Aspects Of Power System Operation Research Articles

Efficient economic operation based on load dispatch of power systems using a leader white shark optimization algorithm

AbstractThis article proposes the use of a leader white shark optimizer (LWSO) with the aim of improving the exploitation of the conventional white shark optimizer (WSO) and solving the economic operation-based load dispatch (ELD) problem. The ELD problem is a crucial aspect of power system operation, involving the allocation of power generation resources to meet the demand while minimizing operational costs. The proposed approach aims to enhance the performance and efficiency of the WSO by introducing a leadership mechanism within the optimization process, which aids in more effectively navigating the complex ELD solution space. The LWSO achieves increased exploitation by utilizing a leader-based mutation selection throughout each generation of white sharks. The efficacy of the proposed algorithm is tested on 13 engineer benchmarks non-convex optimization problems from CEC 2020 and compared with recent metaheuristic algorithms such as dung beetle optimizer (DBO), conventional WSO, fox optimizer (FOX), and moth-flame optimization (MFO) algorithms. The LWSO is also used to address the ELD problem in different case studies (6 units, 10 units, 11 units, and 40 units), with 20 separate runs using the proposed LWSO and other competitive algorithms being statistically assessed to demonstrate its effectiveness. The results show that the LWSO outperforms other metaheuristic algorithms, achieving the best solution for the benchmarks and the minimum fuel cost for the ELD problem. Additionally, statistical tests are conducted to validate the competitiveness of the LWSO algorithm.

Optimization-Based Ramping Reserve Allocation of BESS for AGC Enhancement

The transient behavior of Automatic Generation Control (AGC) systems is a critical aspect of power system operation. Therefore, fully extracting the potential of Battery Energy Storage Systems (BESSs) for AGC enhancement is of paramount importance. In light of the challenges posed by diverse resource interconnections and the variability associated, we propose an online optimization scheme that can adapt to changes in an unknown and variable environment. To leverage the synergy between BESSs and Conventional Generators (CGs), we devise a variant of the Area Injection Error (AIE) as a measure to quantify the ramping needs. Based on this measure, we develop a distributed optimization algorithm with adaptive learning rates for the allocation of the ramping reserve. The algorithm restores a larger learning rate for compliance with the ramping needs upon detecting a potentially destabilizing event. We demonstrate the effectiveness and scalability of the proposed scheme through comprehensive case studies. It is shown that the proposed scheme can improve the transient behavior of the AGC system by bridging the gap in ramping capability.

Two-stage low-carbon optimal dispatch of the power system considering demand response to defend large uncertainties and risks

Introduction: In order to promote the consumption of renewable energy, reduce carbon emissions, and take into account the uncertainty of renewable energy output and load fluctuations in the new power system that can affect the normal operation of market mechanism, a two-stage low-carbon optimization scheduling method for power system that considers demand response under multiple uncertainties is proposed in this paper.Methods: Uncertain scene sets are generated through Latin hypercube sampling and heuristic synchronous backpropagation method is used to reduce scenes to obtain typical scenes and their probabilities. Then, a one-stage optimization model is established with the goal of maximizing energy efficiency and corresponding demand response strategies are obtained. Green certificate carbon trading joint mechanism model consisting of tiered green certificate trading and time-sharing tiered carbon trading are established, and the output of two-stage units are optimized with the goal of minimizing comprehensive operating costs.Result: The simulation results show that the carbon emissions are decreased by 251.57 tons, the consumption rate of renewable energy is increased by 8.64%, and the total costs are decreased by 124.0612 million yuan.Discussion: From this, it can be seen that the dual layer low-carbon optimization scheduling strategy for power system considering demand response under multiple uncertainties can effectively reduce the operating costs and carbon emissions of the system, while balancing the economic and environmental aspects of power system operation.

