Applications of Grid Computing in Power Systems - CiteSeerX

Applications of Grid Computing in Power Systems Mohsin Ali1 Zhao Yang Dong1 Xue Li1 Pei Zhang2 1 School of Information Technology and Electrical Engineering The University of Queensland, Brisbane, QLD 4072, Australia {mohsin, zdong, xueli}@itee.uq.edu.au 2 EPRI, 3412 Hillview Ave. Palo Alto, CA 94304-1395, USA ABSTRACT Grid computing is an infrastructure that involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations [1]. Currently, Grid computing is effectively used in scientific research, oil and gas fields, banking and education. It has provided significant contribution in these areas. In this paper, we introduce the fundamentals and applications of Grid computing in order to provide more open access and more efficient & effective computing services to meet the increasing needs of the power industry, especially in the context of a competitive electricity market. Power system applications developed on the Grid computing can provide real time information for the whole system. Grid computing can provide services in power generation, transmission distribution and in its marketing [2]. It can also provide efficient and effective services in the power system monitoring, scheduling, fault detection, transmission congestion management, planning, and electricity market analysis such as forecasting. In this paper, we will give detailed analysis of Grid computing in the context of power system applications. We will also investigate the existing Grid computing and similar computing applications in practice, and propose a general framework of Grid computing in power systems application approach. 1

INTRODUCTION

Power systems consist of generation, transmission and distribution systems. In many countries, electricity markets are formed with the aim to achieve higher efficiency and reduced electricity prices through competition. The information involved in an electricity market is huge seeing the needs for market operation and planning. In an electricity market, the information owned by a single organization can also be relevant to many other organizations as well. If such information is not commercially confidential, the sharing of such information with other participants will improve the overall efficiency in the market. We know that future planning for power system expansion requires a combine effort of many companies, who need to collaborate to achieve this goal. Some efforts have been made so far to share the market information in the form of Open Access Same-time Information System (OASIS) [7]. Along with data sharing there is also a need of high computation power for processing of such huge volume of data. It was

easy in regulated market but with the deregulation, it has become more complex and difficult. This requires more computation power for providing various solutions for power industry in the fields of generation, transmission and distribution systems. Also there is a need of high computing power and large size of memory for processing the data related to planning, reliability analysis and system security assessment. There are many applications in power system, which need large processing. These applications can be developed by dividing the main task in to sub tasks which can run independently and distributed across the Grid. The best example of such applications is Monte Carlo simulation [14]. In many utility companies and system operators, their computing resources normally run at full capacity within themselves. There is an increasing need for higher computing efficiency with the limited resources available. Grid Computing provides the answers to these issues. Motivated by popularity and reliability of the power grid, computer scientists in the mid 90s started designing and developing new infrastructure; computational grids for network computing [14]. Computational Grids are now used in many fields; helping the scientists working on large scale data and intensive applications those require more computing power and resources. This need for greater computing power was the reason for emergence of Grid Computing. Computational Grid is very much similar to electrical Grid other than the nature of their job [14]. Both have heterogeneous resources, like in electrical grid, these are thermal hydro, wind, solar and nuclear. While in computational grid, they are workstations and clusters of different machines running different operating systems [14]. Both have a network for connecting different areas. For this purpose electrical grid has transmission lines while computational grid has Internet [14]. In Grid computing the use of multiple computers can deliver the results faster and more accurate by processing voluminous of data. Other than sharing and distributing data, Computing Grid offers more powerful services like science portals, distributed computing, large scale data analysis and collaborative work [9]. It has been deployed in different form in many fields [10] due to its processing power, efficiency and availability of resources. This paper gives a brief overview of the possible use of Grid computing in power systems. For this purpose the rest of the paper is organized as follows. In section 2, we review the Grid computing technology, its working criteria and its advantages. In section 3, we discuss its

applicability in the field of power engineering and we conclude in section 4. 2

INTRODUCTION TO GRID COMPUTING

Grid Computing can be defined as a form of parallel and distributed computing that involves coordination and sharing of computing, application, data storage and network resources across dynamic and geographically distributed organizations [13]. Grid is a type of parallel and distributed system that enables the sharing, selection, and aggregation of geographically distributed "autonomous" resources dynamically at runtime depending on their availability, capability, performance, cost, and user’s quality-of-service requirements. It is a back-bone infrastructure for web services. The main advantage of Grid computing is that it exploits the unused processing cycle of the CPUs connected in network and gives performance more than mainframe and super-computers. Grid Computing is analogous to the electric grid. The only difference is that instead of consuming electricity from grid we are consuming the wasted computing cycles of computers on a global scale. A key objective to using Grid technologies is to allow resources at multiple sites to be combined with little a priori coordination among the sites themselves. This integration creates a virtual organization; where in a number of mutually distrustful participants with varying degrees of prior relationship; want to share resources in order to perform some task [1]. Grid computing has expanded greatly in last five years. There are a few pioneering projects such as Globus, Conder, Legion and Unicore provided Grid solutions. Grid computing provides many advantages depending upon the nature of the requirement. It

