A strategy based on community detection for parallel topology analysis in power networks

This paper is the second part of a two-part paper on communication-failure-resilient architecture for distributed operation and control in smart grids with hybrid producer/consumer (prosumer) agents. Part I of this paper proposed the distributed architecture and algorithmic development, while this Part II provides the corresponding algorithmic implementation and simulations. We propose a general and scalable framework for implementing resilient distributed frequency regulation (DFR) on large-scale prosumer-based power grids, such as utilities, where each prosumer represents a frequency control area. We first develop a method to obtain quasi-steady state models of prosumers from the dynamic models of generators, loads, and power lines. This model allows demonstrating the dynamic evolution of prosumers under normal conditions and during communication failures. Next, we propose a framework to implement the resilient DFR algorithm on prosumer power grids. We show that under normal conditions prosumers need to solely communicate with their neighbors to obtain optimal control actions. But, during communication failures, prosumers need to extend the communication hops to maintain system-wide stability as well as fair power sharing. The resilient DFR algorithm is demonstrated on two real-world, large-scale power grids and the results show that it can indeed complement and enhance today's Automatic Generation Control systems.

With integration of the large wind energy bases into power grid, wind energy has gradually become an important form of power supply. In order to ensure the stable operation and safe of the power grid after the large wind energy bases are connected, the operation control technology of the power grid after the large wind enengy bases are connected will become more and more important. Therefore, it is necessary to study the operating characteristics and control strategies of large wind energy bases based on the specific problems of power grids and the large-scale centralized connect to wind power grids, combined with the large wind energy bases already constructed and planned in the Northwest and North China power grids. The technical conditions for wind farms grid-connected operation study, the impact of large wind energy bases in North and Northwest China Power Networks on the system operation and stability modes, and the control measures would be include. Technical measures for optimal allocation of reserve capacity, auxiliary decision, power balancing and frequency regulation, suppression of low-frequency oscillation and reactive voltage control for large-scale wind power grid connected power systems would be studied.

Due to the rapid advances of integrated circuit technology, the size of power distribution network (power grid) is becoming larger and larger. There are usually multi-million nodes on a power grid. Analyzing these huge power grids has become very expensive in terms of both time and memory. This paper presents an efficient parallel implementation of the Additive Schwarz Method (ASM) for IR-drop analysis of large-scale power grid. Based on distributed memory system, a new data storage method is proposed to overcome memory bottleneck of traditional methods. Techniques including overlapping in multiple layer and irregular power grid, via detection and grouping are utilized to accelerate the simulation. Moreover, a new communication strategy exhibiting minimum communication overhead is proposed. The proposed method is very accurate in the final solution, with the maximum error less than 0.1mv. Experimental results on industrial medium size benchmarks show that the proposed method achieves more than 110X speedup over a state-of-the-art direct LU solver. The proposed approach can easily solve very large-scale benchmarks, while LU solver fails to obtain the solution because of system memory limitation. It is the first time reported in literature that IR-drop analysis of power grid with over 190M nodes is successfully solved within 5 minutes.

In recent years, with the deepening of smart grid construction, the data generated by power grid operation have increased rapidly, and the power grid big data environment has gradually formed. The power grid data management based on graph data has gained more and more attention, and its efficient storage and processing have become a research hotspot. In this paper, a subgraph partitioning algorithm for power grid graph data is developed. The power grid graph data are partitioned into multiple subgraphs, and then a parallel topology analysis algorithm for multiple subgraphs is proposed. Related experiments show that the parallel analysis scheme of power grid graph data is effective and meets the actual needs of power grid graph data.

In order to effectively improve the operating environment of large-scale power grid and effectively monitor the safety of power grid, this paper analyzes the concept of smart regulation system for large-scale power grid based on big data and artificial intelligence (AI) in the new era environment of smart operation, then analyzes problems existing in the current dispatching system of large-scale power grid in China, as well as the specific needs of smart dispatch system in the design process. And the corresponding smart control system is designed to effectively optimize and improve the operation environment of power grid, and upgrade and improve the core technology of smart dispatching system of power grid.

In the high-voltage power grid of coal mine, the existing adaptive topology analysis algorithm based on the correlation matrix for coal mine high-voltage power grid can effectively identify the network topology and construct a network topology analysis model to provide a basis for subsequent short-circuit current calculation and setting calculation. However, the topology analysis algorithm based on the correlation matrix takes much time. As the scale of the high-voltage power grid network of the coal mine increases, the time consumption will increase sharply as well. However, the prior-to-first-served parallel topology analysis algorithm has been used to reduce the topology analysis time consumption to some extent. On this basis, this article proposes a parallel topology analysis algorithm based on the simulated annealing and optimizes the scheduling strategy of parallel topology analysis. The simulation results show that compared with the prior-to-first-served parallel topology analysis algorithm, the parallel annealing topology analysis algorithm can further reduce the time consumption and improve the computational efficiency. And when the number of available threads increases, its computational efficiency will improve more significantly.

