Power System Voltage Security Research Articles

Improved multi objective particle swarm optimization based reactive power optimization for ensuring voltage security of power systems

In this study an improved multi objective particle swarm optimization (IMOPSO) algorithm is proposed for power system reactive power optimization with the objective of ensuring voltage security. The multi objective particle swarm optimization (MOPSO) is improved by introducing an adapted binary crossover (ABX) to the new positions obtained by the basic particle swarm optimization (PSO) algorithm. Additionally, diversity maintenance strategy is added to the algorithm by employing crowding distance (CD) calculation. The developed algorithm is tested and compared with standard MOPSO and non dominated sorting genetic algorithm (NASGA II). The comparison is made based on the degree of closeness to the true pareto front, as measured by the inverted generational distance (IGD), and based on diversity, as measured by the CDs . The test is made using ZDT1, ZDT2, and ZDT3 test functions. The IMOPSO showed improved performance over MOPSO and NASGA II algorithms in terms of convergence to the true pareto front (PF) and in terms of the speed of convergence as well as in maintaining diversity. The algorithm is then implemented to reactive power optimization of IEEE 14 bus test system. For the implementation purpose, the voltage stability and voltage deviation components of voltage security are formulated as a multi objective functions. The implementation has resulted diverse options of optimal settings of reactive power controlling parameters. The optimal settings proved to produce an improved voltage security as measured in terms of voltage deviation and voltage stability.

A Reactive Power Reserve Constrained Optimum Reactive Power Dispatch Using Coronavirus Herd Immunity Optimizer

The Optimal Reactive Power Dispatch (ORPD) is a very important study in planning the power system operation. The conventional ORPD formulations focus only on driving the objective functions toward optima and ignore the benefits to retain adequate Reactive Power Reserve (RPR) in the system. Studies show that inadequate RPR can jeopardize the power system voltage security under stressed conditions. In view of this, a Reserve Constrained ORPD (RC-ORPD) is proposed in this paper and solved using the recently developed, Coronavirus Herd Immunity Optimizer (CHIO). For this purpose, the minimum required Effective Reactive Reserve (ERR) is devised and introduced as a constraint in the ORPD problems. Here, the minimization of power loss and L-index are taken as objective functions, and the problem is formulated as a non-linear constrained optimization problem. The proposed problem is tested on standard IEEE 30 bus and IEEE 57 bus systems. To assess the impact of the proposed strategy, the same problems are also solved by relaxing the ERR constraint. Comparisons reveal that the added constraint improves voltage stability linked parameters and offers more RPR in the system without sacrificing much on the optimum solution. Further, the proficiency of CHIO is verified through various case studies and comparisons.

Gas Network's Impact on Power System Voltage Security

Due to the energy linkage between electricity and gas networks, assessing the voltage security of the electricity system without considering the practical constraints of both systems, may lead to unrealistic values of loading margins (LM). This work proposes a model for investigating the impact of gas networks on the voltage security of electric transmission networks. The overall objective is to maximize the LM of the electricity network while satisfying all relevant constraints in both gas and electricity networks such as hourly line pack of gas pipelines, reactive power capability limits of generators, and complementarity constraints representing the generators active/reactive power limits based on the capability curves, power flow equations at both current operation, and security limit points. Three (small, medium, and large) case studies are presented as the applications of the proposed model for LM maximization in power systems that are highly coupled with gas networks. The obtained results corroborate the impact of both gas and electrical networks operation constraints such as voltage and reactive power limits, nodal gas pressure limits, gas network loading as well as the line pack phenomenon of gas pipelines on the LM of power systems.

