Post Contingency Research Articles

The LSBmax algorithm for boosting resilience of electric grids post (N‐2) contingencies

A computationally improved algorithm is presented to find the best transmission switching (TS) candidate for boosting resilience of electricity grids subject to (N-2) contingencies. Here, resilience is computed as the reduction in load shed after the above-mentioned (N- 2 ) contingencies. TS is a planned line outage, and past research shows that changing the transmission system's topology changes the power flow and removes post contingency violations. Finding the best TS candidate in a computationally suitable time for effectively boosting resilience is a challenge. The best TS candidate is found using a novel heuristic method by decreasing the search space based on proximity to the bus with the maximum load shedding (LSB m a x ). The LSB m a x algorithm is faster than existing algorithms in the literature; and, it is compatible with both the AC and DC optimal power flow formulations. To validate the authors' claims of speedup and accuracy, two metrics are used to analyze the results from the IEEE 39-bus and 118-bus systems. Finally, the inherent parallelism of the LSB m a x algorithm is leveraged on a high-performance computing platform and applied to the large-scale Polish 2383-bus test system to validate scalability in both size and speedup in computation time.

PFR constrained energy storage and interruptible load scheduling under high RE penetration

Large-scale renewable energy (RE) integration in the power systems is displacing conventional sources of generation, thus reducing the system's inherent inertia and primary frequency response (PFR) capabilities. This reduced response may decline the system's ability to stabilise frequency after inevitable events such as loss of generation or load and thus requires additional PFR. To meet the PFR requirements, fast-acting resources like energy storage systems (ESS) and demand response (DR) (transferrable and interruptible loads) need to be integrated within the system. In this regard, a novel stochastic security-constrained unit commitment framework is proposed to assess the potential of ESS and DR to ensure additional PFR requirements and handle post contingency frequency dynamics. Moreover, the proposed methodology analyses the impact of uncertain RE integration on system frequency dynamics using Bayesian inference statistics. Case studies are carried out on 39 bus New England and 118 bus IEEE test systems, incorporating post fault frequency security parameters. Simulation results analyse the PFR contribution of ESS and DR and indicate a substantial reduction in system operating cost and RE curtailment with their integration. The proposed analysis would help system operators to maintain required PFR under high RE penetration, and handle unavoidable contingencies.

LP based solution for Security Constrained Optimal Power Flow including Power Routers

Power Routers offers many benefits to the power system, it helps in improving the existing transmission asset utilization. Security Constrained Optimal Power Flow (SCOPF) is becoming more important in the electrical power system especially in the present deregulated environment. This paper focuses on completely linearizing the complex non-linear SCOPF problem. The objective function is linearized using Piecewise linearization technique and the constraints are framed using linear sensitivity factors. A formal extension is made to the traditional SCOPF by including power router control in the post contingency time frame. DC power flow analysis is used to calculate the real power flow in the lines.Thus, in this paper, further minimization of cost is achieved by using Power Router control and it is compared with the conventional SCOPF.

Stochastic scheduling of compressed air energy storage in DC SCUC framework for high wind penetration

High intermittent wind generation necessitates integration of bulk energy storage systems (ESSs) for maintaining security and reliability in power system operation. Considering this, stochastic security constrained unit commitment (SCUC) including compressed air energy storage (CAES) as bulk ESS for high wind penetration and with wind uncertainty modelling is addressed. Network constraints for pre- and post-line contingency are modelled using DC power flow. Injection sensitivity factors (ISFs) are conventionally used in power flow equations which, however, make N -1 network security constrained formulation huge and computationally demanding for the proposed stochastic model. Therefore, this study proposes a line outage distribution factor (LODF) to reduce the number of coefficients of post contingency DC power flow equations. This is a compact formulation with the lower computational requirement. Wind uncertainty is modelled as probable scenarios. The proposed SCUC is a complex mixed integer linear programming problem and solved using Benders decomposition technique for IEEE 30-bus and 118-bus system. Simulation results to analyse the impact of CAES, wind uncertainty and line contingency with ISF and LODF on overall operation costs, CAES scheduling, wind curtailment, locational marginal price and computational time. Results show that the proposed model is computationally efficient for system operation under high wind penetration.