A survey on voltage stability indices for power system transmission and distribution systems

Voltage stability is a critical aspect of power system operation, ensuring the reliable and efficient delivery of electrical energy to consumers. Recently, voltage stability in the power system has received much attention. The primary cause of voltage instability is the lack of real and reactive power generation to cope with the continuous demand increment. Maintaining voltage stability while planning, controlling, and assessing the system’s security is a difficult task for power system engineers. From knowledge of past incidents, a lack of reactive power is identified as the primary cause of voltage instability, which may further lead to the total collapse of the system. The importance of voltage stability assessment is essential to maintain the integrity of power systems. It helps prevent voltage instability, which can lead to cascading failures and widespread outages. This paper uses various parameters, including load demand, generator capacity, and system impedance, to develop voltage stability indices (VSIs). The paper mainly focuses on the idea of VSIs that have been developed in order to monitor and control the criticality of the power system. The voltage stability indices for transmission and distributed systems, as well as their subclasses, are thoroughly reviewed in this study. Furthermore, traditional voltage stability methods, as well as various software tools for monitoring the voltage stability problems, are also discussed. In addition, the development of VSIs and its related concepts are clearly described in this paper. This comprehensive survey provides a decent groundwork for future work in this area, and assists professionals in selecting the optimal VSI for various applications. Moreover, it provides a concise overview of methods and the importance of voltage stability assessment in both transmission and distribution systems.

Application of data‐driven methods in power systems analysis and control

AbstractThe increasing integration of variable renewable energy resources through power electronics has brought about substantial changes in the structure and dynamics of modern power systems. In response to these transformations, there has been a surge in the development of tools and algorithms leveraging real‐time computational power to enhance system operation and stability. Data‐driven methods have emerged as practical approaches for extracting reliable representations from non‐linear system data, enabling the identification of dynamics and system parameters essential for analysing stability and ensuring reliable operation. This study provides a comprehensive review of recent contributions in the literature concerning the application of data‐driven identification, analysis, and control methods in various aspects of power system operation. Specifically, the focus is on frequency support, power oscillation detection, and damping, which play crucial roles in maintaining grid stability. By discussing the challenges posed by parametric uncertainties, load and source variability, and reduced system inertia, this review sheds light on the opportunities for future research endeavours.

ENHANCEMENT OF LOAD FREQUENCY CONTROL OF MULTI AREA TIE LINE INTERCONNECTED POWER SYSTEM BASED ON INTEGRAL CONTROLLER TECHNIQUE AND POLE PLACEMENT DESIGNE BASED ON STATE SPACE MODELING

Load Frequency Control (LFC) is an important essential aspect of power system operation that ensures the frequency constraints at normal condition. This article deals with the Load Frequency Control of multi region area for tie-line interconnected power system and present a control system to improve the frequency deviation response for a specific changing in the load. The control system that using in this article are the integral controller and the pole-placement design based on state space modeling to improve the performance of frequency response and get a robust stability.

Transformer-based deep learning model for forced oscillation localization

Accurately locating Forced Oscillations (FOs) source(s) in a large-scale power system is a challenging task, and an important aspect of power system operation. In this paper, a complementary use of Deep Learning (DL)-based and Dissipating Energy Flow (DEF)-based methods are proposed to localize forced oscillation source(s) using data from Phasor Measurement Units (PMUs), by tracing the forced oscillations source(s) on the branch level in the power system network. The robustness, effectiveness and speed of the proposed approach is demonstrated in a WECC 240-bus test system, with high renewable integration in the system. Several simulated cases were tested, including non-gaussian noise, partially observable system, and operational topology variations in the system which correspond to real-world challenges. Timely localization of forced oscillation at an early stage provides the opportunity for taking remedial reaction. The results show that without the information of system operational topology, the proposed method can achieve high localization accuracy in only 0.33 s.