A large-scale power grid's ability to transfer energy from producers to consumers is constrained by both the network structure and the nonlinear physics of power flow. Violations of these constraints have been observed to result in voltage collapse blackouts, where nodal voltages slowly decline before precipitously falling. However, methods to test for voltage collapse are dominantly simulation-based, offering little theoretical insight into how grid structure influences stability margins. For a simplified power flow model, here we derive a closed-form condition under which a power network is safe from voltage collapse. The condition combines the complex structure of the network with the reactive power demands of loads to produce a node-by-node measure of grid stress, a prediction of the largest nodal voltage deviation, and an estimate of the distance to collapse. We extensively test our predictions on large-scale systems, highlighting how our condition can be leveraged to increase grid stability margins.

When a large-scale random charging load is connected to the regional power grid, it can negatively affect the safe and stable operation of the power grid. Therefore, we need to study its charging load and response potential in advance so that electric vehicles can interact well with the grid after being connected to the regional grid. Firstly, after analyzing the influencing factors of regional electric vehicle ownership, an electric vehicle ownership prediction model based on the sparrow search algorithm-improved BP neural network (SSA-BPNN) is established. On this basis, an electric vehicle charging load prediction model is established based on the sparrow search algorithm-improved BP neural network and Monte Carlo algorithm (SSA-BPNN-MC). Secondly, the charging behavior of different types of electric vehicles is analyzed and modeled, and the data from a certain area are taken as an example for the prediction. Then, according to the load forecasting results, the potential of electric vehicles participating in demand response in the region in the future is deeply analyzed using the scenario analysis method. Finally, with the aim of resolving the problems of massive multi-source heterogeneous data processing and the management of electric vehicles participating in the regional power grid demand response, a basic framework of electric vehicles participating in the regional power grid demand response is developed, which provides effective support for promoting electric vehicles to participate in regional grid demand response.

Existing state-of-the-art realizable RC reduction methods may not be suitable for scalable power grid reductions due to the fast growing computational complexity and the large number of ports. In this work, we present a scalable power grid reduction method for reducing large-scale flip-chip power grids based on recent spectral graph sparsification techniques. The first step of the proposed approach aggressively reduces the large power grid blocks into much smaller power grid blocks by properly matching the effective resistances of the original power grid networks. Next, an efficient spectral graph sparsification scheme is introduced to dramatically sparsify the relatively dense power grid blocks that are generated during the previous step. In the last, an effective grid compensation scheme is proposed to further improve the model accuracy of the reduced and sparsified power grid. Since reduction of each power grid block can be performed independently, our method can be easily accelerated on parallel computers, and therefore expected to be capable of handling large power grid designs as well as incremental designs. Extensive experimental results show that our method can scale linearly with power grid sizes and efficiently reduce industrial power grids sizes by 20X without loss of much accuracy in both DC and transient analysis.

The inherent structure of the power grid deeply influences its secure functioning and stability. As power grids move towards becoming 'smarter' with increased demand response and decentralized control, the topological aspects of the grid have become even more important. Understanding the topology can thus lead to better strategies to control the smart grid as well as enable rapid identification and prevention of risks such as blackouts. This paper focuses on modeling and analyzing basic similarities in network structure of large power grids across America and Europe. A simple but accurate model of the power grid can help generate real-sized test cases to evaluate new grid technologies as well as aid in tractable theoretical analysis of the grid structure.

With the continuous promotion of the global energy Internet, the power grid interconnection across regions and countries needs long distance and large capacity power transmission. UHVAC or UHVDC is the main transmission technology. Reference to China's domestic operation experience, with the rapid development of electric power system, large capacity UHVDC construction faster and faster, if the construction of AC system is relatively lagging behind, there will be a "strong DC with weak AC" problem. Through the study, we view from the grid planning point, optimize the power grid structure to solve the problem. In this paper, based on the analysis of the interaction mechanism of AC and DC in different structural forms and the classification of safety and stability of power grid, puts forward three types of indicators for power grid strength evaluation. And through the actual grid example, the correctness of the proposed evaluation index system is verified, which provides a strong guarantee for the planning and development of power grid.

Assessing novel methods for increasing power system resilience against cyber-physical hazards requires real power grid data or high-quality synthetic data. However, for security reasons, even basic connection information for real power grid data are not publicly available. We develop a randomised model for generating realistic synthetic power networks based on the Delaunay triangulation and demonstrate that it captures important features of real power networks. To validate our model, we introduce a new metric for network similarity based on topological data analysis. We demonstrate the utility of our approach in application to IEEE test cases and European power networks. We identify the model parameters for two IEEE test cases and two European power grid networks and compare the properties of the generated networks with their corresponding benchmark networks.