Reactive power optimization under interval uncertainty of renewable power generation based on a security limits method

With the integration of high penetration renewable power generation, the voltage security of power systems is threatened. The reactive power optimization including interval uncertainty (RPOIU) model is applied for developing a voltage control strategy to ensure that the state variables of a power grid reside within their safe operating limits under uncertainty of renewable power generation and load demand input data. However, the RPOIU model is not solved properly in terms of solution efficiency and optimization effect at present. This paper proposes a novel method for solving the RPOIU model, which is denoted as the security limits method (SLM). The proposed SLM first computes the security limits of the state variables of the RPOIU model using an interval power flow method, i.e., the optimizing-scenarios method, and then transforms the RPOIU model into a deterministic model whose constraints conform to the established security limits. The deterministic model is then efficiently solved using the interior point method. We verify that the voltage control strategy obtained by solving the deterministic model is able to ensure that the values of the state control variables satisfy the constraints of the original RPOIU model, but with more conservative security limits. This issue is addressed by modifying the security limits of the SLM through defining an interval ratio, and applying an iterative predictor-corrector procedure. The result obtained by the proposed SLM and modified SLM based on numerical simulations are compared with those obtained by a previously proposed method for effectively solving the RPOIU model, and analysis of the results demonstrates the advantages, effectiveness, and good applicability of the proposed SLM.

Coordinated Optimization of Generation and Compensation to Enhance Short-Term Voltage Security of Power Systems Using Accelerated Multi-Objective Reinforcement Learning

High proportions of asynchronous motors in demand-side have pressured heavily on short-term voltage security of receiving-end power systems. To enhance short-term voltage security, this paper coordinates the optimal outputs of generation and compensation in a multi-objective dynamic optimization model. With equipment dynamics, network load flows, lower and upper limitations, and security constraints considered, this model simultaneously minimizes two objectives: the expense of control decision and the voltage deviation. The Radau collocation method is employed to handle dynamics, by transforming all differential algebraic equations into algebraic ones. Most importantly, Pareto solutions are obtained through an accelerated multi-objective reinforcement learning (AMORL) method by filtering the dominated solutions. The entire feasible region is partitioned into small independent regions, to eliminate the scope for Pareto solutions. Besides, the AMORL method redefines the state functions and introduces creative state sensitivities, which accelerate the switch from learning to applying, once the agent accumulates sufficient knowledge. Furthermore, Pareto solutions are diversified via introducing some potential solutions. Lastly, the Fuzzy decision-making methodology picks up the tradeoff solution. Case studies are implemented on a practical 748-node power grid, which validate the acceleration and efficiency of the AMORL method. The AMORL method is overall superior to conventional reinforcement learning (RL) method with more optimal non-dominated objective values, much shorter CPU time, and better convergence to accurate values. Moreover, compared with another three state-of-the-art RL methods, the AMORL method takes almost the same CPU time of several seconds, but is slightly superior to the state-of-the-art methods in terms of optimal objective values. Additionally, the calculated values of the AMORL method fit the best with the accurate values during each iteration, resulting in a good convergence.

Risk-based security assessment of power system voltage drop: a case study of Nigerian 330KV 41-bus transmission grid

Researchers, system operators, engineers, and utility owners are making extensive efforts to fully utilize the installed facilities of power systems in response to increasing energy demand and thereby creating security challenges for power systems. Thus, this paper addresses the problem of power system security using the risk-based security assessment. A linearized risk-based method which uses fast decoupled load flow algorithm was used to assess the low voltage security of power systems. The method is based on the concept of risk, which considers both the likelihood of occurrence and the severity of the contingency. It requires the probability of voltage distribution, the probability of contingency and severity function to evaluate the impact of the contingency. The proposed method was illustrated on a real power system, the simulation model of the Nigerian 41 bus 330kV transmission grid network for calculating the risk indices of three simulated contingencies at various rates of occurrence. The calculated risk indices show that as the rate of occurrence increases, risk indices increase. This indicates that contingencies with high rate of occurrence with little impact possess higher or equivalent risk to contingencies with great impact, which rarely occur. Therefore, system operator, technician, and engineer should quickly identify, investigate, and proffer solution to them in order to alleviate their effects on the network and improve service delivery. Keywords : Contingency, risk-based index, severity function, power system security

Enhancement of power system voltage stability in multi-carrier energy systems

The concept of multi-carrier energy systems has provided new approaches for solving power system problems. Voltage stability is an important feature of power system which has capability of enhancement in the multi-carrier energy environment. Ordinarily, system operators are forced to select the expensive load curtailment option to preserve voltage stability. However, coupled operation of electrical and natural gas networks using energy hubs, can bring out new solutions for the voltage instability problem which occurs following severe contingencies. In this paper, a new method is proposed for improvement of voltage stability, with utilization of multi-carrier systems concept. This method is based on using natural gas network capability. It is shown that, in the coupled operation of electricity-gas networks, in addition to the reduction of power system voltage security costs, operational cost of the whole system is decreased in regular and contingency conditions, as well. IEEE 14-bus electrical system and 17-bus natural gas system are used for validation of the proposed method.

