Analyzing the Chord Peer-to-Peer Network for Power Grid Applications

Transcription

1 Analyzing the Chord Peer-to-Peer Network for Power Grid Applications Hakem Beitollahi Geert Deconinck Katholieke Universiteit Leuven Electrical Engineering Kasteelpark Arenberg 10, Leuven, Belgium Abstract Various smart power grid applications can be based on agent control systems such as intelligent protection, agents in power market, supply demand matching, autonomous electricity grid (AEG), etc. The dynamic nature of these applications makes that the information infrastructure underlying the power grid is needed not only for static configuration of application but also for modification at run time. This dynamic nature, along with a geographically distributed nature of power grid applications makes the necessity of a robust ICT network, especially based on dependability, security, dynamicity and scalability attributes. Chord is a purely decentralized peer-to-peer network. Its structure is a ring that is constructed using distributed hashing tables (DHT). This paper analyzes and studies properties of Chord network for power grid applications. Analyses show the major advantages of Chord network for power grid applications are fault-tolerance, scalability, self-organization, decentralization, and efficient lookup network. This paper also analyzes dependability aspects of Chord network for power grid applications. It considers dependability with reference to reliability, scalability, availability, and security. This paper shows Chord network is suitable for power grid applications from reliability, scalability, availability, dynamicity and quick search view but it is not suitable from security perspective. 1 Introduction The power grid transports and distributes electricity from the power plants to the consumers [11]. Improving performance of power grid (optimize power quality, cost, energy Acknowledgements: This work has been partially supported by the K.U.Leuven Research Council (project GOA/2007/09) and by the European Commission (project IST CRUTIAL) loss, etc.) needs precise management and distributed control [12]. Today the security of major international and national infrastructures in all countries has became a more critical concern to governments and industry. So nowadays a dependable networked ICT system for the management and control of the electric power grid is desired [5]. The dynamic nature of applications on power grid (e.g. the Autonomous Electricity Network applications [10]), along with a geographically distributed nature of power grid applications makes that information infrastructure on power grid is needed not only for static configuration but also for modification during run time of application. For example the set of components that needs to communicate varies over time because of switching of generators and loads in the distributed generation and hence, the logical communication topology has to follow accordingly [12]. This dynamic nature of applications provides opportunities to use the Chord peer-to-peer network [9]. The main advantages of Chord network for power grids are that it is scalable, selforganizing and distributed. Furthermore it degrades gracefully in the advent of failures, restores automatically after repair and can cope with a dynamic environment. It allows construction of a communication structure that requires little communication and also allows implementation of distributed algorithms for the control and coordination among nodes as well as for the aggregation of measured data. This paper analyzes and studies properties of Chord network for power grid applications. This paper also analyzes dependability aspects of Chord network for power grid applications. Dependability can be defined as the trustworthiness justifiably placed on the service that it delivers [2]. This paper considers dependability with reference to scalability, reliability, security, and availability. Scalability and reliability depend on number of peers and their interconnections, security depends on system s open nature and Internet s communication infrastructure, and availability depends on structure of the system.

2 It shows Chord network is suitable for power grid applications from reliability, scalability, availability, dynamicity and quick search view but it is not suitable from security view. The rest of this paper is organized as follows: in section 2 the Chord network is presented. Section 3 briefly studies the basic control base for new power grid system. In Section 4 it analyzes properties of the Chord network for power grid applications. Section 5 analyzes dependability aspects of the Chord network for power grid applications and section 6 presents conclusion. K54 N56 N51 N48 N1 Source N8 N14 N21 N8+1 N14 N8+2 N14 N8+4 N14 N8+8 N14 N8+16 N32 N8+32 N42 Finger table 2 Chord Network Chord is a decentralized P2P lookup service that stores key/value pairs for distributed data items [9]. Given a key, the node responsible for storing the key s value can be determined using a hash function that assigns an identifier to each node and to each key (by hashing the node s IP address and the key). Each key k is stored on the first node whose identifier id is equal or follows k in the identifier space. Chord uses SHA-1 algorithm [7] as a consistent hashing to map nodes onto an m-bit circular identifier space. Consistent hashing is designed to let peers enter and leave the network with minimal interruption. This decentralized scheme tends to balance the load on the system, since each peer receives roughly the same number of keys, and there is little movement of keys when peers join and leave the system. In Chord, active nodes will form a connected Ring P2P topology under ideal case. In a steady state, for N peers in the system, each peer maintains routing state information for about only O(logN) other peers (N number of peers in the system). In fact, Chord is similar to binary search, where the searching space will be reduced half after a search/routing-hop. So the number of nodes that must be contacted to resolve a query in a N-node network is O(logN). Chord routing algorithm suppose m is the number of bits in the key/node identifier space. Each node n maintains a routing table with up to m entries, called the finger table. The ith in the table at node n contains the identity of the first nodes s that succeeds n by at least 2 i /2 on the identifier circle, i.e.,s = successor(n + 2 i /2), where 1 i m (and all arithmetic is modulo 2 m ). We call node s the ith finger of node n. Note that the first finger of n is the immediate successor of n on the circle and we call it the successor of node n. The example in figure 1 shows finger table of node 8. The fist finger of node 8 points to node 14, as node 14 is the N42 N38 N32 Figure 1. Chord routing model: finger table entries for node 8 K54 N51 N48 N56 N42 N38 N1 Destination Source N8 N32 N14 N21 Figure 2. Chord routing model: path of query for key 54 starting at node 8 first node that succeeds ( )mod2 6 = 9, where m = 6. Similarly, the last finger of node 8 points to node 42, as node 42 is the first node that succeeds ( )mod2 6 = 40. Now suppose node 8 wants to find the successor of key 54 (figure 2). Since the largest finger of node 8 that precedes 54 is node 42, node 8 will ask node 42 to resolve query. In turn, node 42 will determine the largest finger in its finger table that precedes 54, i.e., node 51. Finally node 51 will discover that its own successor, node 56, succeeds key 54, and thus return node 56 to node 8. Since each node has finger entries at power of two intervals around the identifier circle. Each node can forward a query at least halfway along the remaining distance between the node and the largest identifier.