A novel optimization method for wind power investment considering economic and security concerns

This paper proposes a novel optimization method for wind power investment to find the optimal location and sizing of multiple wind farms considering both the economic and security aspects of power system operation and planning. The proposed approach maintains the system's security against transient instabilities while improving the voltage profile in the network and minimizing the cost resulting from the investment of wind farms and their operation with thermal units. The transient stability assessment is performed for the power system, considering the uncertainties due to its wind power generation. To model these uncertainties, Taguchi's orthogonal array testing method is utilized. Using Taguchi's method, all the uncertainties in an optimization problem are modeled with only a few representative testing scenarios, and thus, it provides computation efficacy. Moreover, an enhanced hybrid algorithm combining the particle swarm and gray-wolf optimization methods is developed to obtain efficient results in solving the problems formulated. The proposed wind power investment approach is implemented on the New England 39-bus test system, and the results show its effectiveness in providing a reliable and economic wind investment strategy for both investors and operators in the long-term operation and planning of the power system.

Guest Editorial: Medpower 2018 Selected Papers

IET Renewable Power GenerationVolume 14, Issue 1 p. 1-2 Special Section: Medpower 2018 Selected PapersFree Access Guest Editorial: Medpower 2018 Selected Papers First published: 19 December 2019 https://doi.org/10.1049/iet-rpg.2019.1432AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Strategies and concepts driving the development of the future energy and transport sectors emerged as a result of the increasing climate change awareness. What seemed as ambitious goals to reduce the climate impact (through increase of the share of renewable energy sources (RES), increase energy efficiency and reduce carbon emissions) now seems to be understatements of what needs to be done stop the effects of global warming. Initially Europe has set a pathway for others to follow in 2009, clearly stating that business as usual of burning fossil fuels is not acceptable and requiring from its members a reduction of CO2 emissions by 20%, increasing share of RES by 20% and improving energy efficiency by 20% by the year 2020 [1]. The latest EU strategies go even further setting challenges for 2030 with 43-27-27 goals [2], emphasising diversification of energy sources and reducing dependency on imported energy, particularly of gas and oil [3]. Although not mentioned as often as the three pillars described above, both of these strategies require the change in perception of transport, pushing the EU member states to stimulate higher efficiency vehicles and recognising transport as a crucial sector for reducing oil dependency [4]. Similar initiatives are taking place in other leading economies, such as the US [5] and China [6]. These general regulatory goals, described in [1, 5, 6], set a framework to be followed and adopted by national governments in order to create national strategies and incentive programs to stimulate the final users to change their habits and to become active participants of the energy system. It can be easily noticed that most significant changes happen on both sides of the energy balance equations, however, the generation side is now moving closer to the final consumer. The challenges lay in not just interaction with the final consumer but also in changing the way the distribution system, especially low voltage, which is the closest to the consumer, is being planned and operated. Changes that new producers and consumers bring to the operational aspects are often difficult to predict and in order to successfully face these challenges, activating prosumers and their locked flexibility in form of either demand response, or other controllable units in new market concepts, is the key for making a successful transition to low carbon society This Special Section presents extended versions of selected top papers of the MediterraneanConference on Power Generation, Transmission, Distribution and Energy Conversion(MEDPOWER), held in Dubrovnik in 2018. The 11th edition was technically co-sponsored byIET with a goal of gathering professional power engineers, technicians, researchers,scholars, computer scientists, and other industry specialists and encouraging theexchange ideas about state-of-the-art developments in academia and industry, focusing onall aspects of power system operation, integration of ICT and energy systems, as well asaddressing challenges in energy markets, regulation, and power system management. Intotal the over 200 paper proposals were submitted to the conference, 156 accepted and147 presented (with additional 50 papers presented in Special sessions of theconference). Out of all those papers, authors of top reviewer-rated papers were invitedto expand their work and submit their research to IET Renewable PowerGeneration. In the end 12 papers have been accepted for publication in thisSpecial Section. Accepted papers forming this issue reflect the importance of the paradigm of energy transitions shift towards