Grid Project Research Articles

基于AHP的营改增对变电安装工程造价影响研究

营改增是我国当前重大的税制改革，在新环境下，原有的电网建设工程造价和电网企业管理不能发挥其最大作用，因而顺应营改增政策，提高电网建设工程造价管理水平成为电网企业关注的重点。本文是以电网工程造价管理为主线，以营改增前后计税变化为指导，根据AHP所建立的模型及分析结果，在实例分析的基础上对电网企业提出了工程造价管理实施建议，有助于企业在新的宏观背景下把握企业未来发展趋势，尽快适应营改增转型期对企业管理的要求。 Replacing business tax with VAT is a current major tax reform in China. In new circumstances, the original power grid construction project cost and the management of power grid enterprises cannot play its biggest role. Thus to comply with the policy of replacing business tax with VAT and improving the level of the power grid construction project cost management level has been the focus of attention of the power grid enterprises. This paper is based on the power grid project cost management and is guided by the change of the tax calculation. According to the results of AHP method model and the case analysis of power grid enterprises, we put forward some suggestions to implement the project cost management. It helps enterprises grasp the future development trend of construction enterprises in the context of the new macro and adapt to the objective requirements of enterprise management in the transition as soon as possible.

Research on Investment Decision Model of Distribution Grid Project Based on Transformer District

Distribution grid is the main bridge connecting the power grid enterprises with the vast number of electrical power users. The investment decision making of the distribution grid is one of the important management issues of which the Grid Corporation often faces. In this paper, based on the actual data produced from electric business system, considering the data availability and the scientific evaluation parameters of the electric grid equipment, a distribution grid equipment evaluation system is set up, and the cluster analysis method is used to classify the transformer district and get the objective classification results. On the basis of this, the priority of equipment investment of transformer district in different classifications is given, which provides decision support for the equipment investment of the electric grid corporation.

A finite-element coarse-grid projection method for incompressible flow simulations

Coarse grid projection (CGP) methodology is a novel multigrid method for systems involving decoupled nonlinear evolution equations and linear elliptic Poisson equations. The nonlinear equations are solved on a fine grid and the linear equations are solved on a corresponding coarsened grid. Mapping operators execute data transfer between the grids. The CGP framework is constructed upon spatial and temporal discretization schemes. This framework has been established for finite volume/difference discretizations as well as explicit time integration methods. In this article we present for the first time a version of CGP for finite element discretizations, which uses a semi-implicit time integration scheme. The mapping functions correspond to the finite-element shape functions. With the novel data structure introduced, the mapping computational cost becomes insignificant. We apply CGP to pressure-correction schemes used for the incompressible Navier-Stokes flow computations. This version is validated on standard test cases with realistic boundary conditions using unstructured triangular meshes. We also pioneer investigations of the effects of CGP on the accuracy of the pressure field. It is found that although CGP reduces the pressure field accuracy, it preserves the accuracy of the pressure gradient and thus the velocity field, while achieving speedup factors ranging from approximately 2 to 30. The minimum speedup occurs for velocity Dirichlet boundary conditions, while the maximum speedup occurs for open boundary conditions.

Low-power instrument transformer-based MV automation: lessons learned and future applications

In this study, the authors share the experience they have gained in the field of medium-voltage (MV) distribution automation, with particular focus on the use of low-power instrument transformers (a.k.a. sensors) and their implications from the perspective of safety, installation procedures, accuracy, standardisation, interoperability etc. The study presents the key learnings from several small pilots and one massive project, IBERDROLA's STAR project, a smart grid project aiming to provide automation solutions for a MV network of 90,000 secondary substations which is entering its final stage after 6 years.

Dashboard and smartphone application to support operation and planning of electric distribution systems

This study aims to describe a dashboard that presents relevant information to the operation, maintenance and planning of subtransmission systems, underground distribution systems and aerial distribution systems, developed as part of the ‘Smart Grid Project’ of Brazilian utility AES Eletropaulo. In addition, it was developed an application for smartphones containing information that were considered important to be viewed remotely by operators and field teams.

