scholarly journals Optimizing Production Scheduling of Steel Plate Hot Rolling for Economic Load Dispatch under Time-of-Use Electricity Pricing

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Mao Tan ◽  
Hua-li Yang ◽  
Bin Duan ◽  
Yong-xin Su ◽  
Feng He
Keyword(s):  
Hot Rolling ◽  
Production Scheduling ◽  
Peak Load ◽  
Economic Load Dispatch ◽  
Electricity Pricing ◽  
Nsga Ii ◽  
Planning And Scheduling ◽  
Batch Type ◽  
Power Load ◽  
Electricity Costs

Time-of-Use (TOU) electricity pricing provides an opportunity for industrial users to cut electricity costs. Although many methods for Economic Load Dispatch (ELD) under TOU pricing in continuous industrial processing have been proposed, there are still difficulties in batch-type processing, since power load units are not directly adjustable and nonlinearly depend on production planning and scheduling. In this paper, for hot rolling, a typical batch-type and energy intensive process in steel industry, a production scheduling optimization model for ELD is proposed under TOU pricing, in which the objective is to minimize electricity costs while considering penalties caused by jumps between adjacent slabs. A NSGA-II based multiobjective production scheduling algorithm is developed to obtain Pareto optimal solutions, and then TOPSIS based multicriteria decision-making is performed to recommend an optimal solution to facilitate field operation. Experimental results and analyses show that the proposed method cuts electricity costs in production, especially in case of allowance for penalty score increase in a certain range. Further analyses show that the proposed method has effect on peak load regulation of power grid.

scholarly journals Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing

Processes ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 42
Author(s):  
Zhengbiao Hu ◽  
Dongfeng He ◽  
Wei Song ◽  
Kai Feng
Keyword(s):  
Hot Rolling ◽  
Interaction Model ◽  
Rolling Process ◽  
Batch Processing ◽  
Steel Plant ◽  
Electricity Pricing ◽  
Improved Genetic Algorithm ◽  
Electricity Cost ◽  
Batch Type ◽  
Plan Optimization

Batch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rolling was established, using an objective function with the goal of minimizing the total penalty incurred by the differences in width, thickness, and hardness among adjacent slabs, as well as the electricity cost of the rolling process. A method was provided to solve the model through improved genetic algorithm. An analysis of the batch processing of the hot rolling of 240 slabs of different sizes at a steel plant proved the effectiveness of the proposed model. Compared to the man–machine interaction model and the model in which TOU electricity pricing was not considered, the batch-processing model that included TOU electricity pricing produced significantly better results with respect to both product quality and power consumption.

Coordinated Charging of EVs Based on Demand-Side Management

2014 ◽  
Vol 596 ◽  
pp. 760-765
Author(s):  
Yu Kai Li ◽  
Hong Ouyang ◽  
Jia Kui Zhao ◽  
Xiu Kai Rong ◽  
Yi Dong
Keyword(s):  
Large Scale ◽  
Peak Load ◽  
Demand Side Management ◽  
Optimal Number ◽  
Demand Side ◽  
Nsga Ii ◽  
On Demand ◽  
Load Fluctuation ◽  
Power Load ◽  
Coordinated Charging

Electric vehicles (EVs) are adopted as an effective way to reduce the pollution of atmosphere. However, if EVs are implemented in a large scale without control, peak load would increase significantly and the grid may be overloaded. Based on Demand-Side Management (DSM), an coordinated charging method for EVs to address the problem of that is proposed. Considering load fluctuation of power grid as well as time-of-use (TOU) power price, a multi-objective optimization model is formulated to minimize the charging cost and restrain the load fluctuation. Overall power load is composed of original daily load and EV charging load, which is obtained through Monte Carlo simulations. On the basis of this, the optimal number of charging EVs in each period is worked out with NSGA-II algorithm. At last, the case study carried out shows the reasonability of this method.

scholarly journals Sustainable Scheduling of the Production in the Aluminum Furnace Hot Rolling Section with Uncertain Demand

2021 ◽  
Vol 13 (14) ◽  
pp. 7708
Author(s):  
Yiping Huang ◽  
Qin Yang ◽  
Jinfeng Liu ◽  
Xiao Li ◽  
Jie Zhang
Keyword(s):  
Hot Rolling ◽  
Production Scheduling ◽  
Demand Uncertainty ◽  
Flow Shop ◽  
Operation Time ◽  
Decision Time ◽  
Scenario Tree ◽  
Mixed Integer ◽  
Rolling Horizon ◽  
The Sustainable Development

In order to reduce the energy consumption of furnaces and save costs in the product delivery time, the focus of this paper is to discuss the uncertainty of demand in the rolling horizon and to globally optimize the sustainability of the production in the aluminum furnace hot rolling section in environmental and economic dimensions. First, the triples α/β/γ are used to describe the production scheduling in the aluminum furnace hot rolling section as the scheduling of flexible flow shop, satisfied to constraints of demand uncertainty, operation logic, operation time, capacity and demand, objectives of minimizing the residence time of the ingot in the furnace and minimizing the makespan. Second, on the basis of describing the uncertainty of demand in rolling horizon with the scenario tree, a multi-objective mixed integer linear programming (MILP) optimization model for sustainable production in the aluminum furnace hot rolling section is formulated. Finally, an aluminum alloy manufacturer is taken as an example to illustrate the proposed model. The computational results show that when the objective weight combination takes the value of α=0.7, β=0.3, the sustainability indicators of the environmental and economic dimensions can be optimized to the maximum extent possible at the same time. Increasingly, managerial suggestions associated with the trade-off between environmental and economic dimensions are presented. Scheduling in the rolling horizon can optimize the production process of the aluminum furnace hot rolling section globally, indicating that it is more conducive to the sustainable development of the environment and economic dimensions than scheduling in a single decision time period.