end-users, analysing different technical and economic aspects of (distributed) generation units and their interaction with the upstream system or network. Interestingly, 5 out of 12 papers propose novel ideas for the operation of the AC microgrids, showing that the link between optimal investment or operation and real-time control aspects are still insufficiently researched [7-11]. Furthermore, 2 papers focus on aspects of connecting and operating distributed, renewable, generation to the system [12, 13], 2 discuss different distributed generation market participation models [14, 15] while 3 deal with technical aspects of power plant and generator operation [16, 17] or production forecasting [18]. Interestingly, majority of papers accepted for publication tend to provide practical solutions for real-life situations and often support the modelling aspect with real measurements. The Guest Editorial Board would like to thank IET Renewable Power Generation forproviding the opportunity to organise this Special Section, the authors for theirinnovative and valuable contributions, and the reviewers for their prompt andcomprehensive feedback and suggestions. Special thanks go to the Editor-in-Chief, DavidInfield, and Managing Editor, Jessica Bristow, for the excellent and continuous supportin putting together this Special Section. Guest Editorial board, Tomislav Capuder, Igor Kuzle and Hrvoje Pandžić, acknowledge the support of Croatian Science foundation through their financing of the projects IMAGINE, FLEXIBASE and WINDLIPS. Lead Guest Editor Tomislav Capuder Faculty of Electrical Engineering and Computing, University of Zagreb E-mail: tomislav.capuder@fer.hr Guest Editors Igor Kuzle Faculty of Electrical Engineering and Computing, University of Zagreb E-mail: igor.kuzle@fer.hr Hrvoje Pandžić Faculty of Electrical Engineering and Computing, University of Zagreb E-mail: hrvoje.pandzic@fer.hr References 1Directive 2009/28/EC of the European Parliament and of the Council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending the subsequently repealing Directives 2001/77/EC and 2003/30/EC, 2009 22030 Energy Strategy, (n.d.). Available at https://ec.europa.eu/energy/node/163, accessed 20 April 2016 3European Commission Directorate-General for Economic and Financial Affairs, Member States’ Energy Dependence: An Indicator -Based Assessment, 2013 4Fergusson, M., Mackay, E., Skinner, I.: ‘ Over a barrel reducing the UK and Europe's oil dependency’, 2006. Available at http://www.greenpeace.org.uk/MultimediaFiles/Live/FullReport/8094.pdf 5International Renewable Energy Agency, Renewable Energy Prospects: United States of America, 2015. Available at http://www.irena.org/remap/irena_remap_usa_report_2015.pdf 6National Renewable Energy Laboratory, Renewable Energy Policy in China: Overview, 2004. Available at http://www.nrel.gov/docs/fy04osti/35786.pdf 7Banis, F., Kjolstad-Poulsen, Madsen, N.H., et al: ‘Active power balancing and frequency stabilization in microgrids using centralized model predictive control’, IET Renew. Power Gener., 2019 8Beires, P.P., Moreira, C.L., Lopes, J.P., et al: ‘Defining connection requirements for autonomous power systems’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0430 9Bintoudi, A., Zyglakis, L., Tsolakis, A.C., et al: ‘MAS-based adaptive control scheme for AC microgrids with increased fault-tolerance needs’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0468 10Carvalho, L.M., Moreira, C., Castro, M.V.: ‘Hierarchical optimisation strategy for energy scheduling and volt/var control in autonomous clusters of microgrids’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0357 11Psarros, G., Papathanassiou, S.A.: ‘Evaluation of battery-renewable hybrid stations in small-isolated systems’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0212 12Klaić, Z., Primorac, M., Topić, D., et al: ‘Impact of photovoltaic and biogas power plant on harmonics in distribution network’, IET Renew. Power Gener., 2019 13Ali, Z., Christofider, N., Saleem, K., et al: ‘Performance evaluation and benchmarking of PLL algorithms for grid-connected RES applications’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0434 14Heymann, F., Lopes, M., Silva, J.M., et al: ‘DER adopter analysis using spatial autocorrelation and information gain ratio under different census-data aggregation levels’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0322 15Carriere, T., Vernay, C., Pitaval, S., et al: ‘Strategies for combined operation of PV/storage systems integrated into electricity markets’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0375 16Brezovec, M., Kuzle, I., Krpan, M., et al: ‘Analysis and treatment of power oscillations in hydropower plant Dubrava’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0523 17Jukic, F., Pravica, L., Sumina, D.: ‘Flying start and continuous operation of a permanent magnet wind generator based on discontinuous currents, discrete second-order sliding-mode observer and phase-locked loop’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0461 18Alamaniotis, M., Karagiannis, G.: ‘Application of fuzzy multiplexing of learning Gaussian processes for the interval forecasting of wind speed’, IET Renew. Power Gener., 2019. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0538 Volume14, Issue1January 2020Pages 1-2 ReferencesRelatedInformation