Behaviour of PV inverters during islanding of a district

Islanding is the most innovative use case of the Nice Grid project led by Enedis. It involves the disconnection of a low-voltage district for a limited duration and its supply only by energy storage and photovoltaic (PV) generation. Five hours of islanding have been achieved in October 2015. Some results of these experiments are displayed. This study also introduces the new European smart-grid project INTERFLEX, which is supposed to go further the Nice Grid experiments. An islanding of two islands in the South-East of France is expected. Principles of the expected experiments are explained.

Software-driven active customer interface for DER integration

The Nobel Grid project is developing information technology to integrate and fully utilise flexibility potentials of demand response and end-customer operated distributed energy resources (DERs) in the electric energy system. As key part of an according technical solution, the authors develop the ‘smart meter extension (SMX)’ for rapid development and deployment of new functionalities at end-customer premises. The document at hand reports the project results achieved so far. After summarising their approach, they introduce the Nobel Grid architecture. They then detail the architecture focusing on the SMX. Finally, they show how the SMX can be used to implement two example smart grid functions, highlighting the SMX's capabilities as a modular interface for software-driven DER integration.

Future sign detection in smart grids through text mining

Policymakers and stakeholders need insights into smart grid issues related to the technologies, markets and so on to drive more effective smart grid projects. A comprehensive examination of relevant references would be helpful in this regard, but extensive time and efforts are required to obtain the insights. We seek to explore which smart grid issues have been highlighted and will emerge in the future using the future sign searching technique through text mining. As a result, keywords such as ‘gateway,’ ‘university,’ ‘oil’ and so on were highlighted as weak signals. Furthermore, this study helps to promote the development of scientific research in future sign analysis through text mining by presenting some challenges in the research methodology. Especially, we need to examine which weak signals have the potential to develop into strong signals in further research.

Dynamic characteristics of smart grid technology acceptance

Smart grid projects are being actively promoted globally for green growth. There is the consumer acceptance among factors that make smart grid business effective. Many studies have emphasized the importance of smart grid consumer acceptance and examined the factors that influence the acceptance. However, almost studies did not observe how smart grid acceptance changes from a dynamic perspective. This study aims to contribute to smart grid acceptance research by examining dynamic characteristics related to the acceptance. As a result of this study, we found that it is important to manage the risk of smart grids and we should try to minimize the gap between expectation and satisfaction. Also, we should maintain the balance of benefits and reductions of smart grid technologies.

A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring

Combination of different satellite data will provide increased opportunities for more frequent cloud-free surface observations due to variable cloud cover at the different satellite overpass times and dates. Satellite data from the polar-orbiting Landsat-8 (launched 2013), Sentinel-2A (launched 2015) and Sentinel-2B (launched 2017) sensors offer 10 m to 30 m multi-spectral global coverage. Together, they advance the virtual constellation paradigm for mid-resolution land imaging. In this study, a global analysis of Landsat-8, Sentinel-2A and Sentinel-2B metadata obtained from the committee on Earth Observation Satellite (CEOS) Visualization Environment (COVE) tool for 2016 is presented. A global equal area projection grid defined every 0.05° is used considering each sensor and combined together. Histograms, maps and global summary statistics of the temporal revisit intervals (minimum, mean, and maximum) and the number of observations are reported. The temporal observation frequency improvements afforded by sensor combination are shown to be significant. In particular, considering Landsat-8, Sentinel-2A, and Sentinel-2B together will provide a global median average revisit interval of 2.9 days, and, over a year, a global median minimum revisit interval of 14 min (±1 min) and maximum revisit interval of 7.0 days.