3 3 Basic control base for new power grid system Today, there is an important trend to use small dispersed generators in low or medium voltage, also referred to as Distributed Generation (DG), for producing electricity [1, 3, 8]. However, this dramatically change in power grid has changed the traditional distributed grid topology, control systems, security measurements, etc [1, 3]. All these changes put new and extra stress on power grid where power is one of the most important commodities for industrial, economical and everyday activities. Control of power elements in power grid has three control levels [10, 8]: A) Primary control is used to balance both active and reactive power, based on frequency measured locally. This kind of control has no need for communications. B) Secondary control is mainly used for maintaining rated voltage levels or rated frequency and scheduled power transfers C) tertiary control optimizes generators output for economic criteria. The last two control levels both require some form of coordination and communication with other generator controllers. By adding DGs to the power grid for these levels of control, traditional central control systems are not suitable due to expenses such as expensive, dedicated communication lines and a large number of load balancing servers. So we are looking for less expensive ICT-infrastructure for these control paradigms. Agent based control systems Evolutions in the power grid have convinced us to design an intelligent, distributed control scheme [1, 12]. In this scheme power grid components (e.g. generators, dispatching loads) are equipped with an autonomous control entity (agent). These agents are implemented on some electronic devices (e.g. PCs or DSPs). Agents can supervise the grid component at hand, fetching state parameters of the components of the component from various sensors. Agents interpret these parameters and aggregate these into a high level conclusion on the current state of the component. Agents may also send control parameters to the control system (e.g. SCADA) of the component. An important aspect of agents, besides autonomy, is that they communicate with a society of (similar) agents, from which they may fetch external knowledge of their interest. This way of exchanging information enables an agent to not be only aware of the state of its own component, but also to have a notion of the global environment in which it is operating. These societies can be built easily by setting up a peerto-peer network. Agent based control scheme by using Low Voltage Distribution Grid with embedded DG Corresponding Peer-to-peer Network Househould (with smart loads) Wind torbin Fossil fuel driven small generator Photovolic generator Peer-to-peer network links Public communications LV power line Grid connected transform Controller agent Figure 3. Example of P2P network that applied to power grid [8] P2P communication opens new opportunities for controlling power grid elements. Some of these opportunities (applications) are Intelligent Protection [6], Power Market [4], Supply demand matching [4], intelligent load shedding, and Autonomous electricity grid (AEG) [10]. A simple example of P2P network formed between agents is shown in figure 3.

