scholarly journals Optimal Scheduling of Microgrid Considering the Interruptible Load Shifting Based on Improved Biogeography-Based Optimization Algorithm

Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1707
Author(s):  
Bo Li ◽  
Hongsheng Deng ◽  
Jue Wang
Keyword(s):  
Optimization Algorithm ◽  
Operation Mode ◽  
Operating Cost ◽  
Electricity Consumption ◽  
Optimal Operation ◽  
Environmental Benefits ◽  
Interruptible Load ◽  
Dispatching Algorithm ◽  
Power Dispatching ◽  
Adaptively Adjusting

A microgrid is an efficient method of uniting distributed generations. To ensure the applicability and symmetry of the microgrid, the environmental benefits and economic costs are considered to comprehensively model the optimal operation of the microgrid under the grid-connected operation mode, at the same time, considering the effect of interruptible load on the operating cost of the microgrid, the power shifting for interruptible load is attempted on the basis of battery storage capacity. By adaptively adjusting the migration rate using the habitat suitability index of a normalized individual and adding a certain differential perturbation to the migration operator of the migration mechanism, an improved biogeography-based optimization algorithm is proposed and the microgrid optimization dispatching algorithm based on the improved biogeography-based optimization is applied. The advancement and effectiveness of the proposed algorithm and model is verified by the example, and the simulation results indicate that the implementation of the power dispatching scheme proposed in this paper can effectively reduce the total cost of the system. Moreover, the proper consideration of shifting interruptible load, the effective load management and guiding the electricity consumption behavior of users are of certain significance for optimizing the utilization of renewable energy and improving the system efficiency and economy.

Study on the Promotion and Operation Mode of Household Electric Vehicle

2014 ◽  
Vol 1030-1032 ◽  
pp. 2121-2125
Author(s):  
Wei Qing Zhai ◽  
Zhi Min Zhao
Keyword(s):  
Energy Saving ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Product Innovation ◽  
Operation Mode ◽  
Operating Cost ◽  
Environmental Benefits ◽  
Management Measures ◽  
The Times ◽  
Service Agencies

The electric vehicle is a newly powered walker alternative tool with good environmental benefits and low operating cost. The subsidy on the product innovation, environmental protection and energy saving is not issued in time because of policy lag, and therefore management measures can't keep pace with the times. This leads to the currently inefficient marketing of household electric vehicle, and its difficult operation situation in our country. This article begins with the promotion and operation mode of household electric vehicles, and puts forward some proposals for the popularization of household electric vehicle which can provide some reference for management department, the electric vehicle manufacturers, and the electric vehicle sales and service agencies.

scholarly journals Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy

2021 ◽  
Vol 7 ◽  
pp. 3703-3725
Author(s):  
Mohammad Ehteram ◽  
Fatemeh Barzegari Banadkooki ◽  
Chow Ming Fai ◽  
Mohsen Moslemzadeh ◽  
Michelle Sapitang ◽  
...  
Keyword(s):  
Power Generation ◽  
Optimization Algorithm ◽  
Optimal Operation ◽  
Reservoir Systems

scholarly journals IMPROVING THE EFFICIENCY OF THE PROCESS OF TECHNICAL OPERATION OF VEHICLES BY USING THE DISTANCE DIAGNOSTIC METHOD

2019 ◽  
Vol 22 (6) ◽  
pp. 6-13 ◽  
Author(s):  
E. V. Ageeva ◽  
B. N. Sabelnikov ◽  
A. V. Shcherbakov ◽  
A. I. Pykhtin
Keyword(s):  
Motor Vehicle ◽  
Operation Mode ◽  
Significant Proportion ◽  
Road Transport ◽  
Spare Parts ◽  
Optimal Operation ◽  
Diagnostic Tools ◽  
Technical Diagnostics ◽  
Causes Of Errors ◽  
Technical Operation