provides high computing power, sharing of resources across the network among many computers and access to the remote and distributed data. It provides the interface to collect and submit the information from the remote location and diversified resources. It provides high level reliability in communication and different levels of security between the nodes. It provides many services like remote process management, remote resource allocation, task distribution and scheduling services. Its major use is in scientific application where distributed resource allocation and high performance are required. Grid projects have been developed in many areas like Earth study, Bio-medical, Physics Astronomy, Engineering and multimedia. 2.1

WORKING OF GRID COMPUTING

In Computing Grid all the intended Local Area Networks (LAN) are connected to each other through Internet. If any client needs to perform some task on the Grid, first it sends query to domain in order to get information of the Master Server. Domain gives information of master server. Then client sends the request to the master server to perform the task. Master server divides the tasks into subtasks and distributes them to all nodes across the Internet. Local servers at each node receive the assigned task, find the available systems on the LAN and distribute the assigned task to available systems. Local PCs perform the task and send their individual results to local servers. Local servers merge the collected results and send back to master server. Master server combines the gathered results and then either sends to the client or the intended database.

Figure 1: Working of Computing Grid

2.2

ADVANTAGES AND FUNCTIONALITIES OF GRID COMPUTING

Grid Computing provides many advantages to its users. A few of them are summarised as follows.

2.2.1

PARALLEL PROCESSING

Parallel processing is one of the most attractive features of Grid computing which increase the CPU processing capacity as a whole. In grid more computation power is available with parallel processing capability. In addition to pure scientific needs, such computing power is driving a new

evolution in industries such as the bio-medical field, financial modelling, oil exploration, motion picture animation, and many others.

unusually busy due to an unusual peak in activity. The job in question could be run on an idle machine elsewhere on the grid. As discussed in previous point, organizations from different part of the world are connected to each other on the Grid. They can take advantage of time zone and random diversity and in peak hours they can even use the idle resource of different time zones across the world [1]. 2.2.4

Figure 2: Master server divides the task into sub tasks, and distribute them to process parallel on the nodes and then assemble the results to generate answer. [8]

2.2.2

VIRTUAL ORGANIZATIONS FOR COLLABORATION

The users of the grid can form virtual organization across the world for their common interest [1]. Each may have different rules and regulation for their own organization but they can be gathered for their collaborative work. These virtual organizations can share their resources collectively as a larger grid. Sharing is not limited to files, but also includes many other resources, such as equipment, software, services, licenses, and others. These resources are “virtualized” to give them a more uniform interoperability among heterogeneous grid participants [8].

GRID SERVICES

There are many factors to consider in developing any application grid-enabled. All applications are required to expose as services in order to run on Grid [8]. But for this, not all applications can be transformed to run in parallel on a grid. Also there are no practical tools for transforming any application to exploit the parallel capabilities of a grid. There are some practical tools that skilled application designers can use to write a parallel Grid based application. However, automatic transformation of applications is a science in its infancy. This can be a difficult job and often requires top mathematics and programming talents, if it is even possible in a given situation. Communication overhead is another important factor in Grid computing, which can affect the Grid performance. On the LAN this is almost negligible. On the other hand, if Grid is implemented on WAN or Internet, then communication overhead may degrade the overall performance [19]. Most of new Grid computing users are frighten in using this technology due to this communication overhead. Now with the advancement in technology, the bandwidth of communication media is increasing day by day which certainly reduces this effect [16]. While on the other hand, several methods and algorithms are used to reduce this overhead like parallel job scheduling [16], asynchronous communication [17], extension of ProActive Groups [18] and data compression. 2.2.5 ACCESS TO SHARED RESOURCES In addition to CPU and storage resources, a Grid can provide access to the number of additional shared resources [1] and to special equipment, software, licenses, and other services [8]. For example, if a user needs some data transfer on the Internet then it can share more the one connection with the internet to increase the total band width. Similarly if a user wants to print any large document, he can use more than one printer in order to decrease printing time.

Figure 3: Organization’s collaboration forms the virtual organizations.

