Statistical modeling and optimal energy distribution of cogeneration units by genetic algorithms

Our main objective is to evaluate the performance of a new method to optimize the energy management of a production system composed of six cogeneration units using artificial intelligence. The optimization criterion is economic and environmental in order to minimize the total fuel cost, as well as the reduction of polluting gas emissions such as COx, NOx and SOx. First, a statistical model has been developed to determine the power that the cogeneration units can provide. Then, an economic model of operation was developed: fuel consumption and pollutant gas emissions as a function of the power produced. Finally, we studied the energy optimization of the system using genetic algorithms (GA), and contribute to the research on improving the efficiency of the studied power system. The GA has a better optimization performance, it can easily choose satisfactory solutions according to the optimization objectives, and compensate for these defects using its own characteristics. These characteristics make GA have outstanding advantages in iterative optimization. The robustness of the proposed algorithm is validated by testing six cogeneration units, and the obtained simulation results of the proposed system prove the value and effectiveness of GA for efficiency improvement as well as operating cost minimization.

Dynamic Optimization of Bus Line Schedule in Commuter Corridor Based on Bus IC Card Data

The aim of this study was to explore the bus operating state of the city bus passenger corridor, taking the minimum bus operating cost and passenger travel cost as the objective function, taking passenger flow demand and operating income as the constraint, and considering the average speed change of the bus line in the bus corridor at different times. This paper proposes a dynamic optimization model of bus route schedule based on bus Integrated Circuit Card (IC Card) data. The optimization variable is the departure frequency of the candidate lines. To solve the model, a dynamic departure interval optimization method based on improved Genetic Algorithm (GA) was designed under different decision preferences. The method includes the calibration of generalized cost functions for passengers and bus companies and grasps the characteristics of bus operating speed changes and the design of departure strategies under different decision preferences. The validity and applicability of the proposed method are verified by a numerical example. We mainly carried out the following work: (1) Dynamic analysis of the time dimension of the bus departure interval takes into account the changes in passenger time characteristics during peak periods. (2) Seven schemes of weight ratio of passenger waiting time cost and bus operation cost were designed, and the departure intervals with different benefit orientations of passengers and operators were discussed, respectively, so as to select the corresponding departure schemes for decision makers under different decision preferences. The results show that (1) the total cost of the 7 different weighting schemes is lower than the actual value by 6.90% to 18.20%; (2) when decision makers need to bias the weight to the bus company, the weight ratio α : β between passengers and bus company is 0.25 : 0.75 which works best. The frequency of departures has been reduced by 6, and at the same time, the total optimized cost is reduced by 18.2%; (3) when decision makers need to bias the weight to the passengers, the weight ratio α : β between the passengers and bus company is 0.75 : 0.25 which works best. The frequency of departures has been increased by 19, and at the same time, the total optimized cost is reduced by 17.7%; and (4) when decision makers consider passengers and bus companies equally, the weight ratio α : β between passengers and bus companies is 0.5 : 0.5, the optimization cost is the closest to the actual cost, the optimization cost is reduced by 6.9%, and the frequency of departures has been increased by 5. The results show that the model in this paper provides a new idea for the information mining of bus routes in the research based on the bus IC Card data and provides an effective tool for the management of different operation decision preferences.

Resource management framework using simulation modeling and multi-objective optimization: a case study of a front-end department of a public hospital in Thailand

