Quantum Annealing Based Power Grid Partitioning for Parallel Simulation

With grid expansion in China, many metropolitan power grids have been divided into partitions at 220kV to reduce the system short-circuit current and make the grid structure clearer. However, there are still a lot of problems with the current domestic (Chinese) grid partitioning. In contrast, urban power grids of developed countries are fully developed, and their partition operation experience can be reference for domestic urban power grids. In this paper, the grid partitioning situation of domestic cities, especially Shanghai power grid, is presented and analyzed. Then, similar work is done to analyze the grid partition status quo of New York and Tokyo of which grid partition features are prominent. Finally, the metropolitan power grid partition situation in China and abroad is comparatively analyzed to provide reference for the Chinese urban power grids. Keywords-metropolitan power grid; power grid partition; Shanghai grid; New York City grid; Tokyo grid

In order to ensure the security of power grids and control the level of short-circuit currents, a multi-objective optimization method for power grid partitioning is proposed. This method takes into consideration both short-circuit currents and multi-scenario safety constraints. A power grid partitioning optimization model is established to achieve objectives such as minimizing disconnected lines, maximizing safety margins, and ensuring load balance in the main transformers. The model aims to satisfy constraints related to short-circuit current levels, base-case power flow, and N − 1 security. To address the significant deviation in the static security constraint model caused by large amounts of active power losses in large-scale power grids, an improved direct current model is proposed to reduce these errors and meet the accuracy requirements for grid partitioning optimization. Additionally, to adapt to the variability of renewable energy output, an optimization method is proposed, combining three scenarios of renewable energy generation while satisfying short-circuit current and static security constraints. The power grid partitioning model is mathematically formulated as a large-scale mixed-integer linear programming problem, which presents challenges in terms of hardware requirements and computational complexity when solved directly. To mitigate these challenges, equivalent WARD values are assigned to the short-circuit current constraints, base-case constraints, and anticipated fault-induced power flow constraints. Anticipated faults and bottleneck branches are accurately incorporated, and the problem is decomposed into smaller-scale mixed-integer linear programming problems, solved in a stepwise iterative manner. This approach significantly improves computational efficiency and meets the requirements of practical large-scale power grid applications. To validate the proposed model and algorithm, a simulation program is developed using C++, and a simulation analysis of a regional transmission network is conducted. The program ensures the correctness of the proposed model and demonstrates the effectiveness of the algorithm.

Power grid partition with improved biogeography-based optimization algorithm

Recently, wide area relaying protection (WARP) is attracting wide concern for its advantages in coping with challenges to traditional backup protection. It is essential for power grid partition based on limitation of WARP having real-time and rapidity. As a result, a novel concept, limited wide area relaying protection system, is proposed and some basic partition principles, including main substation selection, regional scope and multi-regional overlap, are elaborated for helping to realize WARP in whole power grid. Furthermore, the implementation methods of grid partition is proposed by using matrix calculation on grid topological structure of graph theory, and the process is given based on IEEE 11 nodes system partition. A simulation of 220 kV grid systems in Easter Hubei province shows the effectiveness of grid partition for wide-area relaying protection.DOI: http://dx.doi.org/10.5755/j01.eee.19.3.1259

Aiming at the problem of fast load recovery after power system blackout, an intelligent optimization strategy of load recovery based on grid partition is proposed. An optimal regionalization strategy for system recovery after major blackouts is proposed. In the optimization model, factors such as charging reactive power of overhead lines for generator recovery and closing times of lines for load recovery are taken into account. After optimizing the large-scale system partition, a unified load recovery optimization model considering network reconfiguration factors is established for each partition to realize the parallel load recovery of each partition. Aiming at the optimization model proposed above, the load recovery optimization problem based on power grid partition is solved by combining traditional graph theory and genetic algorithm. In the solution, the genetic algorithm is improved, and aiming at a large number of infeasible problems arising from the application of genetic algorithm, a method of random load rejection and shortest path repair strategy is proposed, which further improves the optimization efficiency and global optimization ability of the algorithm. The correctness and effectiveness of the proposed model and method are verified by simulation analysis of IEEE30-bus system.