2.2.3

USING OF IDLE RESOURCES

Mostly in any organization we use the processing cycles of every computer at their peak for 8 hours while rest of the day they remain idle. On the other hand some of the systems are doing heavy processing. Their job can be shifted to other idle systems. The easiest use of Grid computing is to run the existing applications on different machines. The machine on which the application normally runs might be

2.2.6

LOAD BALANCING AND MANAGEMENT

Grid computing can offer a load balancing effect by scheduling grid jobs for Grid based applications on machines having low utilization. This feature can be very useful for handling occasional peak loads of activity in any part of a large organization [8]. This can happen in two ways: The unexpected load can be shifted to comparatively idle machines in the Grid or if the Grid is already fully utilized, the lowest priority work being performed on the Grid can be temporarily suspended or even cancelled and performed again later to make room for the higher priority work.

The Grid offers priority management among different projects. In the past, each project may have been responsible for its own IT resources and the expenses associated with it. Often this hardware might be underutilized while another project finds itself in trouble, needing more resources due to unexpected events. With the larger view that a Grid can offer, it becomes easier to control and manage such situations. 2.2.7

RELIABILITY OF THE COMPUTING GRID

Large computing systems use expensive hardware to increase reliability. They use build-in redundant circuits and contain much complex computational logic to achieve graceful recovery from an assortment of hardware failures. Power supplies and cooling systems are used. The systems are operated on special power sources that can start generators if utility power is interrupted. All of this builds a reliable system, but at a great cost, due to the duplication of high-reliability components. Grid is one of the alternative approaches for reliability that relies more on software technology rather than expensive hardware [8]. The systems in a grid can be relatively inexpensive and geographically dispersed. Thus, if there is a power or other kind of failure at one location, the other parts of the grid are not likely to be affected. In critical, real-time situations, multiple copies of the important jobs can be run on different machines throughout the grid. Their results can be checked for any kind of inconsistency, such as computer failures, data corruption, or tampering. 2.2.8

SECURITY ISSUES OF THE COMPUTING GRID

Security issue becomes very important when resources and data are shared in huge amount within the organizations. Data flowing across the different nodes of the grid is very much valuable for its owner, so it should go only to those who are intended to receive it. And therefore, there is enormous concern about data and application security both during its flow across the Internet. The first concern is mainly because it is possible for someone to tap your data and possibly modify it on its path. The second concern is that when you use others computers in the grid, it is possible that the owners of those computers may read your data. These can be addressed by sophisticated encryption techniques both during transmission and also during their representation/storage on external resources. We can use SSL (Secure Sockets Layer) encryption system in order to authenticate the users. The Grid Security Infrastructure (GSI) [15] uses SSL certificates for authentication. Operating systems already provide means to control who is allowed to access data. For example, on UNIX systems there is a support to set permissions such as only the owner of resource is permitted to access data. 3

APPLICATION IN POWER SYSTEMS

Evolution of electric power systems has developed through history from isolated plants to individual systems, interregional, and finally international

connections [6]. Grid computing can provide new solution for the power generation, transmission, distribution and trading as well which are considered the fundamental components of a power system. Grid Computing is the next IT revolution [2, 4]. The future power system will involve many participants: generator owners and operators, generator maintenance providers, generation aggregators, transmission network operators, distribution network operators, load managers, energy market makers, energy supplier companies, metering companies, energy customers, regulators and governments [2]. Grid computing can provide an integrated environment for all these participants to either compete or co-operate with each other in power system operations. Grid computing can be involve in all fields in which computers are involved, and these fields can be related to communications, analysis and organizational decision making. Some areas of power systems are highlighted in following to explain the use of Grid computing. 3.1

MONITORING AND CONTROL

In the coming years the power system will have large number of small generators rather than small number of large generators [2]. It will be necessary to monitor their generation at distribution level. Grid computing can provide the information about the total production of power from the large number of generators and also can help in its scheduling in remote areas. It is necessary to monitor them in real time situation because a small disturbances in system can result in black out. This monitoring system can also be helpful in monitoring the generation status for scheduling the maintenance. 3.2

RELIABILITY AND SECURITY

Reserve margins are needed to ensure the reliability in the event of outage [5]. Many computations are required for contingencies analysis. Grid computing provides high computing power for such analysis. Also intelligent algorithms can be applied to find the alternated resources and availability to transmission media. Circuit breakers can be controlled through the Grid computing to prevent from damaging the other part of the system. It also helps in changing the tracks by using the available information about the transfer capability of transmission media. Mathematical modelling and simulations can be used to detect any disturbances which can cause undesired results in the system. Grid computing can provide an excellent platform for fast computation of very large data for simulation. There are many ways for reliability study, but they require high computations and memory resource like Monte Carlo based techniques for examining the voltage stability and load flow analysis. Grid computing provides best plat form for such simulations. Parallel and distributed computing in reliability assessment has been practiced and this is a special case of application of Grid computing in power systems.

