National System Operator Research Articles

Even‐Order Harmonic Distortion Observations During Multiple Geomagnetic Disturbances: Investigation From New Zealand

AbstractLarge geomagnetic storms are a space weather hazard to power transmission networks due to the effects of Geomagnetically Induced Currents (GICs). GIC can negatively impact power transmission systems through the generation of even‐order current and voltage harmonics due to half‐cycle transformer saturation. This study investigates a decade of even‐order voltage total harmonic distortion (hereon referred to as Even‐Order Total Harmonic Distortion (ETHD)) observations provided by Transpower New Zealand Ltd., the national system operator. We make use of ETHD measurements at 139 locations throughout New Zealand, monitored at 377 separate circuit breakers, focusing on 10 large geomagnetic disturbances during the period 2013–2023. Analysis identified 5 key substations, which appeared to act as sources of ETHD. The majority of these substations include single phase transformer banks, and evidence of significant GIC magnitudes. The ETHD from the source substations was found to propagate into the surrounding network, with the percentage distortion typically decaying away over distances of 150–200 km locally, that is, at a rate of −0.0043 %km−1. During the study period some significant changes occurred in the power network, that is, removal of the Halfway Bush (HWB) single phase bank transformer T4 in November 2017, and decommissioning of the New Plymouth substation in December 2019. Decommissioning of these two assets resulted in less ETHD occurring in the surrounding regions during subsequent geomagnetic storms. However, ETHD still increased at HWB with increasing levels of GIC, indicating that three phase transformer units were still susceptible to saturation, albeit with about 1/3 of the ETHD percentage exhibited by single phase transformers.

An Overview of Short-Term Load Forecasting for Electricity Systems Operational Planning: Machine Learning Methods and the Brazilian Experience

The advent of smart grid technologies has facilitated the integration of new and intermittent renewable forms of electricity generation in power systems. Advancements are driving transformations in the context of energy planning and operations in many countries around the world, particularly impacting short-term horizons. Therefore, one of the primary challenges in this environment is to accurately provide forecasting of the short-term load demand. This is a critical task for creating supply strategies, system reliability decisions, and price formation in electricity power markets. In this context, nonlinear models, such as Neural Networks and Support Vector Machines, have gained popularity over the years due to advancements in mathematical techniques as well as improved computational capacity. The academic literature highlights various approaches to improve the accuracy of these machine learning models, including data segmentation by similar patterns, input variable selection, forecasting from hierarchical data, and net load forecasts. In Brazil, the national independent system operator improved the operation planning in the short term through the DESSEM model, which uses short-term load forecast models for planning the day-ahead operation of the system. Consequently, this study provides a comprehensive review of various methods used for short-term load forecasting, with a particular focus on those based on machine learning strategies, and discusses the Brazilian Experience.

Proposition of a hydro-economic model applied to the water conflict in the Alto São Marcos to optimize water allocation

The use of water as the main input for agricultural and livestock production and electricity usually reveals conflicts between the demanding sectors when it is relatively scarce. In this scenario, the conflict in the Alto São Marcos basin is notable in Brazil due to the inefficiency of meeting the demand for water for the irrigation and electric sector, involving the national domain, the states of Minas Gerais, Goiás, and the Federal District. Thus, the objective of this work is the construction and application of a hydro-economic model that optimizes the allocation of water between these sectors and has as a parameter the economic value of the resource defined by the maximization of intersectoral profits. The methodology employed was inspired by the works proposed by Fujisawa (2016) and Silva (2017), using non-linear programming under the contour conditions of Karush-Kuhn-Thucker (1951) in a deterministic scenario. An objective function is proposed that minimizes the operational cost of a scarcity of irrigated perimeters while maximizing the economic benefit of energy production. The data used are derived from ANA (National Water Agency) regulations and the hydroelectric plant's operating history made available by ONS (National System Operator) and CCEE (Electric Energy Trading Chamber). From the results obtained, there was a reduction in the value of water for irrigators, considering the value once delimited by the real dynamics, under the equivalent availability of inputs, an indication of the efficiency of the proposed seasonal dynamics. However, despite the economic rationale inserted, the reproduction of the prioritization of use for the irrigating sector, within the established limits, penalized the remuneration and generation of Batalha HPP. Thus, the aim is, through modeling, to contribute to the measurement of the economic effects of the negotiated allocation of water.

