2014 Sixth Annual IEEE Green Technologies Conference最新文献

Observer Based Sensor Fault Tolerant for Grid Tied - Solar Inverters 并网太阳能逆变器基于观测器的传感器容错

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.16

Andres Salazar-Llinas, A. Ginart, C. Restrepo

{"title":"Observer Based Sensor Fault Tolerant for Grid Tied - Solar Inverters","authors":"Andres Salazar-Llinas, A. Ginart, C. Restrepo","doi":"10.1109/GREENTECH.2014.16","DOIUrl":"https://doi.org/10.1109/GREENTECH.2014.16","url":null,"abstract":"Grid-tied Solar Inverters rely heavily on the current sensor information to fulfill all the complex tasks associated to deliver appropriate power to the energy system with low distortion. Sensing voltage and current are an essential part of the feedback current control loop for any grid tied-solar inverter. When the sensed signal is lost, the inverter output could become unstable thus having, as a consequence, over-current situations, and other undesired power generation conditions that could lead to the catastrophic failure of the inverter. To overcome this issue, a fault-tolerant system is proposed using an observer structure designed as a way to make a 3 phase inverter current control system immune to any fault or lost of its sensing capabilities. The sensor verification is made by a smart control capable of monitoring the physical sensor operation and switch to the synthetics sensors in case of physical damage of the equipment. The proposed technique is verified by inserting a sensor fault in the system. Under this condition a good performance of the proposed fault tolerant structure is observed. The fault tolerant scheme is able to follow and determine the sensing signal lost or corrupted and seemliness continue the operation of the inverter, notified of the fault situation and wait planned shutdown is scheduled.","PeriodicalId":194092,"journal":{"name":"2014 Sixth Annual IEEE Green Technologies Conference","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133794640","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}

引用次数: 2

Review of State and National Renewable Energy Policies 回顾州和国家可再生能源政策

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.13

Venkatesh Yadav Singarao, R. Singh

引用次数: 5

Designing the Optimal Pricing Policy for Aggregators in the Smart Grid 智能电网中聚合器最优定价策略设计

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.28

Xue Lin, Yanzhi Wang, Massoud Pedram

{"title":"Designing the Optimal Pricing Policy for Aggregators in the Smart Grid","authors":"Xue Lin, Yanzhi Wang, Massoud Pedram","doi":"10.1109/GREENTECH.2014.28","DOIUrl":"https://doi.org/10.1109/GREENTECH.2014.28","url":null,"abstract":"The real-time pricing policy can incentivize the electricity users to dynamically change or shift their electricity consumption, thereby improving reliability of the grid. In the smart grid infrastructure, aggregators between the electricity suppliers and users control the users' electricity consumption by dynamically setting electricity price. This work aims at maximizing the overall profit of an aggregator in a billing period by designing a real-time pricing policy. The aggregator pre-announces a pricing policy for an entire billing period, then in each time interval of the billing period, the electricity users (i.e., both residential and EV users) try to maximize their own utility functions based on the pricing model in the current time interval and the awareness of the other users' behaviors. We first formulate a nested two-stage game between the aggregator and the users for each time interval in a billing period, in which the sub game perfect equilibrium can be found. Then, based on backward induction, a dynamic programming algorithm is presented to derive the optimal real-time pricing policy for maximizing the aggregator's overall profit. Different from other works, a battery energy storage system (BESS) is integrated with the aggregator to buffer the mismatch between supply and demand and to improve reliability of the grid. More importantly, this work derives the optimal pricing policy for an aggregator from a global point of view, taking into account the BESS energy state variation in a billing period. Simulation results show that the optimal pricing policy can achieve up to 24.3% improvement on the aggregator's overall profit.","PeriodicalId":194092,"journal":{"name":"2014 Sixth Annual IEEE Green Technologies Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123157150","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}

引用次数: 6

A Probability Theory Based Price Determination Framework for Utility Companies in an Oligopolistic Energy Market 寡头垄断能源市场中公用事业公司基于概率论的价格决策框架

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.11

Tiansong Cui, Yanzhi Wang, Xue Lin, Shahin Nazarian, Massoud Pedram

{"title":"A Probability Theory Based Price Determination Framework for Utility Companies in an Oligopolistic Energy Market","authors":"Tiansong Cui, Yanzhi Wang, Xue Lin, Shahin Nazarian, Massoud Pedram","doi":"10.1109/GREENTECH.2014.11","DOIUrl":"https://doi.org/10.1109/GREENTECH.2014.11","url":null,"abstract":"Distributed power generation and distribution network with the dynamic pricing scheme are the major trend of the future smart grid. A smart grid is a network which contains multiple non-cooperative utility companies that offer time-of-use dependent energy prices to energy consumers and aim to maximize their own profits. Decentralized power network allows each energy consumer to have multiple choices among different utility companies. In this paper, an optimization framework is introduced to determine the energy price for utility companies in an oligopolistic energy market. At the beginning of each billing period (a day), each utility company will announce the time-of-use dependent pricing policy during the billing period, and each energy consumer will subsequently choose a utility company for energy supply to minimize the expected energy cost. The energy pricing competition among utility companies forms an n-person game because the pricing strategy of each utility company will affect the profits of others. To be realistic, the prediction error of a user's energy consumption is properly accounted for in this paper and is assumed to satisfy certain probability distribution at each time slot. We start from the most commonly-used normal distribution and extend our optimization framework to a more general case. A Nash equilibrium-based pricing policy is presented for the utility companies and the uniqueness of Nash equilibrium is proved. Experimental results show the effectiveness of our game theoretic price determination framework.","PeriodicalId":194092,"journal":{"name":"2014 Sixth Annual IEEE Green Technologies Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123299937","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}

引用次数: 0

Analysis and Control of Ripple Eliminators in DC Systems 直流系统纹波消除器的分析与控制

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.23

Xin Cao, Qing-Chang Zhong, Wen-Long Ming

引用次数: 4

Dynamic Power Control of a PV-Fuel Cell Hybrid Energy System Used in DC Motors Applications 直流电机用光伏-燃料电池混合能源系统的动态功率控制

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.19

Andres Salazar-Llinas, E. Ortiz-Rivera, J. Gonzalez-Llorente

引用次数: 1

An Investigation of Parametric Load Leveling Control Methodologies for Resistive Heaters in Smart Grids 智能电网电阻加热器参数化负荷均衡控制方法研究

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.15

Lee Holland, H. Karayaka, Martin L. Tanaka, Aaron Ball

引用次数: 4

Improved Estimation of Induction Motor Circuit Parameters with Published Motor Performance Data 利用已公布的电机性能数据改进感应电机电路参数估计

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.18

Gang Wang, Sungwan Park

引用次数: 8

Study of Utilization of Wind Induced Vibrations in Generation of Electricity 风力振动在发电中的应用研究

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.17

A. Aithal, A. Deshpande, P. Dinesh

引用次数: 0

Ocean Energy Conversion and Storage Prototypes for Wave, Current and Tidal Energy Generators 波浪、电流和潮汐能发电机的海洋能量转换和存储原型

2014 Sixth Annual IEEE Green Technologies Conference Pub Date : 2014-04-03 DOI: 10.1109/GREENTECH.2014.26

M. Mehrubeoglu, L. McLauchlan, Bora Karayaka

引用次数: 4