Stochastic multi-objective optimal energy and reactive power dispatch considering cost, loading margin and coordinated reactive power reserve management

In the recent years, modern wind farms (WF) are being increasingly integrated in the power systems. Thanks to the capability curve of doubly-fed induction generator (DFIG) wind turbines, these modern WFs are able to separately supply active and reactive powers. Accordingly, by increasing the penetration of this kind of sources, both voltage stability and reactive power reserve (RPR) management of power system can be affected. This issue makes it important to propose a new methodology for optimal energy and reactive power dispatch in a system with integrated modern WFs in order to effectively take into consideration the capabilities of modern WFs in different aspects of power system operation. Under this perspective, this paper proposes a stochastic multi-objective optimal dispatch (SMO-OD) problem in the presence of modern WFs to make a techno-economic framework for the system operators (SOs). The proposed SMO-OD problem aims at minimizing expected payments of energy and reactive power markets, and maximizing expected RPR and loading margin (LM) in the presence of wind power generation uncertainty. This paper also contributes to the relevant literature by formulating a model which determines the RPR of modern WFs to be included in the management of total RPR of the power system. Also, a coordinated RPR (CRPR) scheme is proposed by using this model. The proposed model benefits from a detailed reactive power output model of the DFIG wind turbines in order to handle real-world power system operation. Two studies are considered in the proposed SMO-OD problem: (i) SMO-OD with uncoordinated RPR provision (SMO-OD-URPR), and (ii) SMO-OD with the CRPR provision (SMO-OD-CRPR). The proposed SMO-OD problem is applied to the IEEE 30-bus test system. Simulation results show that using the proposed model, a proper trade-off is made between technical and economic aspects of power system operation, and considerable LM and RPR are provided. In the proposed SMO-OD-CRPR problem, the value of expected RPR increases compared to SMO-OD-URPR problem, and the DFIG-based WF has more expected RPR to inject to grid under contingency or sudden increased load. Moreover, by increasing the wind penetration level, not only does the value of expected payments of energy and reactive power markets reduce, but also the value of expected LM and RPR increases.

Geographic information system and weather based dynamic line rating for generation scheduling

Transmission line ratings influence the economic and security aspects of power system operation, generation and planning. The use of geographical information systems in power system generation and planning activities is gaining importance. This paper proposes a geographical information system and weather based dynamic line rating (GISWDLR) and investigates its effectiveness in a security constrained unit commitment problem (SCUCP). Here, the dynamic line ratings (DLRs) of conductors at different locations along the transmission line are calculated using the geographic parameters and weather parameters. Thereafter, the minimum value of DLRs at all indentified locations of the transmission line is taken as DLR of the transmission line. Here, binary real coded particle swarm optimization (BRPSO) is employed to solve the SCUCP. The proposed method is validated using the benchmark IEEE 30 bus system. Here, results obtained using the proposed GISWDLR, static line rating (SLR) and conventional UCP are compared. Also, the effectiveness of BRPSO is validated by comparing it with the conventional enhanced priority list based method.

Analyzing Effect of System Inertia on Grid Frequency Forecasting Usnig Two Stage Neuro-Fuzzy System

Frequency forecasting is an important aspect of power system operation. The system frequency varies with load-generation imbalance. Frequency variation depends upon various parameters including system inertia. System inertia determines the rate of fall of frequency after the disturbance in the grid. Though, inertia of the system is not considered while forecasting the frequency of power system during planning and operation. This leads to significant errors in forecasting. In this paper, the effect of inertia on frequency forecasting is analysed for a particular grid system. In this paper, a parameter equivalent to system inertia is introduced. This parameter is used to forecast the frequency of a typical power grid for any instant of time. The system gives appreciable result with reduced error .