Deducing Energy Consumer Behavior from Smart Meter Data

The ongoing upgrade of electricity meters to smart ones has opened a new market of intelligent services to analyze the recorded meter data. This paper introduces an open architecture and a unified framework for deducing user behavior from its smart main electricity meter data and presenting the results in a natural language. The framework allows a fast exploration and integration of a variety of machine learning algorithms combined with data recovery mechanisms for improving the recognition’s accuracy. Consequently, the framework generates natural language reports of the user’s behavior from the recognized home appliances. The framework uses open standard interfaces for exchanging data. The framework has been validated through comprehensive experiments that are related to an European Smart Grid project.

When social practices meet smart grids: Flexibility, grid management, and domestic consumption in The Netherlands

This article seeks to analyse recent shifts in goals concerning domestic energy uses. Drawing on two Dutch smart grid projects, we observe that in the smart grid transition the balancing of (renewable) supply and demand in energy grids becomes the key priority of grid managers. This shift becomes translated at the household level through so called ‘teleoaffective structures’ of energy practices which motivate and direct the behaviour of householders towards flexible timing-of-demand. New grid objectives are codified in the rules of social practice concerning the use of flexibility instruments (notably time-of-day pricing) and are materialized in monitoring devices, smart appliances, and energy storage. We investigated which domestic practices are most open for flexible timing-of-use. Cleaning practices were found to be most suitable for demand-side response, whereas practices implied in ambiance regulation, leisure, cooking and eating, align only with some flexibility instruments. Next, an analytical focus on linkages between social practices was used to specify opportunities and barriers to sustainable domestic energy consumption. In the concluding section, we argue that householder engagement with sustainability goals should be safeguarded from the flexibility instruments, goals and strategies that seem to turn this engagement into grid management performed for financial benefits only.

Metodología para el análisis de costos y beneficios de proyectos Smart Grid y su aplicación en un piloto de medición inteligente de energía (AMI)

The aim of this paper is to present a methodological approach to obtain the cost-benefit impact at environmental and socioeconomic level, related to the integration of Advanced Measurement Infrastructure into utilities and their residential customers. The methodology used to quantify the costs and benefits of implementing such technology was established by the European Union and adjusted to the local context. It is worth highlighting that this methodology can be used to evaluate any kind of Smart Grid project. The socioeconomic benefits estimated in this research were related to job creation, energy consumption decrease, reduction of non-technical losses, and the reduction of CO2 emissions. An economic analysis using the net present value is presented here for assessing the impact caused by smart metering implementation.

A short-term traffic prediction model in the vehicular cyber–physical systems

The advances in Cyber–Physical Systems (CPS), vehicular networks and Intelligent Transportation System (ITS) boost a growing interest in the design, development and deployment of Vehicular Cyber–Physical Systems (VCPS) for some emerging applications. As one of the key application for realizing traffic guidance, the traffic prediction could provide better route planning for people and accuracy decision basis for traffic managements. In practice, short-term traffic information has the characteristics of real-time, incompleteness, non-linearity and non-stationary, and few proposed methods could successfully implement this forecasting. In this paper, we proposed a fuzzy Markov prediction model which can estimate the short-term traffic conditions in VCPS in urban environment. First, we selected a real-time GPS dataset in the Shanghai Transport Grid Project as our data source for traffic prediction and pre-process this raw dataset to make it consistent with the practical case. Next, we combine the fuzzy theory with Markov progress in the prediction model, and use the continuous three-step average method to reduce the errors caused by the one-step transition. Finally, we choose the speed and traffic flow to express the metrics of traffic state and use the fuzzy reasoning rules to give out the determined traffic state. The simulation results show that our proposed model can be precisely used for the short-term traffic prediction in urban environment.

Research on the Investment and Operation Model of Distributed Energy Industry

With the development of the new generation of distributed technology and the comprehensive promotion of the smart grid project, the distributed energy will realize the large-scale grid connection. However, the current investment model of distributed energy market is still inadequate. In order to promote the development of distributed energy industry this paper systematically analyzed the participants of distributed energy market based on the research of distributed energy development status and related development models. At the same time, combined with China's national conditions, from the two stages of investment and operation of distributed energy development, this paper summarized and developed the design of distributed energy development models. At last, this paper concluded that China's distributed energy industry development opportunities have come, and the government should actively promote the marketization of energy supply.

