Power Flow Entropy Research Articles

Emergency repair strategy of distribution network under wind disaster based on multidimensional importance evaluation

In order to enhance the power supply reliability of distribution network under wind disasters and provide assistance for distribution network operators to formulate post disaster repair strategies, this paper proposes an optimization method for key nodes and lines evaluation and distribution network repair strategy under wind disaster. Firstly, based on the complex network theory, we considered the status of nodes and lines in the topology and working state. The multi-dimensional evaluation indexes are proposed including improved node degree, node cohesion degree, node intermediate number, weighted line intermediate number, line transfer power flow entropy and line failure rate, etc. Then, the entropy weight method is used to objectively weight the six indicators, and TOPSIS algorithm is used to rank the comprehensive importance of nodes and lines in the distribution network. On this basis, the dynamic programming theory is used to optimize the emergency repair strategy of the fault distribution network after the wind disaster. And the problem of restoring as many key nodes and lines as possible in a short time is proposed. Finally, the method is applied to the IEEE 39 bus system network to verify the feasibility.

The Effect of Power Flow Entropy on Available Load Supply Capacity under Stochastic Scenarios with Different Control Coefficients of UPFC

With the sharp increase in fluctuant sources in power systems, the deterministic power flow (DPF) calculation has been unable to meet the demands of practical applications; thus, the probabilistic method becomes indispensable for the reliable and stable operation of power systems. This paper adopts the probabilistic power flow (PPF) method, which is a Monte Carlo simulation (MCS) based on the Latin hypercube sampling (LHS) method, to analyze the uncertainties of power systems. Specifically, the available load supply capability (ALSC) based on the branch loading rate is used to analyze the safety margin of the whole system, while the improved power flow entropy is introduced to quantify the equilibrium of power flow distribution. The repeated power flow (RPF) calculation is combined with the PPF method, and, hence, the probabilistic repeated power flow (PRPF) method is proposed to calculate the power flow entropy at the initial state and the probabilistic ALSC. To flexibly control the power flow, the unified power flow controller (UPFC) is added to the AC power system. The different control coefficients of UPFC are set to reveal the relationship between power flow entropy and available load supply capability under the stochastic scenarios. Finally, the modified IEEE14 test system is used to study the adjustment abilities of UPFC. With consideration of uncertainties in the test case, the positive effect of UPFC on the power flow entropy and the probabilistic ALSC under stochastic scenarios is deeply studied.

Local Evolution Model of the Communication Network for Reducing Outage Risk of Power Cyber-Physical System

The deep integration of power grids and communication networks is the basis for realizing the complete observability and controllability of power grids. The communication node or link is always built according to the physical nodes. This step is alternatively known as “designing with the same power tower”. However, the communication networks do not form a “one-to-one correspondence” relationship with the power physical network. The existing theory cannot be applied to guide the practical power grid planning. In this paper, a local evolution model of a communication network based on the physical power grid topology is proposed in terms of reconnection probabilities. Firstly, the construction and upgrading of information nodes and links are modeled by the reconnection probabilities. Then, the power flow entropy is employed to identify whether the power cyber-physical system (CPS) is at the self-organized state, indicating the high probability of cascading failures. In addition, on the basis of the cascading failure propagation model of the partially dependent power CPS, operation reliabilities of the power CPS are compared with different reconnection probabilities using the cumulative probability of load loss as the reliable index. In the end, a practical provincial power grid is analyzed as an example. It is shown that the ability of the power CPS to resist cascading failures can be improved by the local growth evolution model of the communication networks. The ability is greater when the probability of reconnection is p = 0.06. By updating or constructing new links, the change in power flow entropy can be effectively reduced.

A Multi-objective Planning of Transmission Line Balance Degree Based on Power Flow Entropy Theory

A Multi-objective Planning of Transmission Line Balance Degree Based on Power Flow Entropy Theory

Research on Urban Load Rapid Recovery Strategy Based on Improved Weighted Power Flow Entropy

As the final stage of power system restoration, the critical task of load restoration is to restore the remaining load as quickly as possible. With the continuous increase of the temperature-controlled load and the proportion of electric vehicle load in the urban power grid, the complexity of the load side in the restoration process gradually increases. Therefore, based on the existing grid environment, this paper considers the sudden increase in load recovery caused by cold load pick-up and the auxiliary effect of electric vehicle discharge on load recovery during the load recovery process. From the perspective of economy, safety, and speed, this paper establishes a multi-objective function that includes the amount of load, improved weighted power flow entropy, and the number of recovered lines. The multi-objective evolutionary algorithm based on decomposition is used to optimize the constructed multi-objective load recovery model. Through the IEEE30 node system, it is verified that the method proposed in this paper can effectively establish a fast and safe load recovery plan that meets the actual grid environment.

