Maintaining Power System Security Research Articles

Analysis of Fast Frequency Response Allocations in Power Systems With High System Non-Synchronous Penetrations

An inevitable consequence of the power system transition towards nearly 100% renewable-based generation is the loss of synchronous generators with their associated inertia, frequency, and voltage control mechanisms. Battery energy storage with different converter technologies, due to their fast-ramping capabilities, are expected to address these challenges and replicate functionalities that so far have been provided by conventional generators. This research presents an in-depth dynamic analysis for the impact of grid forming and grid following battery energy storage locations on the frequency metrics. Performance comparisons that account for the interactions between storage technologies and the decrease of regional inertia are also investigated via dynamic simulations for the projected 90% inverter-based generations in Ireland in 2030. The analysis is conducted using a high-fidelity model of the 39 Bus system, which was modified in DIgSILENT, to best replicate a real frequency event that occurred in the Irish power system. Finally, the empirical findings provide a new understanding of the optimal placement of grid-scale fast storage technologies to maintain power system security at high renewables.

An improved relaxation based spatial domain decomposition method for parallel transient stability simulation

Transient stability assessment by time domain simulation is an indispensable module in Dynamic Security Assessment application employed for maintaining power system security and reliability. Due to continuous expansion and imposition of new complexities, reduction in time required for the simulation of system dynamics is vital for both grid operation and planning. This paper proposes a domain decomposition methodology employing spatial parallelism based on relaxation conditions to speedup transient stability simulations to handle the aforementioned challenge. Since convergence is an issue in relaxation methods, in this work, a convergence enhancing mechanism involving admittance parameters of fictitious networks which mimic the rest of the system for each decomposed smaller network is derived. The proposed method, improves the convergence property of the Parallel Update Relaxation algorithm employed for the concurrent simulation. Also, a technique of port dependency reduction, which guarantees convergence for any general network is presented. The accuracy of the proposed algorithm is validated on a 9-bus system. For the purpose of measuring the performance metrics of the algorithm, two large test cases comprising of 39936 and 79872 buses are considered. Results corroborate the scalability and improved speedup features of the methodology which achieves a significant reduction in the simulation execution time.

Realistic Optimal Power Flow of a Wind-Connected Power System With Enhanced Wind Speed Model

The complexity of achieving optimal power flow in the presence of renewable resources decreases the accuracy and optimality levels of the power system due to the associated intermittency and uncertainty. The increased challenge of large-scale deployment of wind energy necessitates the proper modeling of wind impact on power system security and reliability levels . This article discusses a new reliable power flow optimization tool that accounts for wind power availability and uncertainty. An accurate wind forecast model is created to maintain power system security considering wind power variability. The error of the forecasting phase is included in the proposed model to accurately predict the available wind power. In this work, the scattered wind data is converted into informative frequency distribution considering the effect of averaging around integers, halves, and quarters. The proposed method maximizes the utilization level of wind energy without deteriorating the system security. The accuracy of the new proposed work is presented by comparing its results with other models discussed in the literature. A complete and integrated formulation of the objective function has been accomplished. The cost function includes transmission losses, generation operating costs, generation gas emissions, and valve-point effects. Reliable and efficient optimization algorithms are adopted to minimize the established cost function of the system—namely, teaching-learning-based optimization and symbiotic organisms search algorithms. The effectiveness of the proposed approach is validated using the IEEE 39-bus system.

Bilateral Electricity Market in a Distribution System Environment

Increasing penetration of proactive agents, including distributed energy resources (DERs) and responsive loads (RLs), in distribution systems motivates methods to incentivize market participation from demand-side resources. The complexity resulting from large-scale integration of proactive agents has challenged the viability of centrally managing grid resources in a distribution system environment and motivated decentralized frameworks to coordinate the transactions. Existing decentralized frameworks are primarily focused on designing transaction mechanisms. They neither include a formal market construct nor a computationally feasible approach for market settlement for a large volume of transactions while ensuring the security of grid operation. This paper presents a distributed computational approach for a distribution system market where the coordination framework is based on agreement on bilateral energy transactions reached by market participants. Using the proposed distributed computational method, participants play a role in determining the set of bilateral transactions that maximizes the social welfare. The distribution system operator (DSO) ensures a secure operating condition of the distribution grid by validating each transaction that is agreed upon. Under a potential violation of security constraints by a proposed bilateral transaction, the DSO runs an optimal power flow (OPF) and recommends a new set of transactions (closest to those previously proposed) while maintaining power system security. The proposed framework is validated using IEEE 123-node test system. The results confirm the feasibility of the proposed approach for distribution systems.