Quantum annealing (QA) can be used to efficiently solve quadratic unconstrained binary optimization (QUBO) problems. Grid partitioning (GP), which is a classic NP-hard integer programming problem, can potentially be solved much faster using QA. However, inequality constraints in the GP optimization model are difficult to handle. In this study, a novel solution framework based on QA is proposed for GP problems. The integer slack (IS) and binary expansion methods are applied to transform GP problems into QUBO problems. Instead of introducing continuous variables in traditional slack methods, the proposed IS method can avoid complex iteration processes when using QA. The case study demonstrates that the IS method obtains accurate feasible solutions with less calculation time.

With the increase of energy demand, the scale of power grid is expanding, and the difficulty of power grid fault diagnosis is increasing. Aiming at the problem of large power grid fault diagnosis, a method of partition fault diagnosis based on improved Probabilistic neural network (PNN) and gray relational analysis (GRA) integral is proposed. Firstly, the large power grid divided into small areas for fault diagnosis through power grid partition, which reduces the difficulty of fault diagnosis. Then the PNN diagnosis module is established by the PNN optimized by GA‐CPSO for diagnosing the power grid fault. Finally, the faults in the overlapping area are reanalyzed by the GRA method, in order to realize the accurate fault diagnosis of the whole power grid. The feasibility and effectiveness of the method are analyzed by two cases. The diagnosis results show that the method can effectively identify the faults in the nonoverlapping area and the overlapping area, and has strong fault tolerance and high diagnosis accuracy. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Network partitioning is a popular research topic. Not all available partitioning methods are equally suitable for power grids. Community detection is a critical issue in complex network theory, and power grid is a typical type of complex network. This paper proposes a functional community structure based on an extended weighted network model. An extended adjacency matrix is used to represent an extended weighted complex network model based on coupling strength rather than the conventional adjacency matrix. Meanwhile, we upgraded the Newman fast algorithm of community detection for establishing a novel power grid partitioning algorithm. The electrical coupling strength (ECS) is defined to better reflect electrical characteristics between any two nodes in power grid. Modularity is also redefined as electrical modularity based on ECS. The Newman fast algorithm is upgraded with electrical modularity maximization as the objective to detect functional communities in power grids. A case study on IEEE test systems with 30, 39, 118, 300 buses and one Italian power network demonstrates the rationality of the extended weighted network model and partitioning algorithm.

Power grid partitioning decomposes a large power grid into several clusters. Most of the existing partitioning methods suffer from a limitation that the buses within a cluster are severely topologically disconnected after partitioning in some cases. As a result, a cluster will inevitably be assigned to two or more power grid corporations. This assignment obstructs inner-cluster monitoring and control applications of the transmission system. To overcome the limitation, this paper proposes a multi-index power grid partitioning approach using Monte Carlo simulation guaranteeing cluster connectivity to ensure the cluster autonomy. A line-based binary coding technique is developed to ensure the cluster connectivity. Three partitioning indices are considered: the coherency, the cluster connectivity, and the number of clusters. Finally, the proposed partitioning method is applied to IEEE 9-bus system, IEEE 39-bus system and IEEE 145-bus system and compared with Fuzzy C-medoid (FCMdd) algorithm.

