Power System Operation Risk Research Articles

Simulation and risk assessment of power system with cascading faults caused by strong wind weather

Global warming has led to the frequent occurrence of extreme weather events and threatened the stable operation of the power system. The faults caused by extreme weather events are of long time and massive scale characteristics, which pose new challenges to assessing power system operation risk. The model of the relationship between strong wind information and power grid faults was constructed considering the uncertain of line galloping and complexity of line trajectory. A meteorological-electric hybrid simulation approach was constructed with alternative and adaptive simulation strategies to simulate the cascading faults scenarios under the extreme weather of strong wind. The risk assessment method and index combining risk and fragility were proposed based on the proposed hybrid simulation approach. Case studies were performed to verify the feasibility of the proposed risk assessment method.

Research and application of power system operation risk assessment method considering new energy grid connection

The traditional distribution network operation risk assessment does not fully consider the intermittency and volatility of new energy sources, which has an adverse impact on the security management of the power grid. Therefore, combined with the probabilistic characteristics of new energy power generation, this paper establishes a distribution network operation risk assessment model and a comprehensive risk index system including new energy grid-connected, mainly including voltage over-limit, voltage collapse, line active power over-limit, system load loss, abandoning the wind and abandoning the light, exceeding the frequency limit, etc. On this basis, this paper formulates the weighting factors of each risk index, and comprehensively judges the weak points of the system. The example analysis shows that the risk assessment method proposed in this paper can quantitatively analyze the weak links after the new energy is connected to the distribution network. This verifies the effectiveness of the proposed method and provides a reference for the future development of new energy grid-connected security.

Modeling multivariate dependence by nonparametric pair-copula construction in composite system reliability evaluation

The correlated variation of bus loads, wind powers, etc., has a significant impact on the power system operation risk. The construction of the accurate dependence model becomes vital in the field of power system reliability evaluation. Most currently used methods in estimating the multivariate joint probability density function (PDF) may encounter obstacles such as modeling accuracy and the curse of dimensionality, especially in the high-dimensional case. To address such problems, a nonparametric pair-copula construction (NPCC), which decomposes the joint PDF into a product of marginal PDFs and a set of bivariate copula (also called pair-copula) densities based on graph theoretic algorithm, is used in this paper to achieve an accurate modeling of the multivariate correlation. To construct a unified framework of nonparametric estimation, the marginal PDFs and the bivariate copula densities are both estimated in a data-driven mode. Moreover, a PDF transformation method is also proposed in estimating the bivariate copula densities, aiming to avoid the problem that the distribution range of the transformed variables in the pair-copula densities exceeds its feasible domain. The performance of the proposed NPCC is verified by a modified version of IEEE-RTS79 with complex correlation among bus loads and wind powers.

An Incremental-Variable-Based State Enumeration Method for Power System Operational Risk Assessment Considering Safety Margin

This paper proposes an incremental-variable-based state enumeration method (IVSE) for power system operation risk assessment and develops the risk indices considering the safety margin. Firstly, the traditional risk indices are modified to take into account the safety margin, which is defined as the virtual distance from the operational limits to the current normal operating point. Those indices can provide more potential risk information to operators for reasonable decision-making. Thereafter, an incremental- variable-based state enumeration is developed by utilizing the relationship between high order contingencies and low order contingencies. The proposed method is more efficient and accurate than traditional methods, which makes it more suitable for online application. Finally, case studies are performed on the IEEE-118 bus system. And results verify the accuracy and efficiency of the proposed method in various situations. In addition, it also can diagnose the weak points of the system, which can assist operators in online decision making.

A Load-Shedding Model Based on Sensitivity Analysis in on-Line Power System Operation Risk Assessment

The traditional load-shedding models usually use global optimization to get the load-shedding region, which will cause multiple variables, huge computing scale and other problems. This makes it hard to meet the requirements of timeliness in on-line power system operation risk assessment. In order to solve the problems of the present load-shedding models, a load-shedding model based on sensitivity analysis is proposed in this manuscript. By calculating the sensitivity of each branch on each bus, the collection of buses which have remarkable influence on reducing the power flow on over-load branches is obtained. In this way, global optimization is turned to local optimization, which can narrow the solution range. By comprehensively considering the importance of load bus and adjacency principle regarding the electrical coupling relationship, a load-shedding model is established to get the minimum value of the load reduction from different kinds of load buses, which is solved by the primal dual interior point algorithm. In the end, different cases on the IEEE 24-bus, IEEE 300-bus and other multi-node systems are simulated. The correctness and effectiveness of the proposed load-shedding model are demonstrated by the simulation results.

Power system operation risk analysis considering charging load self-management of plug-in hybrid electric vehicles

Many jurisdictions around the world are supporting the adoption of electric vehicles through incentives and the deployment of a charging infrastructure to reduce greenhouse gas emissions. Plug-in hybrid electric vehicles (PHEVs), with offer mature technology and stable performance, are expected to gain an increasingly larger share of the consumer market. The aggregated effect on power grid due to large-scale penetration of PHEVs needs to be analyzed. Nighttime-charging which typically characterizes PHEVs is helpful in filling the nocturnal load valley, but random charging of large PHEV fleets at night may result in new load peaks and valleys. Active response strategy is a potentially effective solution to mitigate the additional risks brought by the integration of PHEVs. This paper proposes a power system operation risk analysis framework in which charging load self-management is used to control system operation risk. We describe an interactive mechanism between the system and PHEVs in conjunction with a smart charging model is to simulate the time series power consumption of PHEVs. The charging load is managed with adjusting the state transition boundaries and without violating the users’ desired charging constraints. The load curtailment caused by voltage or power flow violation after outages is determined by controlling charging power. At the same time, the system risk is maintained under an acceptable level through charging load self-management. The proposed method is implemented using the Roy Billinton Test System (RBTS) and several PHEV penetration levels are examined. The results show that charging load self-management can effectively balance the extra risk introduced by integration of PHEVs during the charging horizon.

Research on Risk Assessment of the Power System Operation Safe

In the current power system scale, complex structure of the power market reform and the new situations, using the deterministic safety standards to describe the security of the power system in power market, already did not adapt the need for safety and economical operation of power system. Evaluation of power system operation risk based on risk consequences for failure probability may occur in the operation of power system and its severity, the comprehensive evaluation system of the risk, and operation of the quantization system for a risk index. This paper first introduces the basic theory of operation risk assessment of power system, research results summarized domestic electricity workers in this field, the research contents and methods, and discusses its application status and development trend, laid the foundation for the further research of power system operation and safety risk assessment.

Power System Operation Risk Assessment Using Credibility Theory

Failure probability of system components may vary with the changes of weather, environment and other operation conditions. The time-varying or condition-based failure probability can be represented using a fuzzy model. Based on credibility theory, this paper presents a novel operation risk assessment method to handle the two-fold uncertainty combining randomness and fuzziness in power system operations. In the proposed method, a random fuzzy model is developed to accommodate impacts due to various operation conditions and other factors on the failure probability of system components. The WECC nine-bus system, IEEE 14-bus system and an actual power system in Northeast China were used to demonstrate feasibility and applicability of the presented method. The operation risk assessment module using the proposed method has been embedded in the EMS system in a district control center of a power company to perform real-time operation risk assessment.