A predictive agent-based scheme for post-disturbance voltage control

In this paper a predictive scheme for dynamic voltage control is proposed, which maintains voltage security (both voltage stability and voltage profile) of power system, in a wide area manner. The proposed algorithm, upon detecting any voltage violation (both under- and/or over-voltages), employs organized multi-agent system (OMAS) in order to coordinate the employment of reactive power devices in returning voltage magnitudes of all buses to the acceptable range and steady behaviour. In order to achieve high benefits of power system response, each agent takes advantage of a predictive scheme, which is based on the corresponding bus voltage trend. By this predictive characteristic, each agent coordinates its command for remedial action with the prediction of bus voltage destination. Moreover, this predictive characteristic is extended to consider incoming remedial actions (or to compensate the latency in activation of previously decided remedial actions). These predictive characteristics lead to making a smooth waveform and reducing the number of needed remedial actions. The performance of the proposed scheme against different scenarios in Nordic32 test system is presented, where the results illustrate effectiveness and robustness of the proposed scheme.

Research on Voltage Stability Boundary under Different Reactive Power Control Mode of DFIG Wind Power Plant

A novel method is proposed to construct the voltage stability boundary of power system considering different Reactive Power Control Mode (RPCM) of Doubly-Fed Induction Generator (DFIG) Wind Power Plant (WPP). It can be used for reflecting the static stability status of grid operation with wind power penetration. The analytical derivation work of boundary search method can expound the mechanism and parameters relationship of different WPP RPCMs. In order to improve the load margin and find a practical method to assess the voltage security of power system, the approximate method of constructing voltage stability boundary and the critical points search algorithms under different RPCMs of DFIG WPP are explored, which can provide direct and effective reference data for operators.

Flower Pollination Algorithm Based Optimal Setting of TCSC to Minimize the Transmission Line Losses in the Power System

To avoid the problems of voltage stability, losses and security of power system is needed to monitor frequently and these problems are controlled by using the Flexible AC Transmission System (FACTS) devices. They help to improve the voltage profiles, security of the system and minimize the transmission line losses. Thyristor Controlled Series Capacitor (TCSC) is one of the FACTS devices which is easier to control than other control devices. The device was placed such that it also meets the constraint of having minimum losses. Further for setting of the TCSC Flower Pollination Algorithm is employed, it is a nature inspired algorithm developed from the pollination of flowers. For Placement of TCSC, a Fast Voltage Stability Index (FVSI) is proposed. For the verification of the proposed method, simulations are carried on IEEE 14 bus system and the results are presented and analyzed to ascertain the effectiveness in reduction of the losses in the power system.

On-line voltage security assessment and control

SUMMARY Voltage stability analysis and control are key applications for maintaining and enhancing the voltage security of bulk power systems. In today's control center, as power systems become more stressed and the penetration of renewable energies increases, system operators need to analyze voltage security of the systems based on actual operating conditions, contingency and power transactions of the system. In this paper, the model used to represent a power system losing stability is described. It is shown that the voltage collapse point is reached at saddle-node bifurcation or a structure-induced bifurcation. Computation of P–V curves showing system load margin to voltage collapse, system load margin to voltage-limit violation and system load margin to thermal-limit violation is presented. The architecture and example results of the Voltage Stability Analysis and Enhancement system at the California Independent System Operator implementing this research are shown. The continuation power flow engine at the core of this work is presented in detail, and study results are shown. Other key functions, contingency selection (insecure or critical) and ranking, preventive control to increase the load margin of insecure contingencies such that it is secure and enhancement control to increase the load margin of critical contingencies, are presented. Finally, a novel method to enhance the continuation power flow in handling uncertainty of renewable energy is shown. Copyright © 2014 John Wiley & Sons, Ltd.