Hierarchical Distributed Mixed-Integer Optimization for Reactive Power Dispatch

Abstract One key aspect of power system operation is the minimization of line losses while maintaining voltages within certain limits. Doing so can be achieved through the use of voltage regulators, tap changing transformers, and shunt capacitors. However, both tap changing transformers and/or shunt capacitors are operated in a discrete manner, i.e. the inputs can only take finitely many discrete values. Thus, the problem of minimizing line losses while maintaining voltage stability can be cast as a mixed-integer optimization problem. For large grids or cases where independent entities have concurrent control of the system, distributed optimization provides a solution. The present paper discusses a hierarchically distributed approach; i.e. the problem is partitioned into local subproblems and solved using a mixed-integer extension of the Augmented Lagrangian based Alternating Direction Inexact Newton (ALADIN) algorithm. We present results for the IEEE 14- and 30-bus systems and compare them with previous approaches, such as particle swarm optimization and genetic algorithms.

Network Structure-Based Critical Bus Identification for Power System Considering Line Voltage Stability Margin

Voltage security assessment of power system is an important and all-inclusive aspect of power system operation and preventive control actions. Fast and accurate detection of critical components of the power system is one essential approach for preventing the occurrence of voltage collapse phenomenon. Over the years, several approaches for voltage collapse point identification and prevention have been widely studied using the continuous power flow approach, minimum singular value of eigenvalues, Jacobian matrices, and power transfer concept. In this work, critical node (bus) identification based on power system network structure is proposed. In this approach, the power system is treated as a multidimensional graph with several nodes (buses) linked together by the transmission lines. An improved line voltage stability margin estimator which is based on active and reactive power changes in a power system is used as the weight of each transmission line and an adaptation of the degree of centrality approach is used to determine the criticality of the system buses. A comparative analysis with other bus voltage stability indices is presented to test the suitability of the proposed approach using the IEEE 14, 30, 57 and 118 bus test systems.

Evaluasi Keandalan Perencanaan Pembangkit Wilayah Jawa-Bali dengan Mempertimbangkan Ketidakpastian Peramalan Beban

Power system reliability is one of important aspects of power system operation. Lack of capacity in the generation system will affect reliability level of the power system. System evaluation needs to be done to know whether the system is still reliable to supply the load that is projected to increase 8.2% per year. Java-Bali system evaluation planning period 2015-2024 is conducted in this paper. Load forecast uncertainty (LFU) is one of the parameters that needs to be considered when conducting system planning. It is because load tends to be uncertain. This research uses two scenarios: without and with load forecast uncertainty. Reliability indexes LOLE and LOLP are used to evaluate the Java-Bali system. All calculations are based on a program using MATLAB. The result shows that reliability indexes LOLE and LOLP are higher with considering LFU. It means reliability decreases, rather than planning without considering LFU. Moreover, Java-Bali system reliability indexes meet the PLN’s standard value with the best value acquired in 2019.

A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns

To study climate-related aspects of power system operation with large volumes of wind generation, data with sufficiently wide temporal and spatial scope are required. The relative youth of the wind industry means that long-term data from real systems are not available. Here, a detailed aggregated wind power generation model is developed for the Republic of Ireland using MERRA reanalysis wind speed data and verified against measured wind production data for the period 2001–2014. The model is most successful in representing aggregate power output in the middle years of this period, after the total installed capacity had reached around 500 MW. Variability on scales of greater than 6 h is captured well by the model; one additional higher resolution wind dataset was found to improve the representation of higher frequency variability. Finally, the model is used to hindcast hypothetical aggregate wind production over the 34-year period 1980–2013, based on existing installed wind capacity. A relationship is found between several of the production characteristics, including capacity factor, ramping and persistence, and two large-scale atmospheric patterns – the North Atlantic Oscillation and the East Atlantic Pattern.