Margin-Based Framework for Online Contingency Selection in Unbalanced Networks

A framework for performing fast online contingency selection in unbalanced power systems is presented in this paper. Selection methods are typically based on the principle of identifying the effect of contingencies on multiple normalized performance indices and ranking them using the results. Presently used performance indices are highly nonlinear and they are known to mask the effects of single contingencies leading to misclassifications. In this paper, we propose two new methods, one relying on margin-based performance indices and another based on state sensitivity. New performance indices are proposed based on margins of 1) circuit loading, 2) bus voltages, and 3) reactive power. In addition, a state sensitivity method is proposed which estimates a system's post contingency operating state via a single iteration of the quadratized power flow model and provides estimates of post contingency line loading, bus voltages, and reactive power levels. Numerical experiments on a three phase version of the IEEE Reliability Test System show that the proposed performance indices yield more accurate results, at a computational cost comparable to a single power flow iteration. The state sensitivity method is more accurate in identifying critical contingencies but its computational cost is higher. The method has been also demonstrated in the larger PEGASE systems.

Analysis of reserve relaxations in electric energy markets

Electric power grids are some of the most complex engineering systems today. System operators must manage generation fleets with complex operating requirements and transmission assets spanning thousands of miles, while maintaining synchronism and meeting strict reliability criteria. Given the limited computational capabilities of modern computers, the Independent System Operators (ISOs) and Regional Transmission Organizations (RTOs) cannot fully integrate all of these complexities in their market model. Thus to ensure scalability, ISOs and RTOs employ a number of approximations within their market models, including proxy reserve requirements that attempt to achieve, but does not guarantee, N−1 reliability. Since the market model is an approximate model itself, and the solution needs to be corrected nevertheless, market management tools allow select constraints to be relaxed for a set penalty price. This paper examines the impacts of different penalty price schemes, for relaxation of reserve requirements, on system N−1 reliability and market outcomes. In particular, the post contingency network violations for the relaxed and non-relaxed market solutions are compared. Moreover, the final cost after making necessary corrections to arrive at the N−1 secure solutions are presented and compared for the relaxed and non-relaxed cases. The paper demonstrates that reserve relaxation does not significantly increase post contingency violations for the market solution or the total system cost after the adjustment phase. Thus, if performed for appropriate reasons such as controlling price or achieving feasibility, reserve relaxation is a justifiable practice in power system operations.

Expected security constrained reactive power planning

The adequate reactive power resources are expected to maintain system integrity under both normal and post contingency operations. Nowadays, the power systems are leading to high-risk operating points, hence, the number of probable contingencies, which should be considered in security constrained reactive power planning (SCRPP), has widely increased. However, considering a large number of contingencies in SCRPP is not practically possible. This study presents an index named expected violation index to consider numerous contingencies in SCRPP. At first, a multi-objective algorithm for the proposed expected SCRPP approach is presented. This novel algorithm uses the probability of each contingency to invest on them more efficiently. Next, it presents a method for selecting candidate buses to install reactive power resources. Then, the effectiveness of the proposed method is analysed using a multi-objective particle swarm optimisation algorithm on IEEE 30-bus test system. Finally, a reliability-based quantitative method is presented for selecting among final Pareto optimal solution. Using the proposed method, the system designers are capable to consider a large number of contingencies in their SCRPPs, to invest more purposefully in reactive power equipment, and to select their most appropriate option among different feasible choices in the optimal Pareto solution.

A parallel computing approach for integrated security assessment of power system

Abstract Fast and accurate assessment of integrated security of present day complex and highly interconnected power system within time frame is a challenging task. The traditional methods used for integrated security assessment are fast but approximate. On the other hand, full simulation methods provide more accurate security assessment, but require large computation time. This paper proposes the use of parallel computing for fast and accurate assessment of integrated security of power system by running full Newton Raphson (NR) load flow program with sparsity technique to compute real power flow or MW performance index ( MWPI ), and voltage performance index ( VPI ), and continuation power flow program with sparsity technique to compute voltage stability index ( VSI ) for all possible single line outage contingencies. The proposed work has been carried out using the Matlab Parallel Computing Toolbox Software (PCTS). To implement parallel computing, the job scheduler, a part of PCTS, divides a computationally intensive job into various tasks and distributes these tasks to its assigned workers for evaluation. Effectiveness of the proposed approach has been demonstrated on IEEE 30-bus system and a practical NREB 246-bus Indian power system. As the proposed method utilizes NR load flow and continuation load flow programs, the accurate post contingency operating status of a power system is also available, which can be used for appropriate corrective actions planning to bring the power system back into secure state. The proposed approach is quite accurate and fast and hence can be implemented for integrated security assessment of practical power systems in smart grid environment also.