4 4 Analyzing properties of the Chord network for power grid applications The dynamic nature of applications on power grid (e.g. the Autonomous Electricity Network applications), along with a geographically distributed nature of power grid agent controllers makes opportunity to use Chord peer-to-peer network. The main advantages of Chord network for power girds are efficient lookup search, decentralization, selforganization, and no partitioning. Efficient lookup search: in power grid agents need to communicate with other agents. For instant an agent needs to search a data in other agents or needs to send a message to the some specific agents. Sometimes an agent needs to collect other agent s decision. Using a Chord network, all of these communication scenarios can be done efficiently and quickly because the Chord network can find a data or send a message to any arbitrary node in only O(log N) steps (N is the number of agents). Decentralization: Chord is fully distributed; no node is more important than any other. This improves robustness and makes Chord appropriate for loosely organized P2P applications. Distributed generation controllers (DG agents) in power grid due to same logic function, and geographically distributed nature need to be distributed. Power grid agents act as peers in Chord network. No agent (peer) is important than any other. Self-organization: as a result of decentralization, there is no node that centrally coordinates its activity or a database to centrally store global information about the system. Therefore nodes have to self-organize themselves, based on whatever local information is available and interacting with locally reachable nodes. By this property any agent itself can decide to leave the system or again join the system. In power grid, an agent may be needed to leave system due to some technical problems (e.g., repair or update) and is joined the system after solving the problems. In fact agents are autonomous and independent from other agents by this property. Leaving and joining of agents does not have bad effect on system performance. Hence, selforganizing property is necessary for agents network. No partitioning: the Chord network never partitions. In a Chord network, when at least one node works, the system works. By Chord network, healthy agents always can communicate with each other without partitioning. If agent network is partitioned, power grid misses its performance and agents cannot control the system correctly. Hence by using Chord network we guarantee that agent network never will be partitioned. 5 Analyzing dependability aspects of the Chord network for power grid applications The section analyzes dependability aspects of Chord network for power grid applications. It considers dependability with reference to reliability, scalability, availability, and security. Reliability: Chord topology is purely decentralized and there is no single point of failure. Furthermore, these systems store a reference to a resource in the nearest peers instead only storing one reference in the next one (replication). Moreover, each peer runs a stabilization algorithm that maintains correctness of references. So agent s network is reliable. Failure of an agent does not have effect on system performance and it simply remove from the network without bad effect on the system. The rest of agents can communicate and control the system. The failure agent can come back the system after reparation. Scalability: As Chord network has efficient query routing searches, a growing number of search queries does not negatively influence on traffic. So the cost of a Chord lookup grows as the log of the number of nodes. Hence even very large systems are feasible. In power grid network may be some generators added the system in future and so new agents may be required. By this property of Chord as much agents as necessary can be supported and added to the system. Availability: Chord automatically adjust its internal tables to reflect newly joined nodes as well as node failures, ensuring that, barring major failures in the underlying network, the node responsible for a key can always be found. This is true even if the system is in a continuous state of change. This property of Chord is very important for power grid system because agents must be available always for controlling the system. It guarantees that agents are available always. Agents are available even when they are in update situation. However other network types maybe are not available always. Security: Chord network is not good from a security point of view. It has a systematic and algorithmic structure. Any peer can be a reference point for attackers. As an attacker gets access to a peer, he/she can start various attacks. Main attacks are routing poisoning, partitioning and virtualization into incorrect network when a new peer joins and contacts a malicious peer, lookup and storage attack, inconsistent behaviors of peers, DoS attack and unsolicited responses to a lookup query. By Chord network if an attacker get access to an agent, he/she can start various attacks

5 against other agents. For example he/she can send wrong control instructions to other agents. However, Chord network is suitable for power grid system from reliability, scalability and availability point of view. Chord network is not good from security point of view for power grid system. 6 Conclusion Dynamic nature of applications on power grid (e.g. the Autonomous Electricity Network applications), along with a geographically distributed nature of power grid agent controllers makes opportunity to use Chord peer-to-peer network. This paper analyzes Chord network for power grid system. It shows the main advantages of Chord network for power grids are efficient lookup search, decentralization, self-organization, and no partitioning. The paper also analyzes dependability aspects of Chord network for power grid applications. It shows Chord network is suitable for power grid applications from reliability, scalability, and availability but it is not suitable from security view. References [1] S.M. Amin and B. F. Wollenberg. Toward a smart grid. IEEE Power and Energy Magazine, 3(5):34 41, September [8] T. Rigole, K. Vanthournout, and G. Deconinck. Interdependencies between an electric power infrastructure with distributed control, and the underlying ict infrastructure. In International Workshop on Complex Network and Infrastructure Protection, pages , Rome, Italy, March [9] I. Stoica, R. Morris, D. Karger, F. Kaashoek, and H. Balakrishnan. Chord: A scalable peer-to-peer lookup service for internet applications. In Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM 01), pages , San Diego, California, USA, August [10] K. Vanthournout. A semantic overlay network based robust data-infrastructure, applied to the electric power grid. PhD thesis, Department of Electrotechniek-ESAT, Katholieke universiteit Leuven, April [11] K. Vanthournout, G. Deconinck, and R. Belmans. A middleware control layer for distributed generation systems. In IEEE Power Systems Conference and Exhibition (PSCE), [12] K. Vanthournout, G. Deconinck, and R. Belmans. Agora: Distributed tertiary control of distributed resources. In 15th Power Systems Computation Conference, Liege, Belgium. [2] A. Burns and A. Wellings. Real-Time Systems and Programming languages. Third Edition. Addison Wesley, [3] J. Cardell, M. Ilic, and R. D. Tabors. Integrating small scale distributed generation into a deregulated market: Control strategies and price feedback. Technical Report MITEL , MIT Energy Laboratory, April [4] J.K. Kok, C.J. Warner, and I.G. Kamphuis. Powermatcher: Multiagent control in the electricity infrastructure. In Proceedings of Autonomous Agents and Multi-Agent Systems, [5] K. Lin and K.E. Holbert. Pra for vulnerability assessment of power system infrastructure security. In 37th Annual North America, Power Symposium, [6] NERC. Review of selected electric system disturbances in north America. NERC Disturbances Analysis Working Group, [7] NIST, U.S. Dept. of Commerce, National Technical Information Service FIPS Secure hash standard, April 1995.