Risk identification method of power grid division based on power flow entropy

This research introduced a new way to identify the weak area of power grid by the maximum entropy increase. The stable quantification of grid is judged by weighted power flow entropy index. The index of weighted power flow entropy can quantitatively evaluate the ordered stability degree of system key facts. A large number of simulation calculations of IEEE39 node system show that when the entropy of weighted power flow increases to 40-50% or more, the power grid is easy to enter the self-organized critical state, that is, the risk of blackout increases significantly. This paper studies the influence of the load growth in different regions on the entropy index of the whole system, and selects the region with the largest entropy increase as the weak region. The feasibility and effectiveness of the proposed method are verified by taking an actual power grid as an example.

Optimization of Wind Power Configuration in Distribution Network Based on Scenario Clustering and Power Flow Entropy

Optimization of Wind Power Configuration in Distribution Network Based on Scenario Clustering and Power Flow Entropy

Analyze the Surplus Power Entropy of Water Supply Network after an Earthquake Based on the Pressure Drive Demand (PDD) Model

It is necessary to evaluate the reliability of the water supply network, when the water supply network is damaged by an earthquake. Therefore, this paper researched the feasibility and characteristics of the surplus power entropy as the reliability index of the water supply network, and established a scheme framework for optimizing and improving the reliability of the water supply network. This paper developed a reliability evaluation model for the water supply network after an earthquake. Combined with the Monte Carlo stochastic simulation hydraulic analysis, this model is also based on the pressure-driven nodes water demand model. In the case study, the surplus power entropy method was applied to test the reliability of the model. The statistical curves of the surplus power entropy of nodes and pipe networks, the distribution of the surplus power entropy with different intensities in pipe networks, and the comparison results of three reliability improvement schemes, before and after, were obtained. The influence factors of the surplus power entropy were obtained from the data analysis. The high consistency between the surplus power entropy and flow entropy verifies the feasibility of the surplus power entropy as a reliability index. The three schemes show that the surplus power entropy index can be used as a beneficial supplement to the reliability evaluation index of the pipe network.

Island division and multi-objective network reconstruction considering power flow entropy

Modern power system can identify component faults, isolate faults and resume operation quickly. In view of the problem that the distribution of line load in distribution network is not reasonable and it is easy to fall into the self-organized critical state, this paper introduces power flow entropy as an evaluation index to measure the robustness of power network reconstruction. Based on the power supply capability and node load level of distributed power supply in the process of network reconstruction, a strategy of island division is proposed. Then, a mathematical model is set up to minimize power flow entropy, network loss and node voltage drop, and the problem of network reconstruction after fault is solved by the improved chaos theory and binary particle swarm optimization algorithm. Finally, an example of IEEE-33 node distribution system is given to verify the feasibility of the proposed strategy and the effectiveness of the algorithm.

Resilience-Constrained Economic Dispatch for Blackout Prevention

Abstract The resilience of power systems under high-impact low-probability events, such as extreme weather conditions is getting a growing concern. However, the operational resilience enhancement strategy based on the generation resource dispatch needs further research. Traditional generation resource dispatch, i.e. security-constrained economic dispatch (SCED), aims at minimizing the generation cost while paying little attention to the resilience under extreme events. This paper proposes a proactive resilience-constrained economic dispatch (RCED) model to enhance operational resilience during extreme weather condition. Weather forecast information from the local meteorological agency is used to divide the whole power system area into normal state area and the extreme weather affected area. Two penalty terms are established in the proposed RCED objective function. One represents the transmission lines load rate in the extreme weather affected area and the other denotes the inhomogeneity of power flow of all lines. The penalty terms are introduced to reduce the power flow entropy and prevent power system evolving into self-organized criticality. Thus, the possibility of blackouts is reduced and the system resilience is enhanced. Case studies demonstrate the effectiveness of the proposed model.

