2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG)最新文献

A simple recurrent neural network for solution of linear programming: Application to a Microgrid 求解线性规划的简单递归神经网络:在微电网中的应用

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-09 DOI: 10.1109/CIASG.2014.7011550

J. Sánchez‐Torres, Martin J. Loza-Lopez, R. Ruiz-Cruz, E. Sánchez, A. Loukianov

引用次数: 3

A low-complexity energy disaggregation method: Performance and robustness 一种低复杂度能量分解方法:性能和鲁棒性

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-09 DOI: 10.1109/CIASG.2014.7011569

Hana Altrabalsi, J. Liao, L. Stanković, V. Stanković

{"title":"A low-complexity energy disaggregation method: Performance and robustness","authors":"Hana Altrabalsi, J. Liao, L. Stanković, V. Stanković","doi":"10.1109/CIASG.2014.7011569","DOIUrl":"https://doi.org/10.1109/CIASG.2014.7011569","url":null,"abstract":"Disaggregating total household's energy data down to individual appliances via non-intrusive appliance load monitoring (NALM) has generated renewed interest with ongoing or planned large-scale smart meter deployments worldwide. Of special interest are NALM algorithms that are of low complexity and operate in near real time, supporting emerging applications such as in-home displays, remote appliance scheduling and home automation, and use low sampling rates data from commercial smart meters. NALM methods, based on Hidden Markov Model (HMM) and its variations, have become the state of the art due to their high performance, but suffer from high computational cost. In this paper, we develop an alternative approach based on support vector machine (SVM) and k-means, where k-means is used to reduce the SVM training set size by identifying only the representative subset of the original dataset for the SVM training. The resulting scheme outperforms individual k-means and SVM classifiers and shows competitive performance to the state-of-the-art HMM-based NALM method with up to 45 times lower execution time (including training and testing).","PeriodicalId":166543,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125836875","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: 33

Remote power system stabilizer tuning using synchrophasor data 使用同步相量数据的远程电力系统稳定器调谐

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-01 DOI: 10.1109/CIASG.2014.7011565

Paranietharan Arunagirinathan, H. A. Abdelsalam, G. Venayagamoorthy

引用次数: 12

Performance of a smart microgrid with battery energy storage system's size and state of charge 电池储能系统规模和充电状态对智能微电网性能的影响

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-01 DOI: 10.1109/CIASG.2014.7127250

A. Ahmadi, G. Venayagamoorthy, Ratnesh K. Sharma

{"title":"Performance of a smart microgrid with battery energy storage system's size and state of charge","authors":"A. Ahmadi, G. Venayagamoorthy, Ratnesh K. Sharma","doi":"10.1109/CIASG.2014.7127250","DOIUrl":"https://doi.org/10.1109/CIASG.2014.7127250","url":null,"abstract":"A mini-grid with various distributed energy technologies such as micro-turbine, micro-hydro, wind, solar, and biomass is known as microgrid. A microgrid can either be connected to the main grid or operate stand-alone. Due to variable nature of renewable resources such wind and solar plants, energy storage becomes necessary to maintain reliability of power supply to critical loads if high level of wind and solar power penetration is to be maximized. Moreover, advanced energy management systems are critical to make intelligent decisions that minimize power outage to critical loads, and maximize the utilization of renewable sources of energy. The primary contribution of this paper is to investigate the impact of size and state of charge (SOC) of a battery energy storage system (BESS) for a given microgrid with dynamic energy management systems (DEMS). Results are presented to show the relative performance of two types of DEMS for a microgrid with different BESS size and initial SOC. The performance of an intelligent DEMS developed using an adaptive critic designs approach is compared with of a DEMS developed using a decision tree based approach.","PeriodicalId":166543,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125667265","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: 14

A learning algorithm and system approach to address exceptional events in domestic consumption management 解决国内消费管理异常事件的学习算法和系统方法

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-01 DOI: 10.1109/CIASG.2014.7011564

L. Gomes, F. Fernandes, Z. Vale, P. Faria, C. Ramos

引用次数: 3

A Kalman filtering approach to the detection of option mispricing in electric power markets 基于卡尔曼滤波的电力市场期权错误定价检测

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-01 DOI: 10.1109/CIASG.2014.7011554