Application of Neural Networks to Secure Scenario Based OPF of Power Systems Considering Transient Stability Criterion

In this paper, a scenario based optimal power flow (OPF) is presented considering economic (operation cost minimization) and security objective functions. Security objective functions include both reliability and system transient stability improvement. Energy not supplied (ENS) cost is considered as the criterion for system reliability and critical clearing time (CCT) is considered as the criterion for power system dynamic stability. In order to reduce the computational burden of the proposed method, off-line training of neural network is used to determine CCT based on the system operating point. For this purpose, CCT parameter is calculated in Dig silent Software environment for various operating points of system and a data set is obtained to train neural network. In the proposed method, it is tried to improve dynamic stability of system, as well as decreasing the operation cost in post contingency state through optimal load shedding and generation rescheduling. Genetic algorithm (GA) is used as the optimization tool. The proposed framework is tested on IEEE 39-bus test system and results show efficiency of the proposed method.

Assessment of post-contingency congestion risk of wind power with asset dynamic ratings

Abstract Large scale integration of wind power can be deterred by congestion following an outage that results in constrained network capacity. Post outage congestion can be mitigated by the application of event control strategies; however they may not always benefit large wind farms. This paper investigates this problem in detail and proposes an advanced mathematical framework to model network congestion as functions of stochastic limits of network assets to capture post contingency risk of network congestion resulting through the constrained network capacity that limits high penetration of wind. The benefit of this approach is that it can limit the generation to be curtailed or re-dispatched by dynamically enhancing the network latent capacity in the event of outages or as per the need. The uniqueness of the proposed mathematical model is that it converts conventional thermal constraints to dynamic constraints by using a discretized stochastic penalty function with quadratic approximation of constraint relaxation penalty. The case study results with large and small network models suggest that the following an outage, wind utilization under dynamic line rating can be increased considerably if the wind power producers maintain around a 15% margin of operation.

Security Enhanced OPF with Transmission Cost Solution under Bilateral and Multilateral Transactions

In a deregulated electricity market, it is important to dispatch the generation in an economical manner. While dispatching it is also important to ensure security under different operating conditions. In this study intelligent technique based solution for optimal power flow is attempted. Transmission cost is calculated using Bialek’s upstream tracing method. Generation cost, transmission costs are combined together for pre and post contingency periods to form objective function. Different bilateral and multilateral conditions are considered for analysis. A human group optimization algorithm is used to find the solution of the problem. IEEE 30 bus system is taken as test systems.

Optimal power flow with transmission cost solution under bilateral and multilateral transactions

Abstract In a deregulated electricity market, it is important to dispatch the generation in an economical manner and to ensure security under different operating conditions. In this study evolutionary computation based solution for optimal power flow is attempted. Social welfare optimization is taken as the objective function, which includes generation cost, transmission cost and consumer benefit function. Transmission cost is calculated using Bialek’s power flow tracing method. Severity index is applied as a constraint to measure the security. The objective function is calculated for pre and post contingency periods. Real power generations, real power loads and transformer tap settings are selected as control variables. Different bilateral and multilateral conditions are considered for analysis. A Human Group Optimization algorithm is used to find the solution of the problem. The IEEE 30 bus system is taken as a test system.

An improved genetic algorithm approach for security constrained optimal power flow with corrective action

Security constrained optimal power flow (SCOPF) is a special type of optimal power flow (OPF) programme in which the optimum value of the objective function is computed while satisfying the constraints, both under normal and contingency conditions. This paper presents an improved genetic algorithm (IGA) approach to solve the corrective SCOPF problem which takes into account the system corrective capabilities in the post contingency state. The resulting schedule will have the same security level as the SCOPF, but with lower operating costs. The IGA uses strings of integers and floating point numbers to represent candidate solutions instead of binary strings. Crossover and mutation operators which can directly deal with the floating point number are used for a more effective genetic operation. Computer simulation is carried out on IEEE 30-bus and IEEE 118-bus systems using the proposed approach and the results are compared with the other approaches. Simulation results show the superiority of the proposed approach over the other approaches in solving the SCOPF problem.

