2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)最新文献

{"title":"Constructing Probabilistic Load Forecast From Multiple Point Forecasts: A Bootstrap Based Approach","authors":"Jiawei Zhang, Yi Wang, Mingyang Sun, Ning Zhang, C. Kang","doi":"10.1109/ISGT-ASIA.2018.8467888","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467888","url":null,"abstract":"Probabilistic load forecast presents more information on the possible deviation of forecast than the point forecast. There are sufficient regression models that can make point forecasts. An intuitive question can be raised: Is there a way to combine the point forecasts to construct a probability or interval forecast? In this paper, a bootstrap based ensemble approach is put forward to construct forecast intervals from multiple point forecasts. Specifically, multiple point forecasting models are first trained based on the bootstrap sampled training datasets and different forecasting models. Then, bootstrap is applied again to the multiple point forecasts. Finally, the quantiles are estimated according to the distribution of the sampled point forecasts. Two common machine learning methods, random forest (RF) and gradient boosting regression tree (GBRT), are combined to test the feasibility of the proposed forecasting framework. Compared with quantile RF (Q-RF) and quantile GBRT (Q-GBRT), numerical experiments demonstrate its advantage over Q-RF and Q-GBRT.","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116639299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal Charging Schedule for Electric Vehicles in Parking Lot with Solar Power Generation","authors":"A. Mathur, Charan Teja S, P. Yemula","doi":"10.1109/ISGT-ASIA.2018.8467916","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467916","url":null,"abstract":"In order to reduce the carbon emission from vehicles, the world transportation system is transforming from conventional gasoline vehicles to electric vehicles. This transformation introduced high penetration of electric vehicles into the utility grid. This lead to a new scope of research in the area of scheduling the charging of electric vehicles. In this context the electric vehicles arriving at the parking lot is increasing which leads a challenge to parking lot owner for scheduling of vehicles for charging. The primary objective of parking lot owner is to charge more vehicles and increase his profit. But due to stringent rules from regulators for network upgrades, increase in the number of charging slots is challenging. Installing a distributed generation like solar microgrid will benefit from allowing many vehicles to charge at the parking lot. This paper aims in proposing an algorithm called parking lot management system (PLMS) for optimal scheduling of electric vehicles with the support of solar generation with the objective of minimizinz the power drawl from the grid during high peak pricing period. Power drawl from the grid is reduced by using the solar power available. Since the power drawl from the grid is reduced, it is obvious that the profit of the parking lot owner is increased. Optimal scheduling is done by shifting the cars to the abundant solar power period and reducing the peaks on the grid which helps the utility operator. The proposed algorithm is simulated using MATLAB programming, and the results are presented. Here in the simulation, it is considered two cases one is the uncoordinated case, and the other is coordinated case. In uncoordinated case charging strategy is first come first served (FCFS) basis and in coordinated case scheduling is done by shifting of cars to abundant solar periods for reducing the cost. It is observed from the results that the savings with solar installation and the uncoordinated case is ₹2729.59 and whereas with the coordinated case the savings are ₹2891.19 for one day. Since the savings are more in coordinated case, it is suggested that coordinated scheduling of vehicles will increase the profit of the parking lot owner.","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116797878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Power Converters for DC Microgrids – Modelling and Simulation","authors":"Zhuang Fusheng, R. T. Naayagi","doi":"10.1109/ISGT-ASIA.2018.8467847","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467847","url":null,"abstract":"This paper presents the performance verification and suitability of a simple boost DC-DC converter and an impedance source boost DC-DC converter for modern DC microgrid applications. Most of the renewable energy resources suitable for Singapore operate at a low voltage. Hence it is important to boost the low voltage obtained from the renewable source to the voltage suitable for the DC bus/load in a DC microgrid. In this context, a 10kW power electronic converter is designed to interface PV resource to the DC bus of a microgrid. Simulink model of the system using a simple boost converter and an impedance source boost converter is designed. Simulation results during steady-state and transient operating conditions demonstrates the performance of the converters and the controller, and confirms the suitability of these converters for the DC microgrid.","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129826298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Day-Ahead PV Power Output for Improved Radial Basis Function Neural Network","authors":"H. J. Lu, H. T. Chen, G. Chang","doi":"10.1109/ISGT-ASIA.2018.8467800","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467800","url":null,"abstract":"Photovoltaic (PV) power output forecasting is a crucial issue in the PV power industry and power company. Nevertheless, the disadvantage of the existing PV power output forecasting models is that they often ignore weather fluctuation and uncertain information between the irradiation and ambient temperature caused by moving cloud, which leads to short of forecasting accuracy. This paper is to present an improved radial basis function neural network structure (RBFNN) with multi- parameters forecasting scheme to overcome above drawbacks. Result of the case study acquired by the proposed scheme is compared with two typical artificial neural network forecasting methods including radial basis function neural network (RBFNN) and back propagation neural network (BPNN). It demonstrations that the proposed model leads to better precision for forecasting PV power output.","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"65 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125304080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model Predictive Control of Induction Machine for Energy Efficient HVAC Operation","authors":"Hanwen Zhang, A. Ukil","doi":"10.1109/ISGT-ASIA.2018.8467875","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467875","url":null,"abstract":"Recently, the energy efficiency in the building has attracted significant research attention. Many papers talk about the optimizations around the Heating Ventilation and Air-Conditioning (HVAC) system, such as sensors and model predictive control (MPC)-based thermostats in the system. However, most of them do not consider the energy usage on the drive level where the fans and pumps are powered by the Induction Machine (IM) which consumes about 50% to 