3.3

ELECTRICITY MARKET

The Open Access Same-time Information System (OASIS) has already been implemented in USA through which small organization even the individuals can take part in electricity trading [7]. For this all companies need to be registered in-order to share their information and to know the market strength. Along with information sharing Grid computing can also provide a workflow system for the electricity market in-order to speed-up the trading process or any decision making operation. Workflow management is emerging as one of the most important Grid services. It is said that about 90% of time spend in just communication not on the actual processing [12]. Workflow system can save this time by automating processes in sequence and flow of data between the processes. This sequence of processes can also be changed easily for different types of electricity markets. It can also help in decision making for the bid accepters and reduce the work load of ISO by providing additional information to like availability of transmission lines from the intendant generator to the required load area.

Geographical Information Systems can be implemented on Grid Computing (like these are highly used in Oil fields) in order to provide the visual information about generation, the available transfer capability of transmission lines and load. It can also provide the information about the alternative routing path in case of any disaster. This can save the system from the black out. Congestion is a condition when devices such as wires or transformers are in danger for overheating due to high currents. It can cause disaster in the system. Grid computing can also provide the services to avoid the congestion problems by working parallel with the transmission system. Energy storage is one of the major problems with electricity as a service [5]. For this reason, there is always need to generate energy according to demand load. Grid computing can provide the services to minimise the difference between the generation and demand load as much as possible by using the load balancing services. 3.5

PLANNING

Much information and computations are involved in planning the new establishment or expansion in the power systems. Grid computing can help in providing all kind of information at one place with authorised access and power of fast computation for this purpose. Planning needs analysis of large amount of data, which requires simulation and modelling. A key source is required for successful simulation and modelling and Grid computing provides the power for this purpose. Planning of future power systems needs the combine effort of many companies [2]. The sharing of accurate and reliable information and forecasting mechanism facilitate this process. Grid computing provides an integrated environment for this purpose for all the companies and individuals involving in planning for power systems.

Figure 4: Work Flow model for bidding system in electricity market.

It can provide the information about market forecasting by providing the history information by making the log of the system. 3.4

SCHEDULING, LOAD BALANCING AVAILABLE TRANSFER CAPABILITY

AND

Power systems scheduling can be of two types according to the type of bidding. It can be either short term as an hour before trading or it can be according to a day before trading. Grid computing can help in scheduling and monitoring the status of transmission lines in the whole network, which can also help in the bidding decision by ultimately saving the time and reduce work load of ISO in bidding finalization. It can track the record of available transfer capability and can provide advance information before finalizing the bids by simulating the data according to the availability of transmission media. This can also be helpful in preventing congestion in the transmission system.

3.6

REGULATION

Grid computing has capability to work in both regulated and deregulated environment with different type of access to the information. It can enhance the performance and efficiency by introducing the better changes in terms of production and economically in regulated environment. In Grid computing each user has different access rights for the share resources. These rights can be altered according to new regulation rules. These access rights can be technical or on the administrative. Also in case of collaboration, each organization can work together with its own policies and regulations. 4

CONCLUSIONS

Grid computing provides high performance data processing service with the help of the integrated computers connected to each other through local area network or through Internet. It uses parallel processing and distributed systems technology which are the

backbone of high performance computing. It has extensive use in many fields of science and engineering. In this paper we focused on power systems and highlighted some applications in power systems where Grid computing technology can be helpful. Power companies need high performance computing systems in order to process their data for operations of their systems and to make the decision for future investments efficiently. Also due to working in same field, companies also need to collaborate and share their data for different purposes. Grid computing with its characteristics provides cheap and efficient solution for all said issues. And we can say that Grid computing will work parallel to the electrical grid for the progress in this industry. This paper highlights the advantages and huge potentials of Grid computing applications in power engineering. Several potential areas of application have been identified. Some special case applications of Grid computing have been practiced by the power industry, however the potential of Grid computing has yet to be explored further to meet today’s challenges in a deregulated power industry. As on going research, we have been implementing Grid computing in power system reliability and security assessments with significant improvement in computational efficiency. As an initial application of Grid computing in power engineering analysis, we have developed a Grid service for Monte Carlo based Probabilistic Small Signal Stability Analysis and we successfully tested this service by running 10 systems and achieved significant performance. We are now able to simulate more scenarios with significantly reduced computational cost.

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