In order to ensure the voltage security of the receiving-end power grid under both steady state and N-1 faults, it is necessary to conduct an accurate dynamic reactive power reserve assessment to ensure its normal voltage operation range at steady state. In other words, it’s to determine the power grid voltage security region which is a transient stability constrained optimal power flow (TSCOPF) problem essentially. However, it needs to consider a large amount operational snapshots and corresponding transient constraints under each snapshot, which increases the computational burden heavily. To overcome this issue, this paper proposes a calculation method for the voltage security region of receiving-end power grid through the equivalence of the transient process. Firstly, based on the power grid partition and the matrix of graph theory, the different snapshots are selected to obtain typical snapshots, and then for the typical snapshots sought, the transient stability constraints under the fault are transformed into steady-state constraints. In other words, the form is consistent with the steady-state equation but the impedance matrix parameters are equivalently adjusted. In essence, it is equally to replace the constraints of the optimization problem under the premise of ensuring that the consistency of the boundary conditions, so as to greatly accelerate the solution speed under the premise of ensuring the accuracy of the solution, and the calculation cases made in the modified IEEE9 system and the modified IEEE39 system prove the effectiveness and reliability of the proposed method in this paper.

Urban power grid has a series of problems such as limited power supply capacity and insufficient reactive power reserve. Reasonable access to VSC-HVDC can effectively alleviate the above problems. In terms of reactive power control, VSC-HVDC can be incorporated into the traditional reactive power support system of regional urban power grids by taking advantage of the rapid, flexible and controllable dynamic reactive power transfer out of VSC-HVDC. Based on BPA simulation, this paper verifies the reactive power support effect of VSC-HVDC on the power grid in the case of flexible direct interconnection of urban power grid partitions and proposes an optimization method of urban power grid partition operation based on the adjustment of VSC-HVDC operation mode, which improves the stable operation level of power grid partitions on the basis of giving full play to the flexible direct reactive power support effect.

Power network partitioning is an old but still challenging and meaningful problem. A large power grid is divided into several zones so that buses within zones are electrically close. Urban power grid partitioning is usually ignored due to its scale is smaller than large power grid partitioning. This paper proposes a method that considers the characteristics of urban loads and a hybridization of genetic algorithm with simulated annealing algorithm is applied to get the best scheme for network partitioning problems. The optimal number of partitions is determined by related theories of matrix analysis and the candidate solutions are evaluated by a multi-index fitness function based on the electrical distance matrix. This method is applied to a real urban power grid with 134 buses. The short circuit currents before and after partitioning are compared to test the validity and practicability of this method.

Power-Grid-Partitioning Model and its Tabu-Search-Embedded Algorithm for Zonal Pricing

Network partition in complex power networks is essential for the var-voltage control. Traditional partition methods such as Ward method are applied in practical power networks, but they are unable to evaluate the quality of partition results. Moreover, they lack efficiency when dealing with large-scale networks. Since complex operation characteristics and topology have emerged in recent power systems, the power grid partition requires higher efficiency and quality. Therefore, this paper proposes a fast network partition method with a balanced-depth-based community detection algorithm. Its aim is to significantly improve the efficiency of partition while maintaining high quality of partition, with which the inter-zone coupling is minimized while the intra-zone coupling is maximized. In the meantime, a surrogate-optimization-based selection algorithm is proposed to select the zonal pilot bus, based on which the secondary voltage control method is used to evaluate the quality of partition. Results from four case studies conducted in various power networks with different sizes, as compared to other partition methods, validate the high efficiency and high quality of the proposed power grid partition approach.

Considering the complex structure of the actual power grid, it is a key measure to partition the power grid reasonably to ensure the safe operation and effective control of the system. Existing methods for grid partitioning are relatively simple, and the accuracy of these methods are difficult to be guaranteed. This paper proposes a method by using improved GN splitting algorithm according to the idea of community detection. Firstly, using analytic hierarchy process (AHP) synthesized the active power betweenness and the voltage-weighted edge betweenness of the line, then defined the comprehensive weighted-edge betweenness based on index of two-factor. This betweenness is used to accurately describe the characteristics of the transmission line such as power flow, voltage and electrical distance. Secondly, using the consistency of flow direction and modularity function as evaluation indexes to verify the rationality of the partitioning results , and the entire partitioning process of the power grid is completed. The improved GN splitting algorithm reduce amount of calculation and increase the speed of area division. The test results of the IEEE 39-node system has verified effectiveness and practicality of this method.