75% of total energy consumption in the overall HVAC system. The various drive control strategies might render different energy savings by considering the losses in the IM (e.g., switching, current, and torque loss) in the different HVAC operating conditions (e.g., ambient temperature changes, etc This paper has analyzed the drive performance under different HVAC operating conditions, including the simulation results for the speed and torque ripples; torque loss and fan power consumption.","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127960057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model Predictive Control for Hybrid Energy StorageSystem using Single-InductorDual-Input Single-Output Converter","authors":"S. M. Tan, Benfei Wang, U. Manandhar, Kalpesh Chaudhari, Amrit Paudel, H. Gooi","doi":"10.1109/ISGT-ASIA.2018.8467942","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467942","url":null,"abstract":"This paper proposes a single-inductor dual-input single-output (SI-DISO) converter for the hybrid energy storage system (HESS) which consists of two energy storages with different characteristics. A model predictive control (MPC) based controller is developed to distribute the variable load power demand and renewable power generation efficiently to the two energy storages based on their characteristics. Ultimately, the DC bus voltage of the DC microgrid is maintained at a constant voltage value, without being affected much by the fluctuation of renewable power generation and the variable load power demand. By sharing a single-inductor converter for the energy storages, the number of circuit components, topology complexity and cost can be reduced. The workability and effectiveness of the proposed method is validated by conducting hardware in-loop (HIL) experiments, and the HIL experimental results are analyzed in details.","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122951660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Analysis of Reduced Communication Network in DC Microgrid","authors":"A. Shyam, Anoop Ingle, S. R. Sahoo, S. Anand","doi":"10.1109/ISGT-ASIA.2018.8467839","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467839","url":null,"abstract":"Distributed secondary controllers for dc microgrids have proven to be more effective and reliable as compared to decentralized and centralized controllers, respectively. The distributed secondary controller relies on information exchange between the distributed units. Conventionally, a full communication network topology is used, wherein all controllers communicate with each other. Recently, adoption of consensus control in DC microgrids have enabled achieving good performance using reduced communication network. This work aims at comparing the performance of the secondary controller with reduced and full communication topologies. It is shown that with proper tuning of gains, the secondary controller under reduced communication has similar performance as under full communication. The results are substantiated with numerical simulations using MATLAB/Simulink..","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128470557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive and Integrated PV Output control with Battery Energy Storage","authors":"Chenrui Jin, Ratnesh K. Sharma","doi":"10.1109/ISGT-ASIA.2018.8467866","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467866","url":null,"abstract":"An adaptive control system for battery integrated PV generation is designed to reduce the fluctuating in PV power production. The core component of the system is a four-layer power control system (PCS) for Battery Energy Storage (BES). BES responds to the power dispatch commands from PCS and charges/discharges to mitigate variations in PV power output. As a core part of the system, a novel PV power smoothing algorithm is proposed to reduce battery capacity requirements and reduce battery life losses by adaptively adjusting control parameter settings based on real-time system characteristics. Extensive simulation results based on real PV generation data have been presented to justify the effectiveness of the proposed approach and to show how several key parameters affect its performance.","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114745671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Data-Based Techno-economic Evaluation of Solar Hydrogen Production in the Middle East and North Africa (MENA) Region","authors":"A. Alshehri, G. Mogi, R. Endo","doi":"10.1109/ISGT-ASIA.2018.8467781","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467781","url":null,"abstract":"The Middle East and North Africa (MENA) region is endowed with solar energy that can be harvested and stored as hydrogen, which has gained increasing focus as a secondary energy medium. This paper introduces modeling and feasibility analysis of cost-optimized hydrogen production, storage, shipment, and methanation in the MENA region. The analysis is based on the economic modeling of hydrogen production through the combination of photovoltaic solar power and electrolysis systems, utilizing NASA surface Meteorology and Solar Energy database (2010) [1]. A system of 100MW grid-connected photovoltaic PV power plant (grid-PV) in combination with hydrogen producing electrolyzer are simulated using spatial data for the MENA region. Then, the simulation assesses cost of methane production by Sabatier synthesis of carbon dioxide. The unit cost of hydrogen from a system, which consists of 100MW PV solar plant and electrolyzer, ranged 4-8 US$/kg. Methanation was found to be expensive vis-à-vis regionally traded natural gas. Location is a major determinant to hydrogen cost due to the difference in irradiation and logistics. In conclusion, this paper can serve as an atlas for mapping the cost of solar power and hydrogen production in the MENA region, and facilitates further research in the future.","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116789404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Traveling Wave Based Method for Fault Location in Multi-Lateral Distribution Network with DG","authors":"Ranjeet Kumar, D. Saxena","doi":"10.1109/ISGT-ASIA.2018.8467895","DOIUrl":"https://doi.org/10.1109/ISGT-ASIA.2018.8467895","url":null,"abstract":"A fault location method based on traveling wave principle is presented in this paper for a multi-lateral distribution network with Distributed Generation (DG). Fault detection and faulted phase selection is performed using Wavelet Energy Entropy (WEE) of three-phase currents and the involvement of ground in the fault is detected by observing the magnitude of Wavelet Modulus Maxima (WMM) of ground mode component of the modal transformation matrix. The WMM of aerial mode component is used for identification of faulted lateral and the exact fault point location for different types of fault. Effectiveness of the proposed method is tested with the Distributed Generation (DG) connected in the distribution network. The results obtained show that the proposed fault location scheme is robust, more accurate and reliable under various fault condition.","PeriodicalId":126140,"journal":{"name":"2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114177064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}