Quantitative Frequency Security Assessment for Multi-Machine Power System based on COI frequency

The frequency is one of the instruments for measuring the health status of the power system, due to its ability to anticipate any imbalance between generations and loads. If the generated power is adequate for the system load and losses, then, the system will be in a steady state, otherwise frequency deviates from nominal value due to the mismatch between the generation and load. If the frequency continues to deviate from nominal value, the system may collapse. The assessment of frequency stability level becomes an essential aspect of power system operation and also for projecting the ability of the power system to maintain nominal frequency when subjected to any disturbance. In this paper, a method is proposed to evaluate frequency security of multi-machine power system using transient frequency deviation index (TFDI) which is based on Center of Inertia (COI) referred frequency. The proposed method has been tested on the New England 39- bus test system. Results show that the proposed method takes the advantage of TFDI in accumulating the effect of frequency trajectory deviations. These frequency trajectories may be obtained from the time domain simulation or Wide Area Measurement System (WAMS). The results also show the advantages of COI referred frequency in representing the equivalent frequency of the system. The method would provide a reliable and efficient base for load shedding relays adjustment and operation control.

Optimal reactive power dispatch using hybrid Nelder–Mead simplex based firefly algorithm

Abstract This paper presents a novel hybrid algorithm combining Firefly Algorithm (FA) and Nelder Mead (NM) simplex method for solving power system Optimal Reactive Power Dispatch (ORPD) problems. The ORPD is a very important aspect of power system operation and is a highly nonlinear, non-convex optimization problem, consisting of both continuous and discrete control variables. Like many other general purpose optimization methods, the original FA often traps into local optima and in order to overcome the shortcoming, in this paper, an efficient local search method called NM simplex subroutine is introduced in the internal architecture of the original FA algorithm. The proposed Hybrid Firefly Algorithm (HFA) avoids premature convergence of original FA by exploration with FA and exploitation with NM simplex. The proposed method is applied to determine optimal settings of generator voltages, tap positions of tap changing transformers and VAR output of shunt capacitors to optimize two different objective functions; such as minimization of real power loss and voltage deviations. The program is developed in Matlab and the proposed hybrid algorithm is examined on two standard IEEE test systems for solving the ORPD problems. For validation purpose, the results obtained with the proposed approach are compared with those obtained by other methods. It is observed that the proposed method has better convergence characteristics and robustness compared to the original version of FA and other existing methods. It is revealed that the proposed hybrid method is able to provide better solutions.

Measuring the volatility of wholesale electricity prices caused by wind power uncertainty with a correlation model

There is an increasing need to understand the impact of high-penetration wind power on various aspects of power system operation. This study presents a methodology to evaluate the impact of market price volatility on intermittent wind power. The proposed methodology first considers the uncertainty of wind power using a probabilistic distribution of wind speed in combination with the rated speed–MW curve. The correlation among different wind power plants is also modelled. With these statistical models, a Monte Carlo simulation (MCS) approach can be used to assess the probabilistic distribution of the price signals, that is, the probabilistic locational marginal pricing (LMP) distribution. Since the computational effort of MCS is intensive, a lookup table is proposed as preprocessing to greatly simplify the MCS. The proposed approach is tested with the PJM 5-bus system and the IEEE 118-bus system. Rules of thumb are drawn regarding the probabilistically calculated LMP and the correlation coefficients.

Computational auction mechanisms for restructured power industry operation

From the Publisher: Computational Auction Mechanisms for Restructured Power Industry Operation outlines the application of auction methods for all aspects of power system operation, primarily for a competitive environment. A complete description of the industry structure as well as the various markets now being formed is given. A thorough introduction to auction basics is included to explain how auctions have grown in other industries. Auction methods are compared to classical techniques for power system analysis, operations, and planning. The material is useful for students performing research on the new business environment based on competition. Regulators will find information on initial methods to design and evaluate market systems, and power exchange and financial analysts will find information on the interdependence of markets and power system based techniques for risk management. This information compares the new business environment solutions with old business environment solutions. Computational Auction Mechanisms for Restructured Power Industry Operation provides a first introduction to how electricity will be traded as a commodity in the future.