Enhanced Genetic Algorithm Approach for Security Constrained Optimal Power Flow Including FACTS Devices

� Abstract—This paper presents a genetic algorithm based approach for solving security constrained optimal power flow problem (SCOPF) including FACTS devices. The optimal location of FACTS devices are identified using an index called overload index and the optimal values are obtained using an enhanced genetic algorithm. The optimal allocation by the proposed method optimizes the investment, taking into account its effects on security in terms of the alleviation of line overloads. The proposed approach has been tested on IEEE-30 bus system to show the effectiveness of the proposed algorithm for solving the SCOPF problem. Keywords—Optimal Power Flow, Genetic Algorithm, Flexible AC transmission system (FACTS) devices, Severity Index (SI), Security Enhancement, Thyristor controlled series capacitor (TCSC). preventive approach for security enhancement, the post contingency state corrective action can also be used for security enhancement. The resulting stage has the same security level as the usual security - constrained optimal power flow case with lower operating cost. The power electronics-based FACTS devices can also be employed for corrective action due to its high speed of response. Thyristor controlled series capacitor (TCSC) is one such device which offers smooth and flexible control of the line impedance, with much faster response compared to the traditional control devices. TCSC can be used effectively in maintaining system security in case of a contingency; by eliminating or alleviating overloads along the selected network branches. It is important to ascertain the location for the placement of these devices due to their considerable costs. In this paper, the location of the TCSC is

Dynamic security constrained optimal power flow/VAr planning

Traditionally security constrained optimal power flow and VAr planning methods consider static security observing voltage profile and flow constraints under normal and post contingency conditions. Ideally, these formulations should be extended to consider dynamic security. This paper reports on a BC Hydro/CEPEL joint effort establishing a dynamic security constrained OPF/VAr planning tool which considers simultaneously static constraints as well as voltage stability constraints. This paper covers the details of formulation and implementation of the tool together with the test results on a large scale North American utility system and a reduced Brazilian system.

Large scale voltage stability constrained optimal VAr planning and voltage stability applications using existing OPF/optimal VAr planning tools

Traditionally in optimal VAr planning, the feasible operation has been translated as observing voltage profile criteria ensuring that the system voltage profile is acceptable for system normal and post contingency conditions. This feasibility definition is not sufficient when considering the VAr planning practice of the utilities concerned with voltage stability problems. Presently, these utilities use two reinforcement criteria for VAr additions. While for VAr design in the regions the voltage profile criteria is considered, for bulk transmission system VAr resources are designed to guard against voltage instability. This paper reports on the findings of a recently completed EPRI project evaluating the existing optimal VAr planning/OPF tools for voltage stability constrained VAr planning and voltage stability applications. Two of the selected tools were adapted to address these applications on four large scale utility systems (up to 6000 buses). The results were also verified using EPRI's voltage stability program (VSTAB). The results obtained indicate that OPF/VAr planning tools can be used to address voltage stability constrained VAr planning and voltage stability applications in an accurate way. Additional advantages offered by these tools are easier procedures, less computation and avoidance of engineering judgment in identifying the amount of VAr requirement at the candidate sites.

Fast contingency evaluation by means of the improved adjoint network method

In this paper, an improvement of the adjoint network (AN) method based on the Tellegen theorem for calculation of power system variables following various contingencies is presented. A new model of PV nodes is developed and the response of PV nodes to line as well as generator outages is modelled accordingly. Furthermore, an improved computational scheme is derived that enables a fast single step evaluation of post contingency power system variables. Example cases of test and practical systems show that the improved adjoint network (IAN) method offers an efficient tool for on-line contingency analysis due to its improved accuracy and computational effort in comparison with the widely accepted 1 PI Q approach based on fast decoupled powerflow (FDPF).

Direct Ranking for Voltage Contingency Selection

It is now commonly accepted that for security assessment of a power system, the most efficient and practical strategy is to deal with the problem in two stages. First in contingency selection, those potentially critical contingency cases are ranked by the severity of their impacts on a system. Then in contingency analysis, detailed AC power flows are applied only to the most dangerous cases appearing on top of the ranked list. In the past decade, the problem of ranking outage cases in the order of decreasing severity has attracted a lot of intensive studies, and many efficient and reliable algorithms were developed. But most of these techniques can only be applied to MW limit security problems. On the other hand, voltage problems were also found to be a very important aspect of security assessment. It has become the target of many research projects. Because the MVAR-voltage problem involves a much more complicated model than the MW-angle problem, significant obstacles were experienced in developing ranking algorithms for voltage security monitoring, making it an area where further study is still required. Almost all contingency ranking algorithms employ a scalar performance index to represent a global severity of voltage disturbance after a contingency event. The scalar performance index can be viewed as a weighted distance in voltage space measuring the post contingency voltage profile against specified voltage limits.

An Emergency Control Algorithm for Real-Time Applications

An emergency control algorithm for possible incorporation as one of the major functions of an Energy Control Center is developed. The algorithm considers the effect of governor and AGC loop settings and determines the post contingency state and checks for any overloading condition. In the event of such overloading a Linear Programming procedure evaluates an alternate safe target state.