The current economic situation in the global fuel market leads to the fact that there is a rise in the cost of operating vehicles. All this makes the owners of such vehicles pay close attention to their optimal operation mode, which primarily depends on competent diagnosis of its components. Saving fuel-operating resources of a modern car directly depends on optimally adjusted parameters of operation of all components and assemblies of a car. The purpose of this work was to increase the efficiency of the process of technical operation of vehicles through the use of the method of remote diagnostics on the example of LLC POGA-1. The practice of using diagnostic tools demonstrates the possibilities of reducing operating costs. This is achieved due to an increase in the resources actually used, a decrease in the number of repairs and the saving of spare parts costs. Over the past years in the Russian Federation has been actively developing the field of freight. The largest share falls on road transport (67.7%). A significant proportion of the country's truck fleet is used as a commercial vehicle, which significantly complicates the procedure for timely diagnosis. Thus, in the event of a malfunction or error in the operation of a motor vehicle, the vehicle can be on a flight and there will not be a specialized service station within range of technical diagnostics of the truck to identify the causes of errors and / or malfunctions. The established problem finds its solution in the application of the method of remote diagnosis of commercial vehicles straight from the TO center, which is equipped with the necessary complex for diagnosing.

Micro-Grid Energy Optimization Include Battery-Swapping-Station

2014 ◽  
Vol 672-674 ◽  
pp. 1358-1363
Author(s):  
Liu Shu ◽  
Fang Liu ◽  
Xiu Yang
Keyword(s):  
Genetic Algorithm ◽  
Renewable Energy ◽  
Electric Vehicle ◽  
Negative Impact ◽  
Operating Cost ◽  
Energy Optimization ◽  
Optimal Operation ◽  
Operation Efficiency ◽  
Micro Grid ◽  
Minimum Operating

Accessing electric vehicle (EV) into micro-grid (MG) by battery-swapping station (BSS) will not only reduce the negative impact brought by EVs which are directly accessed into MG, but also improve the capacity of MG to absorb more renewable energy. That BSS is regarded as schedulable load is guided to avoid peak and fill valley according to TOU. As a result, the gap between peak and valley of MG is decreased and the operation efficiency of MG is elevated. A specific MG is taken as the studying object and the minimum operating cost is regarded as the optimizing goal, then the genetic algorithm is used to optimize the outputting of each micro-source and the charging power of BSS so that the optimal operation is realized.

A decision-making method based on Bayesian optimization algorithm for small modular reactor

Kerntechnik ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. 109-121 ◽  
Author(s):  
B. Zhang ◽  
M. Peng ◽  
S. Cheng ◽  
L. Sun
Keyword(s):  
Decision Making ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Optimal Operation ◽  
Bayesian Optimization ◽  
Operating Personnel ◽  
Bayesian Optimization Algorithm ◽  
Autonomous Operation ◽  
Small Modular Reactor ◽  
The Cost

Abstract Small modular reactors (SMRs) are suitable for deployment in isolated underdeveloped areas to support highly localized microgrids. In order to achieve almost autonomous operation for reducing the cost of operating personnel, an autonomous control system with decision-making capability is needed. In this paper, a decision-making method based on Bayesian optimization algorithm (BOA) is proposed to explore the optimal operation scheme under fault conditions. BOA is used to adjust exploration strategy of operation scheme according to observations (operation schemes previously explored). To measure the feasibility of each operation scheme, an objective function that considers security and economy is established. BOA attempts to obtain the optimal operation scheme with maximum of the objective function in as few iterations as possible. To verify the proposed method, all main pump powered off fault is simulated by RELAP5 code. The optimal operation scheme of the fault is applied, the transient result shows that all key parameters are within safe limits and SMR is maintained at relatively high power, which means that BOA has the decision-making capability to get an optimal operation scheme on fault conditions.

