Impact of Time-of-Use Demand Response Program on Optimal Operation of Afghanistan Real Power System

Like most developing countries, Afghanistan still employs the traditional philosophy of supplying all its load demands whenever they happen. However, to have a reliable and cost-effective system, the new approach proposes to keep the variations of demand at the lowest possible level. The power system infrastructure requires massive capital investment; demand response (DR) is one of the economic options for running the system according to the new scheme. DR has become the intention of many researchers in developed countries. However, very limited works have investigated the employment of appropriate DR programs for developing nations, particularly considering renewable energy sources (RESs). In this paper, as two-stage programming, the effect of the time-of-use demand response (TOU-DR) program on optimal operation of Afghanistan real power system in the presence of RESs and pumped hydropower storage (PHS) system in the day-ahead power market is analyzed. Using the concept of price elasticity, first, an economic model indicating the behaviour of customers involved in TOU-DR program is developed. A genetic algorithm (GA) coded in MATLAB software is used accordingly to schedule energy and reserve so that the total operation cost of the system is minimized. Two simulation cases are considered to verify the effectiveness of the suggested scheme. The first stage programming approach leads case 2 with TOU-DR program to 35 MW (811 MW − 776 MW), $16,235 ($528,825 − $512,590), and 64 MW reductions in the peak load, customer bill and peak to valley distance, respectively compared to case 1 without TOU-DR program. Also, the simulation results for stage 2 show that by employing the TOU-DR program, the system’s total cost can be reduced from $317,880 to $302,750, which indicates a significant reduction in thermal units’ operation cost, import power tariffs and reserve cost.

REDUCING DIRECT LABOR COSTS THROUGH U-SHAPED CELLULAR LAYOUT IN INJECTED AUTOMOTIVE COMPONENTS INDUSTRY

Reducing direct labor costs can be used to create a low operation cost as the way for winning future markets including injected automotive components. This paper aims to provide an overview of direct labor costs reduction in injected automotive components through a U-shaped cellular layout as part of the lean concept. Over a decade, many types of research had already used the lean concept to solve problems in production activity through lean tools. In this paper, several lean tools such as Takt time, value stream mapping, and U-shaped cellular will be used for reducing direct labor costs that have increased yearly in Indonesia since 2015. Those lean tools will be performed in a job-shop of injected automotive components. After performing the U-shaped cellular layout, the direct labor costs were reduced to 25 % by combining the job held by two operators to become one operator.

Low-Carbon Operation of a Multi-Energy System with Hydrogen-Based Vehicle Applications

In order to cope with the challenges of improving energy efficiency, increasing the integration of renewable energy, and achieving carbon emission reduction, multi-energy systems have received more and more attention in recent years and have been developing rapidly. Traditionally, different energy infrastructures are usually scheduled and operated independently, which leads to inefficient use of energy and waste of resources. By integrating into a multi-energy system, different energy infrastructures can be coupled and optimized into one unit. In this article, from a low-carbon point of view, the optimal scheduling of a real multi-energy system with hydrogen-based vehicle applications is proposed. The simulation results show that the proposed optimal scheduling can help quantify the daily operation cost and carbon emissions and achieve considerably operation cost saving and carbon reduction by reasonably arranging and utilizing all the devices in the system.

Low-Carbon Operation of a Multi-Energy System with Hydrogen-Based Vehicle Applications

In order to cope with the challenges of improving energy efficiency, increasing the integration of renewable energy, and achieving carbon emission reduction, multi-energy systems have received more and more attention in recent years and have been developing rapidly. Traditionally, different energy infrastructures are usually scheduled and operated independently, which leads to inefficient use of energy and waste of resources. By integrating into a multi-energy system, different energy infrastructures can be coupled and optimized into one unit. In this article, from a low-carbon point of view, the optimal scheduling of a real multi-energy system with hydrogen-based vehicle applications is proposed. The simulation results show that the proposed optimal scheduling can help quantify the daily operation cost and carbon emissions and achieve considerably operation cost saving and carbon reduction by reasonably arranging and utilizing all the devices in the system.

Performance Improvement on Some Closed Loop Plastic Recycling Plants

This research focuses on pertinent parameters to improve the performance of four plastic recycling plants. The method used in this work is the overall equipment effectiveness (OEE) analysis. After assessing data collected and comparing calculated values with global accepted standards, there was need to optimize the OEE value of 74.40% for plant P48mold which was below the universally accepted value of 85% and for plant P72mold which is exactly 85%. Optimization toolbox is used to select values for cycle time ranging between 0.75min and 0.73min to improve the calculated value of 74.40% for plant P48mold and 85% for plant P72mold. Optimizing the OEE values significantly increases production by making the operation cost-effective. The OEE value was obtained by multiplying the three factors of availability rate, performance rate and quality rate and optimized values of 87% for P48 mould and 115% for P72 mould were obtained respectively. The cycle time was used to optimize the performance of both plants, which improved the OEE values. These values proved that change in cycle time can improve OEE. A Pareto principle 80/20 rule was also used to proactively check the effects of the planned and unplanned downtime. Keywords: Throughput, Efficiency, Overall Equipment Effectiveness, Cycle time. Cite the Article: Davids S. O., Sodiki J. I., and Isaac O. E. (2021) Performance Improvement on Some Closed Loop Plastic Recycling Plants. Journal of Newviews in Engineering and Technology (JNET),

A Scheduling Approach for the Combination Scheme and Train Timetable of a Heavy-Haul Railway