Voltage security constrained multi-period optimal reactive power flow using benders and optimality condition decompositions

This paper proposes a new coordinated voltage control scheme to ensure voltage security of power systems. The scheme schedules reactive power injection from VAR sources, including synchronous generators and condensers, capacitor banks, switchable reactors and FACTS devices, to ensure desired loading margin of power systems for a given horizon of time. The problem is treated as voltage security constrained multi-period optimal reactive power flow (VSC-MPORPF). To incorporate scheduling of both continuous and discrete VAR sources, the VSC-MPORPF is formulated as a mixed-integer nonlinear programming problem, and is solved using generalized Benders decomposition (GBD). Multi-period formulation ensures both optimal switching pattern of discrete voltage controllers and voltage security for a given future horizon. Also, to make the proposed method applicable for large-scale power systems, optimality condition decomposition approach is utilized, along with the GBD. The proposed methodology is examined through case studies conducted on a simple 6-bus, the IEEE 118-bus, and a 1180-bus test systems. The results demonstrate effectiveness and efficiency of the proposed framework in real-time operation of power systems.

Integrating voltage stability assessment and enhancement into wide-area situational awareness based on international standards

This paper presents a platform for integrating a voltage stability assessment and enhancement (VSA&E) application into wide-area situational awareness (WASA) based on international standards. VSA&E is a key tool for maintaining and enhancing voltage security of bulk power systems. As power systems become more complicated and the penetration of renewable energies increases, system operators require powerful tools to analyze voltage security of the system based on actual online system operating conditions. We have proposed a concept of the international standard-based WASA that can provide such a next generation VSA&E application platform with no vendor lock-in. The effectiveness and practicability of the international standard-based WASA are demonstrated with VSA&E application integrated into a WASA evaluation system. Copyright © 2013 John Wiley & Sons, Ltd.

Approximating the loadability surface in the presence of SNB–SLL corner points

Power system voltage security assessment is generally applied by considering the power system loadability surface. For a large power system, the loadability surface is a complicated hyper-surface in parameter space, and local approximations are a necessity for any analysis. Unfortunately, inequality constraints due to for example generator overexitation limiters, and higher codimension bifurcations, make the loadability surface non-smooth.One situation that is particularly difficult to handle is when a saddle-node bifurcation surface intersects a switching loadability limit surface. In this article we intend to investigate how several local approximations can be combined to obtain an adequate approximation of the loadability surface near such intersections.

ANN based integrated security assessment of power system using parallel computing

This paper presents the application of cascade neural network (CANN) based approach for integrated security (voltage and line flow security) assessment. The developed cascade neural network is a combination of one screening module and two ranking modules, which are Levenberg–Marquardt Algorithm based neural networks (LMANNs). All the single line outage contingency cases are applied to the screening module, which is 3-layered feed-forward ANN having two outputs. The screening module is trained to classify them either in critical contingency class or in non-critical contingency class from the viewpoint of voltage/line loading. The screened critical contingencies are passed to the corresponding ranking modules, which are developed simultaneously by using parallel computing. Parallel computing deals with the development of programs where multiple concurrent processes cooperate in the fulfillment of a common task. For contingency screening and ranking, two performance indices: one based on voltage security of power system (VPI) and other based on line flow (MWPI) are used. Effectiveness of the proposed cascade neural network based approach has been demonstrated by applying it for contingency selection and ranking at different loading conditions for IEEE 30-bus and a practical 75-bus Indian system. The results obtained clearly indicate the superiority of the proposed approach in terms of speedup in training time of neural networks as compared to the case when the two ranking neural networks were developed sequentially to estimate VPI and MWPI.