Production Scheduling Method to Reduce Fuel Costs of Hot Rolling Processes

2020 ◽  
Vol 2020 (0) ◽  
pp. S14202
Author(s):  
Takeru DOAN ◽  
Satoshi NAGAHARA ◽  
Takafumi CHIDA ◽  
Junichi KATSUBE ◽  
Tooru ADACHI ◽  
...  
Keyword(s):  
Hot Rolling ◽  
Production Scheduling ◽  
Scheduling Method ◽  
Fuel Costs

scholarly journals Peak load minimization of an e-bus depot: impacts of user-set conditions in optimization algorithms

2021 ◽  
Vol 4 (S3) ◽  
Author(s):  
Enrico Toniato ◽  
Prakhar Mehta ◽  
Stevan Marinkovic ◽  
Verena Tiefenbeck
Keyword(s):  
Optimization Algorithm ◽  
Peak Load ◽  
Mixed Integer ◽  
Computational Time ◽  
Transport Sector ◽  
Fleet Management ◽  
Peak Reduction ◽  
Management Options ◽  
Power Load ◽  
The Impact

AbstractThe transport sector is responsible for 25% of global CO2 emissions. To reduce emissions in the EU, a shift from the currently 745,000 operating public buses to electric buses (EBs) is expected in the coming years. Large-scale deployments of EBs and the electrification of bus depots will have a considerable impact on the local electric grid, potentially creating network congestion problems and spikes in the local energy load. In this work, we implement an exact, offline, modular multi-variable mixed-integer linear optimization algorithm to minimize the daily power load profile peak and optimally plan an electric bus depot. The algorithm accepts a bus depot schedule as input, and depending on the user input on optimization conditions, accounts for varying time granularity, preemption of the charging phase, vehicle-to-grid (V2G) charging capabilities and varying fleet size. The primary objective of this work is the analysis of the impact of each of these input conditions on the resulting minimized peak load. The results show that our optimization algorithm can reduce peak load by 83% on average. Time granularity and V2G have the greatest impact on peak reduction, whereas preemption and fleet splitting have the greatest impact on the computational time but an insignificant impact on peak reduction. The results bear relevance for mobility planners to account for innovative fleet management options. Depot infrastructure costs can be minimized by optimally sizing the infrastructure needs, by relying on split-fleet management or V2G options.

scholarly journals Strategies for Datacenters Participating in Demand Response by Two-Stage Decisions

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yuling Li ◽  
Xiaoying Wang ◽  
Peicong Luo
Keyword(s):  
Smart Grid ◽  
Demand Response ◽  
Smart Grids ◽  
Peak Load ◽  
Two Stage ◽  
The Sustainable Development ◽  
Second Stage ◽  
Potential Demand ◽  
Electricity Costs ◽  
Demand Response Programs

Modern smart grids have proposed a series of demand response (DR) programs and encourage users to participate in them with the purpose of maintaining reliability and efficiency so as to respond to the sustainable development of demand-side management. As a large load of the smart grid, a datacenter could be regarded as a potential demand response participant. Encouraging datacenters to participate in demand response programs can help the grid to achieve better load balancing effect, while the datacenter can also reduce its own power consumption so as to save electricity costs. In this paper, we designed a demand response participation strategy based on two-stage decisions to reduce the total cost of the datacenter while considering the DR requirements of the grid. The first stage determines whether to participate in demand response by predicting real-time electricity prices of the power grid and incentive information will be sent to encourage users to participate in the program to help shave the peak load. In the second stage, the datacenter interacts with its users by allowing users to submit bid information by reverse auction. Then, the datacenter selects the tasks of the winning users to postpone processing them with awards. Experimental results show that the proposed strategy could help the datacenter to reduce its cost and effectively meet the demand response requirements of the smart grid at the same time.

scholarly journals Capacity Design and Cost Analysis of Converged Renewable Energy Resources by Considering Base Load Conditions in Residential and Industrial Areas

2020 ◽  
Vol 10 (21) ◽  
pp. 7822
Author(s):  
Sang Hun Lee ◽  
Wonbin Lee ◽  
Jin Hee Hyun ◽  
Byeong Gwan Bhang ◽  
Jinho Choi ◽  
...  
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Fuel Cells ◽  
Storage System ◽  
Peak Load ◽  
Power Source ◽  
Design Technique ◽  
Renewable Energy Resources ◽  
Power Load ◽  
Base Load

In this paper, a design technique for constructing a renewable-energy-based power system based on a customer’s power load is proposed. The proposed design technique adopts a second renewable energy power source in charge of the base load and is an improved method of the referenced studies with one type of renewable energy power source. In this proposed method, fuel cells are adopted as the base power source, and PV (photovoltaic) power generation and an ESS (energy storage system) are adopted as the power generation sources that supply the middle-load and peak-load power. When the fuel cell is applied as a base power source through the method designed in this study, a cost reduction of approximately 30.03% is expected, compared to a system that does not use a base power source. In addition, the criteria for securing a system’s power supply stability and the economics when fuel cells are adopted are analyzed in terms of the system’s installation cost.

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