Identification of vulnerable lines in power grids with wind power integration based on a weighted entropy analysis method

Vulnerable overhead electricity lines are a cause of serious risk to power distribution grids as damage can be the cause of large scale blackouts and cascading failures. With the integration of large scale wind power into generating capacity, both the topology structure and the distribution characteristics of power flow in distribution grid have undergone various changes that have increased line vulnerability. A novel approach to identify vulnerable lines based on the weighted entropy analysis method is proposed in this paper. In this approach, an assessment index, named the incremental power flow entropy, is first developed, which is used to describe influences caused by variation of the lines' capability of carrying power flow transfers on the vulnerability of the lines themselves at the same aggregation level. A second assessment index, named structural importance, describes the structural changes of a power grid that are caused by the integration of wind-generated electric power. The two assessment indices then are merged into one index by using the entropy weight analysis method, which can assess the vulnerability of the lines from the two aspects of power flow transmission and structural links. Vulnerability analysis under different situations, such as with and without the integration of the wind farm, and sharp fluctuations in wind speed at the wind farm, were carried out on an IEEE 39-bus system integrated with a 75 MW wind farm. Simulation results verified that the proposed assessment index not only can identify the vulnerable lines in a power grid with wind farm integration but also accurately reflected the vulnerability of the internal lines of the wind farm itself.

Power Betweenness Based Identification of Power Grid Critical Links

Synthesizing power transmission relation, topological structure and operational status of power grid a concept of power betweenness is proposed. According to network connectivity and the allocation of power transferring, the power betweenness of transmission line and that of node are defined respectively. Through the cascading attacks such as the breakage or overload on critical transmission lines, the effectiveness validation of the selected critical transmission lines is performed. Taking IEEE 39-bus system as the testing example, the power betweenness of transmission lines and that of nodes are calculated and sorted; according to sorted results, attacks are made on these elements to verify that these elements with high power betweenness are the weak links in power grid indeed. The stability verification under the static attack is performed by network efficiency function and power flow entropy respectively. Verification results show that the higher the power betweenness of electric element is, the greater the attack affects power grid operation.

Optimal allocation of multi-type FACTS devices in power systems based on power flow entropy

Flexible AC transmission systems (FACTS) devices can effectively optimize the distribution of power flow. Power flow entropy can be applied as a measure of load distribution. In this paper, a method is proposed to optimize the distribution of power flow with the coordination of multi-type FACTS devices and establishes the corresponding mathematical models. The modified group searcher optimization (GSO) algorithm is proposed, in which the angle search is combined with chaotic search model to avoid jumping into local optimization. Compared with the different optimal allocation of multi-FACTS devices, the optimal allocation of multi-FACTS devices is achieved under the economic constraints. The locations obtained by this method can achieve the purpose of balancing power flow and enhancing the system performances. The simulations are demonstrated in an IEEE 118-bus power system with two classical types of FACTS, namely static var compensator (SVC) and thyristor controlled series Compensator (TCSC). The simulation results show that the proposed method is feasible and effective.

Research of Power Flow Distribution Evenness Based on Entropy

Research of power flow evenness has great significance for grid steady state analysis. This paper researched for a method for power flow evenness analysis through entropy theory. According to current power flow distribution and branch power limits, the branch load ratio distribution could be obtained, and the power flow entropy was calculated based on discrete information entropy theory. The study case indicates that the power flow entropy effectively describes the power flow evenness. With certain system load level, the system security level will be dramatically declined when power flow evenness reduces to a certain level, which is demonstrated in the case meanwhile. Power flow evenness analysis based on entropy theory is applicable in power system static security assessment.

The Analysis of Influences of Source-Network-Load's Operation Mode on Power Grids Self-Organized Criticality

The distribution of power flow is a determinant of power grids self-organized criticality, and the uniformity of power flows distribution can be quantified by power flow entropy. The theory of power flow entropy is applied in this article to the research of influencing factors of power grids self-organized criticality. First the mathematics mechanism of self-organized criticalitys quantifying by power flow entropy is researched. And then the influence of start-up mode (source), running state (network), load distribution (load) on power flow entropy is analyzed respectively. Finally, the Hexi grid located in Gansu province is employed to verify the critical influences of source-network-loads operation mode on power grids self-organized criticality.

Analysis of cascading failure in electric grid based on power flow entropy

Large-scale blackouts are an intrinsic drawback of electric power transmission grids. Here we propose a concept of power flow entropy to quantify the overall heterogeneity of load distribution and then investigate the relationship between the power flow entropy and cascading failure. Simulation results, from the small-world 300-node test system and the IEEE 300-bus system, show that the power flow entropy has close relations with the cascading failure in terms of both the dynamic propagation course and the static blackout size. Particularly, at the early stage of failure spreading the potential large blackout can be identified according to the power flow entropy. The power flow entropy can serve as an index not only for long-term planning, but also for short-term operational defense to large-scale blackouts.