New Local Adaptive Load-shedding Methods to Mitigate Power System Blackouts

Under-frequency load shedding is a globally accepted remedial measure against a severe drop of power system frequency. With the ever-increasing size of power systems, severe frequency drops are usually caused by combinational severe disturbances. For such disturbances, the active power deficit is usually accompanied by a reactive power deficit presenting some challenges to the load-shedding protection schemes. In this article, two adaptive combinational load-shedding methods are proposed that enhance the frequency and voltage security of power systems for such disturbances. In the proposed algorithms, the under-frequency load-shedding scheme is modified so that the load shedding is adaptively started from locations that have a lower voltage stability margin. Besides, the speed of load shedding is changed adaptively depending on the voltage stability status of the system and the rate of frequency decline. The proposed methods use locally measured frequency and voltage signals and are, therefore, easily applicable. Performance of the proposed load-shedding methods has been compared to that of the conventional method for various disturbances in two different systems. Obtained simulation results confirm that by using the proposed algorithms the power system becomes more robust against large disturbances and the probability of the power system instability is decreased.

On the Validity of Local Approximations of the Power System Loadability Surface

Power system voltage security assessment is generally applied by considering the power system loadability surface. For a large power system, the loadability surface is a complicated hyper-surface in parameter space, and local approximations are a necessity for any analysis. Unfortunately, inequality constraints due to for example generator overexitation limiters and higher codimension bifurcations makes the loadability surface nonsmooth. This makes the use of local approximations limited and calls for a method for estimating the distance to a nonsmooth part of the surface. This paper suggests a method for calculating the distance from a point on the loadability surface to the closest point of nonsmoothness of the loadability surface.

Congestion management considering voltage security of power systems

Congestion in a power network is turned up due to system operating limits. To relieve congestion in a deregulated power market, the system operator pays to market participants, GENCOs and DISCOs, to alter their active powers considering their bids. After performing congestion management, the network may be operated with a low security level because of hitting some flows their upper limit and some voltages their lower limit. In this paper, a novel congestion management method based on the voltage stability margin sensitivities is introduced. Using the proposed method, the system operator so alleviates the congestion that the network can more retain its security. The proposed method not only makes the system more secure after congestion management than other methods already presented for this purpose but also its cost of providing security is lower than the earlier methods. Test results of the proposed method along with the earlier ones on the New-England test system elaborate the efficiency of the proposed method from the viewpoint of providing a better voltage stability margin and voltage profile as well as a lower security cost.

Contingency ranking for voltage collapse using parallel self-organizing hierarchical neural network

On-line monitoring of the power system voltage security has become a vital factor for electric utilities. This paper proposes a voltage contingency ranking approach based on parallel self-organizing hierarchical neural network (PSHNN). Loadability margin to voltage collapse following a contingency has been used to rank the contingencies. PSHNN is a multi-stage neural network where the stages operate in parallel rather than in series during testing. The number of ANNs required is drastically reduced by adopting a clustering technique to group contingencies of similar severity into one cluster. Entropy based feature selection has been employed to reduce the dimensionality of the ANN. Once trained, the proposed ANN model is capable of ranking the voltage contingencies under varying load conditions, on line. The effectiveness of the proposed method has been demonstrated by applying it for contingency ranking of IEEE 30-bus system and a practical 75-bus Indian system.

00/01894 A hybrid artificial neural network (ANN) and Ward equivalent approach for on-line power system voltage security assessment

An accelerating rate calorimeter (ARC) is used to measure the thermal stability of de-intercalated Li1+xMn2−xO4 in LiPF6 EC:DEC (33:67) electrolyte. Self-heating is detected well after the 80°C onset of self-heating measured for lithium intercalated mesocarbon microbead (MCMB) electrodes in LiPF6 EC:DEC (33:67) electrolyte. As a result, the initial self-heating measured in a practical carbon/Li1+xMn2−xO4 lithium-ion cell is caused by reactions at the anode. In previous work, we have proposed a model for the reactions that cause self-heating in MCMB electrodes in electrolyte. By assuming that a cell self-heats only because reactions occur at the anode, the model can be used to predict the power generated by the amount of MCMB in practical cells with an inert cathode. The calculated chemically generated power can be combined with power loss measurements, due to the transfer of heat to the environment, to predict the short-circuit behaviour and the oven exposure behaviour for a cell containing an MCMB anode and an inert cathode. The results agree qualitatively with short-circuit and oven exposure results measured on NEC Moli energy 18650 cells containing an Li1+xMn2−xO4 cathode.