Background The overcrowded patients, which cause the long waiting time in public hospitals, become significant problems that affect patient satisfaction toward the hospital. Particularly, the bottleneck usually happens at front-end departments (e.g., the triage and medical record department) as every patient is firstly required to visit these departments. The problem is mainly caused by ineffective resource management. In order to support decision making in the resource management at front-end departments, this paper proposes a framework using simulation and multi-objective optimization techniques considering both operating cost and patient satisfaction. Methods To develop the framework, first, the timestamp of patient arrival time at each station was collected at the triage and medical record department of Thammasat University Hospital in Thailand. A patient satisfaction assessment method was used to convert the time spend into a satisfaction score. Then, the simulation model was built from the current situation of the hospital and was applied scenario analyses for the model improvement. The models were verified and validated. The weighted max–min for fuzzy multi-objective optimization was done by minimizing the operating cost and maximizing the patient satisfaction score. The operating costs and patient satisfaction scores from various scenarios were statistically compared. Finally, a decision-making guideline was proposed to support suitable resource management at the front-end departments of the hospital. Result The three scenarios of the simulation model were built (i.e., a real situation, a one-stop service, and partially shared resources) and ensured to be verified and valid. The optimized results were compared and grouped into three situations which are (1) remain the same satisfaction score but decrease the cost (cost decreased by 2.8%) (2) remain the same satisfaction score but increase the cost (cost increased up to 80%) and (3) decrease the satisfaction score and decrease the cost (satisfaction decreased up to 82% and cost decreased up to 59%). According to the guideline, the situations 1 and 3 were recommended to use in the improvement and the situation 2 was rejected. Conclusion This research demonstrates the resource management framework for the front-end department of the hospital. The experimental results imply that the framework can be used to support the decision making in resource management and used to reduce the risk of applying a non-improvement model in a real situation.

Sales Volume, Operating Cost and its Effect on Profitability (Study on Listed Companies in The Indonesia Stock Exchange (IDX) for 2017-2020)

This study is associative research that uses more than one independent variable to determine the relationship between the variables studied, namely sales volume, operating costs, and profitability. The data used are in the form of company profit and loss financial statements, which were obtained from the Indonesian stock exchange website www.IDX.co.id. The population used is the annual financial statements published for 4 periods 2017-2020 as many as 16 companies. The sample in this study is in the form of annual financial statements (profit and loss statements) for the 2017-2020 period as many as 10 companies (40 samples) according to the sampling criteria. The results obtained, Sales Volume and Operational Costs affect Profitability as evidenced by the results of Fount 6.827 > Fable of 3.250 with a significant level of 0.003. While partially Sales Volume affects Profitability as evidenced by the results of count of 2,980 and table of 2,026 with a significant value of 0.005, and also Operational Costs affect Profitability as evidenced by a count of -3.599 and table of 2.026 with a significance value of 0.001

Economic Analysis of Atomization Drying of Concentrated Solution Based on Zero Discharge of Desulphurization Wastewater

With the improvement of environmental protection requirements, more and more attention has been given to desulphurization wastewater with zero discharge in coal power plants. Atomization drying is part of the main zero discharge technologies at present. Economic analysis of the atomization drying of desulphurization wastewater is beneficial to the formulation of an appropriate operation scheme and to the reduction of operation costs. The economic analysis and sensitivity analysis of different operating conditions such as unit load, the handling capacity of concentrates, and the temperature of the extracted flue gas in the atomization drying process of concentrated desulfurized wastewater were carried out in this paper. The main cost of the drying process came from the influence of flue gas extraction on the overall heat transfer in the boiler, resulting in the decrease in power generation revenue, which can reach more than 80%. The operating cost of auxiliary machinery was relatively low. The cost of treatment for per ton of concentrates increased first and then decreased with the increase in temperature of the extracted flue gas, and it decreased with the increase in the handling capacity of the concentrates. The effect of a unit load on the treatment cost was also related to the temperature of the extracted flue gas, and the optimal flue gas temperature increase to higher temperatures as the unit load decreased. The minimum treatment costs per ton of concentrate ranged from CNY 143.54/t to CNY 158.77/t under different unit loads. Sensitivity analysis showed that the temperature of the extracted flue gas had the greatest impact on treatment cost, and its sensitivity coefficient was 0.0834. The ways in which to improve economic benefits were discussed.