G. Rigatos

{"title":"A Kalman filtering approach to the detection of option mispricing in electric power markets","authors":"G. Rigatos","doi":"10.1109/CIASG.2014.7011554","DOIUrl":"https://doi.org/10.1109/CIASG.2014.7011554","url":null,"abstract":"Option pricing models are usually described with the use of stochastic differential equations and diffusion-type partial differential equations (e.g. Black-Scholes models). In case of electric power markets these models are complemented with integral terms which describe the effects of jumps and changes in the diffusion process and which are associated with variations in the production rates, condition of the transmission and distribution system, pay-off capability, etc. Considering the latter case, that is a partial integrodifferential equation for the option's price, a new filtering method is developed for estimating option prices variations without knowledge of initial conditions. The proposed filtering method is the so-called Derivative-free nonlinear Kalman Filter and is based on a transformation of the initial option price dynamics into a state-space model of the linear canonical form. The transformation is shown to be in accordance to differential flatness theory and finally provides a model of the option price dynamics for which state estimation is possible by applying the standard Kalman Filter recursion. Based on the provided state estimate, validation of the Black-Scholes partial integrodifferential equation can be performed and the existence of inconsistent parameters in the electricity market pricing model can be concluded.","PeriodicalId":166543,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG)","volume":"53 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132714857","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

Coordinated electric vehicle charging solutions using renewable energy sources 协调使用可再生能源的电动汽车充电解决方案

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-01 DOI: 10.1109/CIASG.2014.7011553

K. Jhala, B. Natarajan, A. Pahwa, L. Erickson

引用次数: 16

A new heuristic providing an effective initial solution for a simulated annealing approach to energy resource scheduling in smart grids 一种新的启发式算法为智能电网能源调度的模拟退火方法提供了有效的初始解

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-01 DOI: 10.1109/CIASG.2014.7011563

T. Sousa, H. Morais, R. Castro, Z. Vale

引用次数: 4

Impact of signal transmission delays on power system damping control using heuristic dynamic programming 启发式动态规划中信号传输延迟对电力系统阻尼控制的影响

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-01 DOI: 10.1109/CIASG.2014.7011567

Yufei Tang, Xiangnan Zhong, Zhen Ni, Jun Yan, Haibo He

{"title":"Impact of signal transmission delays on power system damping control using heuristic dynamic programming","authors":"Yufei Tang, Xiangnan Zhong, Zhen Ni, Jun Yan, Haibo He","doi":"10.1109/CIASG.2014.7011567","DOIUrl":"https://doi.org/10.1109/CIASG.2014.7011567","url":null,"abstract":"In this paper, the impact of signal transmission delays on static VAR compensator (SVC) based power system damping control using reinforcement learning is investigated. The SVC is used to damp low-frequency oscillation between interconnected power systems under fault conditions, where measured signals from remote areas are first collected and then transmitted to the controller as the inputs. Inevitable signal transmission delays are introduced into such design that will degrade the dynamic performance of SVC and in the worst case, cause system instability. The adopted reinforcement learning algorithm, called goal representation heuristic dynamic programming (GrHDP), is employed to design the SVC controller. Impact of signal transmission delays on the adopted controller is investigated with fully transient model based time-domain simulation in Matlab/Simulink environment. The simulation results on a four-machine two-area benchmark system with SVC demonstrate the effectiveness of the adopted algorithm on damping control and the impact of signal transmission delays.","PeriodicalId":166543,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121746025","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

LMP forecasting with prefiltered Gaussian process 预滤波高斯过程LMP预测

2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) Pub Date : 2014-12-01 DOI: 10.1109/CIASG.2014.7011555

H. Mori, K. Nakano

{"title":"LMP forecasting with prefiltered Gaussian process","authors":"H. Mori, K. Nakano","doi":"10.1109/CIASG.2014.7011555","DOIUrl":"https://doi.org/10.1109/CIASG.2014.7011555","url":null,"abstract":"In this paper, a new method is proposed for Locational Marginal Pricing (LMP) forecasting in Smart Grid. The marginal cost is required to supply electricity to incremental loads in case where a certain node increases power demands in a balanced power system. LMP plays an important role to maintain economic efficiency in power markets in a way that electricity flows from a low-cost area to high-cost one and the transmission network congestion in alleviated. The power market players are interested in maximizing the profits and minimizing the risks through selling and buying electricity. As a result, it is of importance to obtain accurate information on electricity pricing forecasting in advance so that their desire is reflected. This paper presents the Gaussian Process (GP) technique that comes from the extension of Support Vector Machine (SVM) that hierarchical Bayesian estimation is introduced to express the model parameters as the probabilistic variables. The advantage is that the model accuracy of GP is better than others. In this paper, GP is integrated with the k-means method of clustering to improve the performance of GP. Also, this paper makes use of the Mahalanobis kernel in GP rather than the Gaussian one so that GP is generalized to approximate nonlinear systems. The proposed method is successfully applied to real data of ISO New England in USA.","PeriodicalId":166543,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG)","volume":"267 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132134507","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: 1