A combined effective time series model based on clustering and whale optimization algorithm for forecasting smart meters electricity consumption

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Medhat Abd el Azem El Sayed Rostum ◽  
Hassan Mohamed Mahmoud Moustafa ◽  
Ibrahim El Sayed Ziedan ◽  
Amr Ahmed Zamel
Keyword(s):  
Optimization Algorithm ◽  
Prediction Accuracy ◽  
Electricity Consumption ◽  
Whale Optimization Algorithm ◽  
Computational Time ◽  
Smart Meters ◽  
Content Type ◽  
Individual Level ◽  
Consumption Values ◽  
Whale Optimization

Purpose The current challenge for forecasting smart meters electricity consumption lies in the uncertainty and volatility of load profiles. Moreover, forecasting the electricity consumption for all the meters requires an enormous amount of time. Most papers tend to avoid such complexity by forecasting the electricity consumption at an aggregated level. This paper aims to forecast the electricity consumption for all smart meters at an individual level. This paper, for the first time, takes into account the computational time for training and forecasting the electricity consumption of all the meters. Design/methodology/approach A novel hybrid autoregressive-statistical equations idea model with the help of clustering and whale optimization algorithm (ARSEI-WOA) is proposed in this paper to forecast the electricity consumption of all the meters with best performance in terms of computational time and prediction accuracy. Findings The proposed model was tested using realistic Irish smart meters energy data and its performance was compared with nine regression methods including: autoregressive integrated moving average, partial least squares regression, conditional inference tree, M5 rule-based model, k-nearest neighbor, multilayer perceptron, RandomForest, RPART and support vector regression. Results have proved that ARSEI-WOA is an efficient model that is able to achieve an accurate prediction with low computational time. Originality/value This paper presents a new hybrid ARSEI model to perform smart meters load forecasting at an individual level instead of an aggregated one. With the help of clustering technique, similar meters are grouped into a few clusters from which reduce the computational time of the training and forecasting process. In addition, WOA improves the prediction accuracy of each meter by finding an optimal factor between the average electricity consumption values of each cluster and the electricity consumption values for each one of its meters.

scholarly journals Optimal operation strategy for subway HVAC system in transition seasons

2019 ◽  
Vol 111 ◽  
pp. 03006
Author(s):  
Yue Zhang ◽  
Xiaofeng Li ◽  
Bin Wang ◽  
Zheren Song
Keyword(s):  
Energy Saving ◽  
Calculation Method ◽  
Operation Mode ◽  
Water System ◽  
Optimal Operation ◽  
Operation Strategy ◽  
Ventilation Mode ◽  
Switching Condition ◽  
System Temperature ◽  
Switching Temperature

This paper mainly studied the operation strategy for subway VAC system during transition seasons. Two modes including WF-AC (Whole Fresh air- Air Conditioning) mode and B/E-V (Back/Exhausted fan-Ventilation) mode were selected based on energy saving principle. In order to decide the optimal operation mode, the calculation method of “switching temperature” was proposed. The main influencing factors of the switching condition include indoor cooling load, COP of the chilled-water-system, temperature difference of the supply air, efficiency of fan and the resistance of air duct. Also, the transfer temperature diagram is provided based on proposed calculation method, which is suitable for engineering use. The aim of this study is to regulate the operation mode and to promote energy saving in subway station.

Equipment Integration-Based Workshop e-Manufacturing Execution Mode and Supporting Technologies

2009 ◽  
Vol 407-408 ◽  
pp. 207-210
Author(s):  
Qi Feng Wang
Keyword(s):  
Real Time ◽  
System Integration ◽  
Manufacturing System ◽  
Operation Mode ◽  
Optimal Operation ◽  
Time Data ◽  
Information Interaction ◽  
Key Issues ◽  
Execution Mode ◽  
Manufacturing Execution

To effectively realize the optimal operation target of paperless production, real time production and integration in manufacturing process for workshop manufacturing system, this paper puts forward an equipment integration-based workshop e-Manufacturing execution mode, and analyzes the basic elements for the operation mode. Furthermore, some of the key issues which are important to support the operation mode are described in detail, including system integration technologies, equipment integration-based real time data collection and information interaction technologies. Finally, the operation mode is applied in a NC workshop of an automobile part manufacturing enterprise in Chongqing, and its feasibility is demonstrated.

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