Fang Yuan Xu

Artificial neural network for load forecasting in smart grid

It is an irresistible trend of the electric power improvement for developing the smart grid, which applies a large amount of new technologies in power generation, transmission, distribution and utilization to achieve optimization of the power configuration and energy saving. As one of the key links to make a grid smarter, load forecast plays a significant role in planning and operation in power system. Many ways such as Expert Systems, Grey System Theory, and Artificial Neural Network (ANN) and so on are employed into load forecast to do the simulation. This paper intends to illustrate the representation of the ANN applied in load forecast based on practical situation in Ontario Province, Canada.

Impact of smart metering on energy efficiency

Smart metering is a subject that attracts much more attention. Smart metering is obtaining many benefits in a lot of aspects. Many smart metering projects are going on many countries, such as UK, Italy, the USA and other countries. Some planning studies list in this paper show that smart metering is technically feasible. Many benefits are available, especially on improving the energy efficiency. The future smart metering system will rely on policies and governmental fiscal stimuli. However cyber security requirement will be an issue. Smart metering deserves a big attention.

Novel Active Time-Based Demand Response for Industrial Consumers in Smart Grid

Time-based demand response (DR) enables industrial consumers to transfer their power consumption by following daily price curve. However, general time-based DR is basically a passive tariff. Utilities usually create general pricing tariff to the whole industrial consumers at the same voltage connection level. Under this situation, consumption transformation of all possible industries occurs together. It may reduce the effect of load characteristics improvement. This paper introduces a new pricing framework named active time-based (ATB) DR to overcome this weak point. Under this tariff, consumers are classified in details. Utilities select target consumers, communicate with them actively, and provide a specified price curve for the industries covered by target consumer group. With a practical survey, this paper implements ATB with the best behavioral scheme (BBS) model and industrial consumer attitude model. This paper includes a numerical case study on cement manufacturing for further analysis. Data acquisition, BBS simulation, consumer attitude estimation, and an investigation on electricity pricing are covered by this case study.

Investigation on July 2012 Indian blackout

Twice Indian blackouts occurred at the end of July in 2012 left over 600 million of people in the dark for several hours. In these two-day, Indian grid disturbances were regarded as the most serious and large-scale blackout in the world in history. A report has been generated by the enquiry committee which was organized by the Ministry of Power, Government of India, to investigate the factors which led to the initiation of the grid disturbance. Recommendations were also generated by the committee in order to provide the plan for Indian grid enhancement. Further to the recommendations by Enquiry Committee, this paper will give further suggestions to minimize blackouts in future. An insight into decision support requirement for power network operation will be made.

Standards, policies and case studies in smart metering

As an important part of Smart Grid, smart metering attracts more and more attention all over the world. It is the way for energy consumer to sense the benefit of smart grid directly. Facing the great demand of smart metering, governments and company are busy with establishing policies and standards for smart metering deployment. This paper enumerates the standards and policies set up by governments or organizations. Also case study on situation of the smart metering deployment all around the world is provided.

A RBF network for short — Term Load forecast on microgrid

Short — term Load forecast significantly influences the management and pricing of power system. This paper presents a Radial Basis Function network based forecasting system to achieve this ability. A mean square error based training algorithm is applied and analysis is given on the Radial Basis Function selection.

Extending version of Graphical User Interface in Neural Network Toolbox of MATLAB and engineering applications

This paper proposes an extending version of Graphical User Interface in Neural Network Toolbox of MATLAB 7.1 which releases the limit of setting more layers in the feedforward network creating. Users can set up a feedforward network with any architecture. Based on this interface two simple applications are applied, namely, a simple voting system design and 3-phase generator output detector design. Simple voting system is based on feedforward network and the 3-phase generator output detector is designed on Radial Basis Network (RBF). These examples show how to design the neural network in applications.

Scope design, charateristics and functionalities of Smart Grid

Facing grimmer power utilization in the future, a Smart Grid construction with more strength and higher efficiency in power utilization is on schedule worldwide. Due to a large amount of new technologies and service will be raised, updated or replaced in Smart Grid from traditional power grid, a framework of the whole Smart Grid structure become necessary for the huge costly deployment, as well as the characteristics and functionalities. This paper introduces one of the Smart Grid scope design with introducing its features and the basic technologies.

A Novel Load Shedding Strategy Combining Undervoltage and Underfrequency with Considering of High Penetration of Wind Energy

Low carbon emission is one of the main targets for smart grid planning. To achieve this goal, intermittent energies such as wind and solar are integrated to the power systems increasingly. However, this may create huge challenges to the power system operators for balancing the generation and demand at all times and guaranteeing the system reliability at the same time. With high penetration of renewable energies, power system operators are compelled to curtail the loads when the power system cannot rely on power from renewable energies continuously due to strong dependence on the environment. As an important defense to protect the power network from collapsing and to keep the system integrating, load shedding has been designed and proposed for decades. However, most of the shedding schemes consider the load increasing instead of lack of generation. This paper applies a load shedding scheme with considering both voltage and frequency changes when the generation is inadequate since the power system cannot obtain the expected renewable generation and renewable energies are highly penetrated into the grid.

Agent-Based Modeling and Neural Network for Residential Customer Demand Response

In this paper, both bottom-up and top-down models for demand response with agent-base approach and neural networks have been investigated. Simulations have been carried out with practical load data from the UK and Canada. Results show that each approach has its advantages and disadvantages depending on difference application scenarios.