Smart Grid Platform Research Articles

A multi‐version CIM‐based database platform for smart grid

In the smart grid area, the Common Information Model (CIM) for energy management systems is widely used. CIM is developed in a Unified Modeling Language (UML) and its entire content is maintained with one version by the IEC TC57 committee. There are officially four versions of CIM so far. For each CIM entity modeled in UML, such as a class or an attribute, there is no version information by default. This makes it extremely difficult to precisely identify a CIM entity in an application. Consequently, any application utilizing CIM faces an obstacle in maintenance and in exchange of data with other parties that may be utilizing different versions of CIM. Furthermore, CIM in UML format is unsuitable for managing a large number of instances. In order to improve the above‐mentioned compatibility and usability problem of CIM, in this paper we introduce a new International Standard, IEC 62656‐3. Through this standard, CIM can be decomposed into a set of tabular data each of which has an explicit version and can be described with a spreadsheet. This format is called Parcellized‐CIM. Based on Parcellized‐CIM, a commercial database platform, Parcimoser, is developed and applied in the engineering of smart grids. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

A Dynamic Secret-Based Encryption Scheme for Smart Grid Wireless Communication

Integrating information network into power system is the key for realizing the vision of smart grid, but also introduces many security problems. Wireless communication offers the benefits of low cost, rapid deployment, shared communication medium, and mobility; at the same time, it causes many security and privacy challenges. In this paper, the concept of dynamic secret is applied to design an encryption scheme for smart grid wireless communication. Between two parties of communication, the previous packets are coded as retransmission sequence, where retransmitted packet is marked as “1” and the other is marked as “0.” During the communication, the retransmission sequence is generated at both sides to update the dynamic encryption key. Any missing or misjudging in retransmission sequence would prevent the adversary from achieving the keys. In our experiments, a smart grid platform is built, employing the ZigBee protocol for wireless communication. And a dynamic secret-based encryption demo system is designed based on this platform. The experiment results show that the retransmission and packet loss in ZigBee communication are inevitable and unpredictable, and it is impossible for the adversary to track the updating of the dynamic encryption key.

Multiagent System Architecture for Short-term Operation of Integrated Microgrids

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid's internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

No peeking: privacy-preserving demand response system in smart grids

Demand response (DR) programs are widely used to balance the supply and demand of electricity in a smart grid. This results in a reliable electric power system. Unfortunately, privacy violation becomes a pressing challenge that drastically affects the DR programs. Power usage and operational data can be abused to infer personal information of customers. Without a well-designed privacy preservation mechanism, adversaries can capture, model and divulge customers' behaviour and activities. In this paper, we first investigate the natures of privacy leakages and explore potential privacy threat models. After that, we design and implement a new protocol named privacy-preserving demand response based on the attributed-based encryption, and formally prove its validity. To demonstrate its viability, the protocol is adopted in several types of DR programs on an emulated smart grid platform. Experimental results show substantially lighter overheads while formidable privacy challenges are addressed.

Special Issue on Challenges and Opportunities in the 21st Century Energy Infrastructure

Special Issue on Challenges and Opportunities in the 21st Century Energy Infrastructure

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players' behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles' batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Investment Evaluation System Development Based on Unified Information Platform for Future Smart Grid

With the aim of strengthening the construction of smart power grid, large investment will be put into power grid of China. Investment evaluation of power grid is necessary in this situation particularly in the light of escalating costs and financing cost. This paper presents the development of Investment Evaluation System with the help of Unified Information Platform to enhance the awareness the technical, economic and social benefits of power grid investment. The overall work flow of Investment Evaluation System and its important aspects, including indicator system, normalization, weighting factor and comprehensive evaluation are presented. The basic architecture of Unified Information Platform and the realization of data exchange are illustrated. Finally system realization and hardware deployment are provided.

Cooperative fuzzy controllers for autonomous voltage regulation in Smart Grids

The large-scale deployment of the Smart Grid paradigm will support the evolution of conventional electrical power systems toward active, flexible and self-healing web energy networks composed of distributed and cooperative energy resources. In a Smart Grid platform, the optimal coordination of distributed voltage controllers is one of the main issues to address. In this field, the application of traditional hierarchical control paradigms has some disadvantages that could hinder their application in Smart Grids where the constant growth of grid complexity and the need for massive pervasion of distribution generation systems require more scalable, more flexible control and regulation paradigms. To try and overcome these challenges, this paper proposes the concept of a decentralized non-hierarchal voltage regulation architecture based on intelligent and cooperative smart entities. The distributed voltage controllers employ traditional sensors to acquire local bus variables and mutually coupled oscillators to assess the main variables that characterize the operation of the global Smart Grid. These variables are then amalgamated by a fuzzy inference system in order to identify proper control actions aimed at improving the grid voltage profile and reducing power losses.