Research On Service-driven Routing Approaches With High Reliability For Smart Grid Communication Network

The smart grid is featured with the integration of advanced information communication technology,remote sensing and many other technologies with the electric network,which is also distinguished from the traditional power grid.The smart grid communication network is an auxiliary network which provids the necessary support for smart grid operation.In the smart grid,the control center periodically interacts with the power plant or the substations according to the obtained electric grid status and makes intelligent decisions to realize management and control of smart grid.Meanwhile,it is responsible for transmitting services to the slave stations or terminals through the smart grid communication network.Services in the smart grid communication network include relay protection,stability control,system protection,dispatching automation,substation surveillance,and some derived services due to the emergence of new applications or value-added services.Different services have different communication requirements,such as transmission latency,bandwidth,etc.One of major differences between the smart grid communication network and the general communication network lies in featured services of electric industry.Given communication network characteristics,service types,and resources utilization,it is important to design high reliability routing algorithms in the smart grid communication network.It is also critical to promote reliable end-to-end service transmission,optimize resource allocation,improve global resource utilization,and balance network load and risk and ensure stable operation of smart grid.The design of high reliability routing algorithm has already attracted extensive attention from academia and industry.However,there are still some problems with existing routing algorithms to be solved in the smart grid communication network.For example,the situation of local network risk expansion caused by service convergence is ignored.There are still lack of dual routes planning approaches for critical services in terms of network structure and service requirements.Moreover,failure occurrences are inevitable in smart grid communication network.The objective and constraints of existing routing model are simply formulated.There are discrepancies between the rerouting models and the actual network operation,and its applicability to smart grid communication network is limited.To solve the problems mentioned above,this thesis focuses on the types of carried services and backbone communication network topology,and studies high reliability routing algorithms in different network scenario including a risk-aware and QoS guarantee dual route planning algorithm,a service route restoration algorithm based on the availability of link bandwidth,service route restoration algorithm oriented to the routing survivability,and a congestion alleviation service route optimation and resource allocation.The main contributions of this thesis are as follows.In the smart grid communication network,the desging of most of existing dual route planning algorithms ignores the peculiarity of service convergence and QoS parameters,the author proposes a risk-aware and QoS guarantee dual route planning algorithm based on the node risk,physical link risk and the total balancing network risk,and formulates a multi-objective optimized model minimizing the transmission delay and the total network balancing risk.Moreover,the nondominated sort genetic algorithm ? with elitist strategy(NSGA-?)is leveraged to solve it.The simulation results show that the proposed scheme enables to satisfy the service transmission latency,and reduces the balancing network risk by about 29.83%,57.48%in the primary and alternate route planning compared with the algorithm of in consideration of the factors of the banlanced load and risk,respectively.Regarding the issue of service difference ignorance and imbalanced network load of the existing rerouting algorithms in occurrence of small-scale failures in smart grid communication network,the author proposes a restoration scheme aiming at the balancing network load in the rerouting algorithm,services are firstly classified into different priorities,and then an integer line programming with the goal of maximizing the link bandwidth availability is established.To reduce algorithm complexity,a heuristic algorithm based on the k shortest algorithm is designed.Finally,extensive experiments are carried out in the two network failures scenarios,namely,one link failure and two link failures,and the simulation results demonstrate that it enables to effectively restore services and reduces the average load standard deviation by 2.26%,3%,respectively.In the smart grid communication network,regional failures resulting from natural disasters easily cause multiple services interruption while the current restoration methods ignore the service performance index and the impact of continuous disasters.Therefore,this thesis proposes service-oriented route restoration algorithm on basis of routing survivability.Firstly,the node,link,and routing path survivability models are established considering the characteristics of earthquake occurrence.To improve algorithm efficiency,satisfy service requirements,and take advantage of excellent representation and decision ability,the author integrates the depth first search algorithm with deep reinforcement learning frame utilizing the improved resample mechanism to obtain the optimal routing combination and realize the overall service recovery.Simulation results demonstrate that the proposed scheme achieves better convergence performance compared to the priority-based deep reinforcement learning.At the same time,the routing path survivability has increased by about 47%in comparison with the greedy algorithm.In case of service switching from the primary routing to the alternate routing,spectrum resource scarcity in the alternate routing path easily results in high service blocking ratio and imbalanced network load.This thesis presents a service routing and resource allocation strategy based on congestion alleviation.The author comprehensively combines service requirements,network topology with network resource status in the time and frequency domain,and formulates the problem of routing and resource allocation as an integer line programming with the aim of minimizing service blocking ratio and time spectrum connectivity.Moreover,this thesis proposes a congestion alleviation mechanism based on the flexible schedule time to deal with the situation of resource shortage.Meanwhile,a heuristic algorithm is designed to solve the model to reduce algorithm complexity.The simulation results show that the proposed scheme reduces the service blocking ratio by about 38.09%,and increases the Jain's fair index by about 54.89%compared to the typical routing and resource allocation strategy.