Models of Closest Marginal States of Power Systems in <italic>p-</italic>Norms

In order to maintain power system security at the appropriate level and low cost, it is essential to accurately assess steady-state stability limits and power flow feasibility boundaries, i.e., power system marginal states (MS). This paper is devoted to researching the closest MS models in the p -norms. The theoretical studies have revealed that the model of the closest MS in the weighted max-norm, which considers errors of the power change forecast by means of the weighted Euclidean norm, corresponds most closely to requirements of the system operator (SO) for an assessment of the steady-state stability reserve and for the preventive control. At the same time the model of the closest MS in the one - norm best satisfies SO requirements for the corrective and emergency control, and for moving a system state into the power flow feasibility region. This model gives a control action to a critical bus, adding others only in the case of a dosage lack. As a result minimum number of buses will be affected, and minimum loads will be shed.

Fast and Reliable Method of SearchingPower System Marginal States

In order to maintain power system security at the appropriate level and low cost, it is essential to accurately assess steady-state stability limits and power flow feasibility boundaries, i.e., power system marginal states (MS). This paper is devoted to a robust realization of the MS model based on nonlinear programming in a given direction of power change. Considering peculiar properties of this model has allowed proposing a simple, robust and computationally efficient method of the MS search that uses only standard blocks of the load flow solution and can be easily realized in the existing load flow programs. The technique developed on this basis allows considering errors of power change forecast quite easily. Tests on IEEE and Russian systems showed effectiveness of the proposed methods.

Cost Analysis Method for Estimating Dynamic Reserve Considering Uncertainties in Supply and Demand

The use of appropriate hourly reserve margins can maintain power system security by balancing supply and demand in the presence of errors in the forecast demand, generation outages, or errors in the forecast of wind power generation. Because the cost of unit commitment increases with larger reserve margins, cost analysis to determine the most economical reserve margin is an important issue in power system operation. Here, we define the “short-term reliability of balance” and describe a method to determine the reserve margin based on the short-term reliability of balance. We describe a case study, in which we calculate the reserve margin using this method with various standards of short-term reliability of balance. A cost analysis is then performed to determine the most economic standard, and a comparison between our method and a conventional method is carried out. The results show that our method with an economic short-term reliability of balance enables more reliable and efficient operation of the power system. Moreover, with an hourly reserve margin, we show that an increase in wind power generation can result in a significant decrease in the operating cost, which makes wind power generation economically viable.

Demand-side system reserve provision in a stochastic market model

ABSTRACTThe complexity and cost of maintaining power system security using only supply-side mechanisms are likely to increase in the future. Advances in control and information technology offer a possibility for the demand to participate in the system reserve market. By providing reserve, consumers could maximize their benefits derived from electricity markets. This paper presents a new approach to the stochastic modeling of the demand-side reserve provision in co-optimized electricity and reserve markets. A new method for the demand reserve offer price function (DROPF) is proposed. The method accounts for the costs and benefits that consumers derive from participating in the reserve market. The proposed method was tested on IEEE Reliability Test System and the results show that demand flexibility has a great influence on demand-side reserve provision, as well as on the benefits that consumers gain from reserve provision and on the security cost.

