to multiple spreaders is conducted by exchanging the movements of the obtained retrieving sequence. Finally, the movements are further assigned to two cranes and integrated with the MCSS retrieval problem mentioned above.The numerical experiments show the effectiveness and practicability of the heuristic algorithms.

Inverse Proportion Technique Based Scheduling Strategy for Energy Storage System Considering Load Demand Differences

The energy storage system(ESS)as a demand-side management(DSM)resource can effectively smooth the load power fluctuation of a power system.However,designing a more reasonable ESS operational strategy will be a prerequisite before incorporating the energy storage device into DSM.As different load levels have different demands for the real-time chargedischarge power of an ESS,this paper proposes a heuristic ESS operation scheduling strategy which can take into account the electrical load demand differences.In this paper,firstly,two demand degree concepts for charging power and discharging power are defined to describe the differentiated ESS demand under the condition of different electrical load levels.Secondly,an inverse proportion technique based ESS scheduling strategy,with the consideration of the load demand difference,is proposed in this paper.Thirdly,some evaluating indices are defined in this paper for describing the influence of the proposed strategy on the smoothing degree of the daily load curve.Finally,several case studies are designed to verify the validity and correctness of the proposed technique,and the results show that the proposed technique can effectively smooth the load curve and improve the ability of peak shaving and valley filling.