Heavy-haul railway transport is a critical mode of regional bulk cargo transport. It dramatically improves the freight transport capacity of railway lines by combining several unit trains into one combined train. In order to improve the efficiency of the heavy-haul transport system and reduce the transportation cost, a critical problem involves arranging the combination scheme in the combination station (CBS) and scheduling the train timetable along the trains’ journey. With this consideration, this paper establishes two integer programming models in stages involving the train service plan problem (TSPP) model and train timetabling problem (TTP) model. The TSPP model aims to obtain a train service plan according to the freight demands by minimizing the operation cost. Based on the train service plan, the TTP model is to simultaneously schedule the combination scheme and train timetable, considering the utilization optimal for the CBS. Then, an effective hybrid genetic algorithm (HGA) is designed to solve the model and obtain the combination scheme and train timetable. Finally, some experiments are implemented to illustrate the feasibility of the proposed approaches and demonstrate the effectiveness of the HGA.

Humidification-dehumidification desalination process using green hydrogen and heat recovery

We propose the use of green hydrogen as a fuel for a seawater heater in a humidification / dehumidification (HDH) desalination plant to increase its productivity, to allow scaling to large dimensions without negative environmental effects, and to guarantee continuous operation. We develop a mathematical model of the proposed HDH configuration. For operating conditions that guarantee very low NOX production, the fuel consumption is ~0.03 kg of H2 per kg of pure water produced. If the exhaust gases from the seawater heater are used for heat recovery, the GOR of the equipment may increase by up to 39 % in relation to the same equipment operating without heat recovery. The operation cost of freshwater is comparable to the costs obtained by other equipment in the literature. If the water produced in the combustion of hydrogen is condensed during the heat recovery process and then added to the freshwater produced, the production cost is reduced by 20 %. We found that an excess of air in the air+fuel mix beyond the minimum value appropriate for a low NOX generation does not provide significant benefits. The efficiency of the seawater heater has an impact on the production of pure water, but this impact is strongly mitigated by the heat recovery process. Fuel consumption increases proportionally with the decrease in the effectiveness of the heat recovery device, which is a key parameter for optimal performance. A hydrogen heater is also a good alternative as an auxiliary power source to guarantee continuous operation. On sunny hours a H2 heater may be used to increase productivity preheating the seawater, and at night the system could operate 100 % based on H2.

A Bi-Level Control Strategy for PV-BES System Aiming at the Minimum Operation Cost of BES

With the increased penetration of the photovoltaic (PV) energy, the power system stability problem becomes an issue, as the output power of PV plants has unpredictable fluctuations. To maintain the power stability of the PV plants, battery energy storages (BESs) play an important role due to their fast and accurate response speed. However, it is challenging that the BES with multiple sub-modules responds well to the PV power fluctuations resulting from the various influence factors, such as defects, faults, and partial shading. Therefore, a bi-level control strategy is proposed in this paper, aiming at minimizing the operation cost of BES in maintaining power stability. The control strategy consists of the PV power fluctuations identification block and the mitigation block. In specific, the identification block can output the power fluctuation of a PV system by the PV power fluctuation identification technique. The technique is developed based on the characteristics of PV-string current under electrical faults and partial shading conditions. Meanwhile, the mitigation block can manage the multiple battery sub-modules with different regulation characteristics to meet the power fluctuations. At last, the promising results are obtained by MATLAB\Simulink with the coordinated operation of those two blocks, including the precise condition of the PV system and the optimal power output of each battery sub-module. Therefore, a comprehensive bi-level control strategy is developed to regulate the operation of battery sub-modules for PV-BES systems.

Analysis and Optimization of Cooling Water System Operating Cost under Changes in Ambient Temperature and Working Medium Flow

The circulating cooling water system is widely used in various industrial production fields, and its operating cost largely depends on external factors, such as ambient temperature and working medium flow. Considering the relative elevation of the heat exchanger, this study establishes a total system operation cost analysis and optimization model based on the superstructure method. The model uses ambient dry bulb temperature, ambient wet bulb temperature, and working medium flow as random variables. Water supply temperature is adopted as the decision variable, and the minimum operating cost of the system is used as the objective function. An analysis of the effect of the three random variables on the operation cost shows that the effect of ambient dry bulb temperature on the operation cost is negligible, and the effect of ambient wet bulb temperature and working medium flow on the operation cost is significant. In addition, a control equation of water supply temperature is established to determine the “near optimal” operation, which is based on the correlation among ambient wet bulb temperature, working medium flow, and optimal water supply temperature. Then, the method is applied to a case system. The operating cost of the system is reduced by 22–31% at different times during the sampling day.

Preventive Control Strategy of Cascading Fault considering Safety and Economy

The operation and structure of the power system are becoming increasingly complex, and the probability of cascading fault increases. To this end, this paper proposes a cascading fault preventive control strategy that considers safety and the economy. First is to give a mathematical form to discriminate the cascading fault according to the action characteristics of the current-type backup protection. Second, the safety and economy of the system are evaluated in terms of power grid safety margin and generation operation cost, respectively, the initial faults are selected based on the power grid vulnerability and safety margin, and a cascading fault preventive control model is constructed for different initial faults’ scenarios. The model is a two-layer optimization mathematical model, with the inner model being solved by particle swarm optimization to minimize the power grid safety margin. The outer model is solved by the multiobjective algorithm to minimize generation cost and maximizing power grid safety margin. Finally, the calculated Pareto set is evaluated using fuzzy set theory to determine the optimal generator output strategy. The feasibility of the proposed method is verified by conducting a simulation study with the IEEE39 node system as an example.