Research on Route Deviation Transit Operation Scheduling—A Case Study in Suburb No. 5 Road of Harbin

Route deviation transit is a flexible “door-to-door” service method that combines the efficiency of conventional public transport modes and the flexibility of demand response modes, meeting the travel needs of people with low travel density and special groups. In this paper, the minimum value of the sum of vehicle operating cost and passenger travel cost was the optimal goal, and the RDT multi-vehicle operation scheduling model was constructed. Taking the available relaxation time as the control parameter of the RDT system and considering the insertion process of the random travel demand of the passengers during the operation process, we used a heuristic search algorithm to solve the scheduling model. This paper took Suburb No. 5 Road of Harbin as an example, using MATLAB to simulate the RDT operation scheduling model to verify the stability and feasibility of the RDT system under different demands. The results showed that under different demand conditions, the system indicators such as passenger travel time, waiting time, and vehicle mileage in the RDT system fluctuated very little, and the system performance was relatively stable. Under the same demand conditions, the per capita cost of the RDT system was 5.9% to 10.8% less than that of the conventional bus system. When the demand ρ is 20~40 person/hour, the RDT system is more effective than the conventional bus for the 5 bus in the suburbs of Harbin.

Growth and yield assessment of lettuce (Lactuca sativa L.): an economic feasibility and performance evaluation of capillary wick irrigation system

The study assessed the growth and yield of lettuce (Lactuca sativa L.) in order to evaluate the performance and economic feasibility of capillary wick irrigation system. Unlike any other capillary rise-based systems that uses the matric potential of the soil to dictate the amount of water to be drawn, this system aimed to continuously supply water imitating a full-time drip irrigation system but cheaper in terms of materials and operating cost. A 5 mm-width, cotton fabric strip was used as a wick material based from the results of the preliminary testing to verify several literature claims. In order to determine number of wicks to optimally supply the water demand of lettuce, treatments namely, T1= 1 wick, T2 = 2 wicks, T3 = 3 wicks and a control treatment T4 which uses manual irrigation method, were tested and compared against each other. Significant results were in terms of the volume of water applied, and the water use efficiency in which T1 showed a better performance among other treatments. However, it does not imply that T1 had produced a supreme yield output. Instead, this can be attributed to the efficient application of irrigation water to an optimal level. This means that T1 or the use of 1 wick material minimizes irrigation water losses through evaporation and percolation. An economic analysis was performed and has resulted to a return on investment of 41.92% or 41.92% of the investment cost will be returned after three cropping, which is an attribute of the particular set-up cost of the study.

A Hybrid GWO-PSO technique for the solution of Reactive Power Planning Problem

Over the years the optimization in various areas of power system has immensely attracted the attention of power engineers and researchers. RPP problem is one of such areas. This is done by the placement of reactive power sources in the weak buses and thereafter minimizing the operating cost of the system which is directly dependent on the system transmission loss. The work proposed in this article utilizes FVSI method to detect the weak bus. GWO-PSO is proposed in the current work for providing optimal solution to RPP problem. To test the efficacy of the proposed technique, comparative analysis is then performed among the variants of PSO and hybrid GWO-PSO. The optimal solution rendered by the proposed method is compared with other heuristic algorithms. The proposed method of GWO-PSO generates a reduction of 4.25% in operating cost for IEEE 30 bus and 5.99% for New England 39 bus system. The comparison thus yields that the GWO-PSO hybrid method is superior in generating optimality, diversity and is efficient to generate solution strategies for RPP even in a practical power network.

Operation and Control of Microgrid

The demand for electricity is increasing day by day due to technological advancements. According to the demand, the size of the grid is also increasing rapidly in the past decade. However, the traditional centralized power grid has many drawbacks such as high operating cost, customer satisfaction, less reliability, and security. Distribution generation has less pollution, high energy efficiency, and flexible installation than traditional generation. It also improves the performance of the grid in peak load and reliability of supply. The concept of micro-grid has been raised due to the advent of new technologies and development of the power electronics and modern control theory. Micro-grid is the significant part of the distribution network in the future of smart grid, which has advanced and flexible operation and control pattern, and integrates distributed clean energy.