Analysing the impact of large-scale decentralised demand side response on frequency stability

Advances in communications technology, higher penetration rates of renewable energy and an evolution towards smarter electrical grids are enabling a greater role from demand side response (DSR) in maintaining power system security and reliability. The provision of primary operating reserve (POR) from domestic loads through a decentralised, system frequency based approach is discussed. By considering a range of system configurations (generation mix, system generation and load) and control strategies, this paper endeavours to answer critical questions concerning the large-scale roll out of decentralised DSR, including the following: what are the implications of DSR resource seasonal variability on system operation and performance following the loss of a large infeed/load? Do increased load coincidence and energy payback phenomena have the potential to significantly impact system frequency recovery? How do DSR controller hardware characteristics influence the provision and effectiveness of reserve delivery? What are the repercussions of a “fit & forget” approach to decentralised control from flexible load on frequency stability as the technology penetration increases? Can DSR be directly substituted for conventional reserve sources while recognising its post-event recovery period? Residential customer behaviour, seasonal effects and the diversity of individual device characteristics are recognised in a detailed thermodynamic flexible load model which is integrated with a detailed power system model to perform the analysis.

Congestion Management Considering Wind Energy Sources Using Evolutionary Algorithm

It is necessary to maintain power system security within a reasonable limit without harming the electric power supply in an emerging electricity market. Power systems are said to be congested when power transmission reaches beyond its limits. Therefore, in a deregulated power system environment, the system operator must look after the power transactions made by market parties. In this article, a novel congestion management method considering wind energy sources is introduced. The proposed congestion management technique is constructed considering the calculation of bus sensitivity factor and generator sensitivity factor. The bus sensitivity factor is used for finding the optimal location of a wind farm. The most sensitive generators are identified to reschedule their output by using the generator sensitivity factor. The artificial bee colony algorithm and particle swarm optimization techniques are applied to compare the generator rescheduling with earlier literature for congestion management. The proposed method has been tested on the 39-bus New-England test system to investigate the effectiveness of the proposed approach of wind farm integration for congestion management.

Effect of line contingency on static voltage stability and maximum loadability in large multi bus power system

Abstract Voltage instability is the phenomena associated with heavily loaded power systems. It is normally aggravated due to large disturbance. Due to deregulation of power system, the system has to cater for the load bids in open access. This may cause the increased transaction level leading to more stress on the power system. It has become an urgent need of today to address the voltage stability problems to keep the voltage profile under control. Several incidences of voltage instability have occurred worldwide recently. In the event of contingency, the most serious threat to operation and control of power system is insecurity. The estimation of the power system state under contingency is an essential task for the power system engineers. The contingency analysis technique is a prerequisite to predict the effects of various contingencies like failure of transformers, transmission lines, etc. It helps to initiate necessary control actions to maintain power system security, reliability and stability. In the present work, two kinds of performance indices viz. active power performance index and reactive power performance index are computed for a large power system using a special code written in MATLAB environment. Furthermore, a novel idea of static voltage stability analysis by incrementing the load in proportion to the original load on load buses along with the most vulnerable line outage using Newton Raphson (N–R) load flow is presented.

Capability of smart appliances to provide reserve services

The growing share of electricity generation from renewable energy creates difficulties in maintaining the balance of generation and demand. This is mainly due to uncertainties caused by prediction errors in renewable generation. In order to maintain power system security, the participation of demand side response to the balancing services such as operating reserve is critical. In this paper, the capability of smart appliances to act as operating reserves for the system operator is investigated. The smart appliances considered are washing machines, dish washers and tumble dryers equipped with communication modules. A novel framework is introduced which enables system operators to access demand response from smart appliances in a timeframe suitable for operating reserves. A mathematical model is developed to simulate appliances with multiple discrete power phases. The delay and interruption of appliances cycles are considered in the model. A multiple time-step simulation is introduced that assesses the load reduction from a number of households as a response to a reserve instruction which is modelled as a price increase with a short notification period. The results are used to estimate the available demand response from Great Britain (GB) households at any moment of the day. With a 20% penetration of smart appliances, the demand response can provide up to 54% of the operating reserve requirements of the GB power system depending on the time of day.