Optimal Sizing of a Photovoltaic/Battery Energy Storage System to Supply Electric Substation Auxiliary Systems under Contingency

Electric substations (ESS) are important facilities that must operate even under contingency to guarantee the electrical system’s performance. To achieve this goal, the Brazilian national electricity system operator establishes that alternating current (AC) auxiliary systems of ESS must have, at least, two power supplies, and in the case of failure of these sources, an emergency generator (EG) must at least supply energy to the essential loads. In order to improve the availability of auxiliary systems, a microgrid with other sources, such as photovoltaic (PV) systems and Battery Energy Storage Systems (BESS), can be an alternative. In this case, an economical optimization of the PV/BESS system must be addressed considering the costs associated with the installation and maintenance of equipment, and the gains from the credits generated by the photovoltaic system in the net metering scheme. In this paper, the size of the BESS system was determined to supply energy to the load of auxiliary systems of an ESS, as well as a PV system to achieve a null total cost. Furthermore, multi-objective optimization using the genetic algorithm technique was employed to optimize the size of the hybrid PV/BESS to minimize the investment cost and time when the demand was not met. Simulations under different scenarios of contingency were allowed to obtain the Pareto frontier for the optimal sizing of a PV/BESS system to supply energy to AC auxiliary systems in an ESS under contingency.

Discussion on the Interaction between Transformers and the Power Systems

A general increase in transformer dielectric failures in the Brazilian transmission system, some of them with no specific causes, motivated the start up of a Cigré Joint Working Group JWG A2/C4–03 Electrical Transient Interaction between Transformers and the Power System. This group has been gathered to assess and discuss the different types of electrical transient interaction between transformers and other components of the T&D power system that could explain some of these failures. The main focus of the JWG is to pursue an improvement of the system reliability based on recommendations regarding the electrical transient interaction between transformers and the power system. This takes into account the necessity of detailed transient studies looking for an upgrade in equipment specifications, system planning and operation criteria. The working group started its activities in May 2005 and is composed of around 30 members, representing utilities, research center, manufacturers, universities and the national grid system operator. The objective of this paper is to present the work that has been carried out so far by the JWG including the main discussions and the conclusions already reached.

Synergies Between Low Carbon Technologies in a Large-Scale MV/LV Distribution System

Power distribution systems are experiencing large deployment of behind-the-meter distributed generation and storage along with electrified transport and heat, requiring fundamental changes in planning and operation. There are increasing efforts to directly model real large-scale networks and conduct detailed analysis beyond conventional practices. Utilizing optimization methods to leverage distributed generation to the benefit of the distribution system and all customers is the ideal. However, progress towards adoption of such controls by system operators are impeded by concerns over privacy, regulatory and market issues in many jurisdictions. While these issues are being addressed, there may be opportunity to exploit the synergistic effect of mixing low carbon technologies (LCT). This paper presents a large-scale medium voltage (MV)-low voltage (LV) integrated system model building, scenario determination and analysis approach for distribution systems. Data with different formats from several databases are used in model building. In collaboration with the national distribution system operator (DSO) in Ireland (ESB Networks), a pilot study is conducted for a rural system in the Southwest of Ireland, highlighting the challenges of directly modelling real distribution systems and investigating the potential synergies between multiple low carbon technologies.

Time series forecasting using ensemble learning methods for emergency prevention in hydroelectric power plants with dam

In hydroelectric plants, the responsibility for the operation of the reservoirs typically lies with the national system operator, who controls the level of the reservoirs based on a stochastic problem for the economy of the potential energy available in the reservoir. However, in an emergency, the responsibility for the operation and control of the reservoir becomes the plant’s management. To have a faster decision-making process, it is important to have a forecast of water affluence in relation to the turbine capacity and use of the spillway. With the objective of evaluating the forecast increase in the level of the reservoir of a hydroelectric plant, this paper compares the use of the bagging, boosting, random subspace, bagging plus random subspace, and stacked generalization ensemble learning models to analyze this problem. The case study is based on data from a 690 MW hydroelectric plant, which has a 94 km reservoir and a 185 m high dam. The random subspace and stacking models had the best results for lower error, with a low time required for convergence in relation to the other models. The ensemble models resulted in greater accuracy for the assessed problem than long short-term memory.

Medium-term projection for the National Hydro-Electrical System using wavelets

The Brazilian energetic matrix is predominantly based on hydroelectric plants and its planning is very sensitive to climate variability in different time scales. Natural Affluent Energy (NAE) is an established planning tool to project different scenarios of possible energy production, especially in an integrated system. This work aims to fill a gap between short-term (seasonal/ interannual) and long-term (climate change) planning scales by realizing NAE medium-term projections for the Brazilian National Interconnected System basins. The historical NAE series provided by the National System Operator was used for the years 1931 to 2014. The series was divided into two periods: from 1931 to 2003 for verification, and from 2004 to 2014 for calibration. The Wavelets Auto-Regressive (WAR) model was applied from low- and medium-frequency bands. The band signal was analyzed and the NAE was projected for the years 2014 to 2024. A relationship of the NAE variability with the Pacific Decadal Oscillation (PDO) climate index and the Atlantic Multidecadal Oscillation (AMO) was verified.