The power industry is the basic industry of the national economy, which can promote the economic development and enhance the living standard. Meanwhile, as the key energy consumption and energy-saving field, the power industry plays an important role in supporting the national economic and social sustainable development. In recent years, the power industry experienced rapid development in China. The report introduces the active efforts and contributions made by the Chinese power industry to the national economic and social sustainable development from multiple aspects and angles with data and examples: 1) With the optimization of power generation and grid structure, promotion of advanced energy-saving technology and enhancement of management level, the technical indicators such as net coal consumption rate, auxiliary power ratio, line loss rate, etc. have been continuously improved. For example, net coal consumption rate of supply reduces from 370tce/kWh in 2005 to 330tce/kWh in 2010, while line loss rate reduces from 7.21% to 6.53%, with a decrease of about 10% during a Five-year Period. The accumulatively 300 million tce of energy conservation has realized outstanding performance; 2) The cleanly energy generators have realized great development with increasing proportion from 23.3% in 2005 to 26.2% in 2010, in which the renewable energy generators gave the main contribution. There has been accumulatively 300 million tce of fossil energy conservation during the period; 3) Desulfurization equipment has developed with very high coverage rate. Fuel gas desulfurization unit was little in 2005, and accounts for 89% of the total coal installed capacity in 2010. The effect of emission reduction is obviously that the emission of sulfur dioxide per unit of thermal power output has decreased by over 60% compared with that in 2005; 4) The national cross-regional grid has come into being, the cross-regional electric energy transmission has been greatly increased and the power grid has played a more and more important role in the resource optimization and allocation, which satisfies the demand of the imbalance between the resource location and power demand focus; 5) The Energy Service Companies (ESCo) subject to power enterprises have been gradually established, that promotes the energy-saving and power Demand-side Management (DSM), brings notable effects from energy management and load management. With the higher influence of the developing concepts such as the low carbon and environmental-friendly in the social development, Chinese economy would realize the sustainable and great-leap-forward new industrialization in future. The power industry will make active contributions through the following measures: To keep on strengthening the power structure adjustment and increasing the proportion of the renewable energy in the power generation; To focus on the upgrade of energy-saving power generation technology, and the development of large-capacity, high-efficiency and high-parameter generators; To emphasize the upgrade of the power grid energy-saving technology and the development of the Ultra High-voltage (UHV) transmission technology, expand the trans-regional network establishment, and strengthen the power generation dispatching and the transaction of generation right; To carry out the renovation of the environmental protection technology, increase the coverage rate of the desulfurization equipment and denitration equipment, and research and apply the Carbon Capture and Storage (CCS) technology; To enhance the management level of energy conservation and emission reduction, and promote the power DSM. In 2020, the proportion of the installation capacity of the renewable-energy-source generators will increase very quickly, the proportion of the single capacity of 600 MW and above in the thermal power generation unit will be over 50%, the coverage rate of the desulfurization equipment will be over 95%, and the coverage rate of the denitration equipment will be about 80%. Calculated according to the Integrated Resource Strategy Planning (IRSP) model, the potential capacity of Efficiency Power Plant (EPP) would be 200 GW, accounting for about 10% of the conventional installed capacity. In the following decade, some indicators of power industry will be the international advanced level, which will promote the national economic and social sustainable development in the aspect of the technology and management, etc.

In smart power grid, power grid and communication network are connected and mutually dependent. The failure in power grid might cause failures in communication network, and vice versa. A tiny failure in either of them could trigger cascade of failures within the entire system. In this paper, we focus on understanding the structure of smart power grid and studying the underlying network model, their interactions, relationships and how cascading failures occur in the system. We propose a practical model for smart power grid as interdependent complex network. The interdependency between two networks is `oneto-multiple': each node in the communication network has only one support link from the power grid, while each node in power grid is connected to multiple communication nodes. We study the effect of cascading failures using percolation theory, and present detailed mathematical analysis of failure propagation in the system. We analyze the robustness of our model caused by random attacks or failures by calculating the size of functioning parts in both networks. Using simulations, we prove that there exists a threshold for the proportion of faulty nodes, beyond which the system collapses. Also we determine the critical values for different system parameters. To the best of our knowledge, this is the first work that models smart grid as interdependent complex networks and studies its fault tolerance.

When large-scale power grids are connected to the power grid, it is conceivable that adverse effects on the operation and planning of power grids can be imagined. Therefore, wind power has characteristics such as intermittency, volatility, anti-peaking characteristics, and large prediction errors. At the same time, the ability to absorb wind power is also weakened by the contradiction between the peak load and the heating load. In addition, due to the thermo-electric coupling characteristics of the cogeneration unit, ie, “heating with electricity,” this characteristic directly determines that its heat output severely limits the regulation of the electric output. The results of the study indicate that the co-production unit’s electric power and thermal power are coupled. Strong nature, the peak load capacity of the unit is greatly affected by the heat load, and the electric power and thermal power distribution lacks a unified calculation and analysis method, which restricts the means of improving the peaking capacity of the unit by controlling the thermal power output of the unit, and through implementation, establishes the main power equipment, The steady-state power model of the thermal equipment, the steady-state power analysis and calculation method of the regional energy system of the power thermocouple, and the realization of adjusting the thermal load related parameters to improve the peak capacity of the thermal power unit.