Hybrid fuzzy-neural network-based composite contingency ranking employing fuzzy curves for feature selection

Maintaining power system security in the deregulated and unbundled electricity market is a challenging task for power system engineers. The idea is to short-list critical contingencies from a large list of contingencies and to rank the contingencies expected to drive the system towards instability. Timely corrective measures can then be planned to save the system from collapse and blackout. This paper presents a simple multi-output fuzzy-neural network for contingency ranking in a power system. A fuzzy composite performance index (FCPI), formulated by combining (i) voltage violations, (ii) line flow violations and (iii) voltage stability margin is being proposed in this paper for composite ranking of contingencies. The proposed approach is very effective in handling contingencies lying on the boundary between two severity classes. Feature selection using fuzzy curves has been employed to reduce the dimension of the network. The performance of the proposed method has been tested on a 69-bus practical Indian power system.

Data management for the electricity market

Electricity markets provide economic signals that encourage network utilization to be maximized. This environment is encouraging network owners and operators to ensure that limits are consistent with actual system conditions. The National Electricity Market Management Company Limited (NEMMCO) is a government agent placed between market participants (generators and retailers) with the roles to manage the electricity market, maintain power system security, and coordinate power system planning. Currently, the eastern Australian states of Victoria, New South Wales, Queensland, and South Australia are involved in the market. Power system security and coordination of power system planning for electricity markets involve various power system analyses being done by NEMMCO and market participants. Efficiency of the data preparation for analysis and consistency and transparency of the data are important issues. A software system called the Operations and Planning Data Management System (OPDMS) is being developed to support planning and operations functions in the electricity market environment. One of its key features is the automated preparation of input data files for load flow and transient stability studies using the PSSE analysis package. These data files are generated from real-time power system data and, therefore, allow accurate analysis of actual system conditions. OPDMS improves NEMMCO's ability to develop limits that are consistent with actual system conditions.

Dynamic preventive control strategies for power systems considering transient and midterm stabilities

AbstractThis paper proposes a new dynamic preventive control strategy to maintain power system security, in terms of both transient and midterm stabilities. While the authors have already presented preventive control strategies for transient stability, a new problem has arisen in midterm instability in which some generators lose synchronism after 10 seconds or more from a fault clearance. It is clear that the cause of the instability is mainly post‐contingency dynamic steady‐state instability.This paper first shows a preventive control strategy for improving midterm stability using a dominant eigenvalue of post‐contingency equilibrium point. This paper also presents a unified dynamic preventive control algorithm that can maintain both stabilities together. In this algorithm, the time domain for each stability problem is considered appropriately and the difference between the classical model and the detailed model is analyzed in detail. The effectiveness of the proposed method is examined with numerical examples for a model system.

Pricing for system security [power tariffs

Security in power systems refers to the ability of the system to withstand imminent disturbances (contingencies). Maintaining security is an issue which must be addressed at the system level. It is shown in this paper, however, that it is possible to maintain power system security in an operating environment with many participants (power companies, independent power producers, co-generators, consumers) each attempting to optimize their own benefit, through pricing incentives and appropriate information exchange. Rates for power generation/consumption and for an offer to use during a contingency, as well as information on the probability distribution of contingency need for each participant, are derived so that individual optimization will lead to the socially optimal solution in which power system security is optimized and the aggregate benefit is maximized. >

An educational interactive program for direct analysis of power system transient stability

Maintaining power system security is a technological challenge as power systems are now operated much closer to their security limits. Recent advances in the control and operation of interconnected power systems have generated the necessity to prepare young engineers for the challenges in the area of power system security. This paper presents the implementation of a direct method or power system transient stability in a personal computer environment. The design of the program allows the user to determine the security of a power system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Dynamic preventive control for power system using transient stability assessment based on pattern recognition

To maintain power system security, the authors are developing an integrated security monitoring and control (ISMAC) system which consists of the three main functions: security monitoring, preventive control and emergency control. This paper focuses on the dynamic preventive control which deals with the transient stability immediately after the contingency has occurred. The proposed method is based on the transient stability assessment using the pattern recognition with two-dimensional feature space. Therefore, a preventive control strategy can be obtained rapidly. An index which represents the severity of the contingency quantitatively (security index) is defined by the distance from a linear decision surface which divides a feature plane into a stable and an unstable region. Further, this method has also the advantage that it is possible to consider the effect of the control devices or damping to some extent and specify the operator demand for stabilization flexibly. The effectiveness of the proposed method is ascertained through numerical examples for model power systems.