C-3 Application of Horizontal Cooperation Platform in P2M to Smart Grid Project

C-3 Application of Horizontal Cooperation Platform in P2M to Smart Grid Project

Fuzzy based clustering of smart meter data using real power and THD patterns

In most of the electric utilities of the world, the classification of customer is based on the amount and purpose of the load sanctioned. Classification of customer based on the duration of energy usage is possible by smart meters. With the smart meter data, time of energy consumption, daily usage pattern and actual volume of energy usage offers better insight of customer consumption pattern. Clustering is the process forming groups( or cluster) based on the similarity among the data. By applying clustering methods various groups of customer can be formed based on their consumption pattern. So far clustering is based on amount of real power sanctioned for the customers but due to increased addition of renewable energy and non linear loads to the utility grid raises issues like voltage fluctuation, harmonic resonance and Total Harmonic Distortion(THD). In this paper, K-means method is used for the clustering the real power and THD load data of smart meter independently. Fuzzy logic technique is used to illustrate the combined effectiveness of real power and THD data for clustering customers and demonstrated with the real time smart grid project.

Smooth Integration of Gansu Wind Farm into the Grid Using the Stator Flux-Oriented Vector Method and Fuzzy Logic Control

Gansu province wind energy potential in China is around 237 GW. According to the schedule, 20 GW wind energy is connected to the grid by 2020. However, there is a chance of instability in the presence of big intermittency. To integrate this huge generated wind power, a reliable control strategy is required. The proposed portable power plant (PPP) energy storage system is fully compatible with a smart grid and mitigates the dispatching complexity and provides better designing and implementation of Gansu wind farm in China. In a two-way power flow, when the generation is bigger than the load demand, the additional power is stored in the PPP for future use, and when the demand is higher than the total generation, the stored power is applied to feed the grid. Also the PPP can charge the grid during peak demand periods or when the local network is stressed. An intelligent controller is linked with PPP to monitor the power flow. The stator flux-oriented vector method is used for modeling the system. Then, a fuzzy controller is applied to adjust the modulation index of PWM inverter and also uses energy storage units to stabilize the output of the power plant. Real field data of the Gansu wind farm with 24-h horizon have been applied on the proposed system. The results show the high performance of the fuzzy-based PPP system in the presence of fluctuations and increase the efficiency of the power system by storing energy through PPP. With a large-scale plan for application of smart grid and renewable energy sources in China, this paper introduces an essential step of this vision to provide a feasible framework for future large-scale smart grid projects in China as well as stable operation of Gansu wind farm as the biggest wind farm in mainland when it is completed.

Smart grids and households: how are household consumers represented in experimental projects?

ABSTRACTThis study contributes a comparative analysis of 11 Danish smart grid experimental projects with household involvement. The analysis describes the scripts for the future smart grid interaction investigated in the examined projects, the approaches to user representation, and the project findings concerning consumers and smart grids. Three main dimensions of the scripts are identified and discussed: economic incentives, automation, and information/visualisation. The methods employed for the development of user representations are primarily technical and techno-economic. While our analysis confirms previous findings that economic rationales and automation are central elements of smart grid scripts, the analysis also shows that there is considerable variation in the details of the scripts investigated. Our findings suggest that it may be useful for future smart grid projects to be more systematic and explicit in the analysis of household user perspectives and may consider a broader set of methods in this regard.

Research on Interpretation Structure Model of Influence Factors on the Price of Power Grid Project Equipment

The influence factors on the price of power grid project equipment are complex, as well as the impact of factors on the price, which make it difficult to predict the price of equipment. Consequently, it is necessary to clarify the relationships among the factors. Based on the interpretative structural model (ISM), this paper sorts out the relationship among the factors and constructs the hierarchical structure model of influencing factors. Finally, the deep influence factors, the shallow influence factors and the surface influence factors of price are summarized.