Energy and reserve strategic offers in regional electricity markets: A complementarity approach

Trade between electric power systems is driven by price differences in the corresponding electricity markets. When cross-border trading involves two or more markets, a regional electricity market could be put in place with different types of agreements and regulations. These cross-border exchanges could imply higher economic welfare for each zone (e.g. country) and a re-distribution of the consumers’ surpluses, producers’ profits and congestion rents within each zone, hindering regional integration. However, a zonal operator (i.e. national operator or system operator —that we introduce in this work) could capture social economic-welfare derived from cross-border trading through managing energy-and-reserve strategic offers to be submitted to the regional electricity market. With this in mind, a zonal “strategic” operator, using the proposed model in this paper, could modify zonal generators’ offers in the process when they are informed to the regional market. This model is implemented through a bilevel programming problem, where, the upper-level optimization problem seeks the zonal social-welfare maximization of a single zone by means of managing producer’s offers, subject to the regional social-welfare maximization, that is represented in the lower-level problem. Energy and reserve market prices and dispatches are obtained through a centralized coordination scheme for regional market-clearing in coherence with welfare optimization. Using KKT conditions, this bilevel model is reduced to a mixed-integer linear programming problem which may be solved using a standard branch-and-cut algorithm. Results from an illustrative example and a case study are hereby reported and analyzed.

The description and evaluation of technical incident risk on the National Power Grid in the context of power safety growth

In the context of increasing the importance of power safety for national security, the security of power systems within the National Power Grid, must be an objective of major and constant interest for the national transmission and system operator. Evolutions in recent decades have shown the increase in vulnerabilities caused by: failure, destruction and/or disruption of technological infrastructures caused by acts of terrorism, natural disaster, negligence in service, work accidents of technical nature, technical incidents, criminal activities and lack of investment. For the critical analysis of the National Power Grid, 4 (four) possible risk scenarios with effects of instability of the power safety and with major effects on the national security were identified, described and evaluated: Risk Scenario 1 - Technical Incident, Risk Scenario 2 - Damage: Technical Incident Sequence, Risk Scenario 3 - Damage: Natural Disaster, Risk Scenario 4 - Damage: Terrorist Attack. The purpose of the paper is to describe and evaluate the Risc Scenario 1- Technical Incident (which is most prevalent) on the power substations and to prevent potential disturbances in the safety of the power supply to consumer.

Analyzing and Forecasting Zonal Imbalance Signs in the Italian Electricity Market

In this paper, within the Italian electricity market, we analyse the features and the dynamics of the imbalance sign, defined as the sign of the algebraic sum of energy bought and sold by the national Transmission and System Operator during the real-time balancing of the electric network. The analyses provide evidence that the probability of having a positive (negative) sign exhibits a serial dependence structure and a dependence on the load periods, as well as on past history. Based on this evidence, we build a suitable model for zonal sign dynamics, and we use it for an out-of-sample forecasting exercise concerning the probability of a positive imbalance sign, nt. The results show that the zonal imbalance sign is ‘predictable.’ An economic evaluation of the benefits of using the proposed model is also provided.

EU energy policies achievement by industries in decentralized areas

Energy Roadmap outlined by the European Commission sets out several routes for a more sustainable, competitive and secure energy system in 2050. All the outlined scenarios consider energy efficiency, renewable energy, nuclear energy and carbon capture and storage. In this paper, more attention has been devoted to the energy efficiency issue, by the identification of new micro and small networks opportunity fed by hybrid plants in the North-East of Italy. National energy balance and national transmission system operator data allowed to collect industrial energy consumptions data on the investigated area. Applying industrial statistics to the local energy needs allows to collect a dataset including consumption information by factory and by company structure (size and employees) for each industrial sector highlighting the factory density in the area. Preliminary outcomes from the model address to the exploitation of local by-product for energy purposes.

Decision support for restoration of interconnected power systems using tie lines

Existing system restoration strategies are primarily based on operators’ experience with no specific decision support tools. Restoration of interconnected grids in Europe is decentralised; restoration planning is limited to within the area of control for each national transmission system operator (TSO). Although coordination of restorative actions between TSOs is encouraged, few agreements exist. This study proposes a decision support methodology for system operators and restoration planners for restoration of interconnected grids. Solutions to optimal and coordinated utilisation of tie lines (TLs) are proposed. The proposed tool facilitates collaboration between TSOs affected by wide area blackouts. The decision support tool allows to adaptively develop restoration strategies based on system conditions, available resources and operating constraints. Optimisation algorithms are proposed to determine the optimal utilisation of TLs and/or black-start (BS) units to crank non-BS units. Optimal power flow problems are formulated for utilisation of TLs. They offer solutions for neighbouring TSOs to determine the extent to which TLs can be used without violating constraints. The proposed decision support tool is tested with IEEE 39-bus system.

Preserving Ireland's iconic railway viaducts

Ireland's national railway system operator Iarnród Éireann has developed innovative repair and strengthening techniques to retain, preserve and extend the longevity of several of its aging bridges. Of those, three nineteenth-century structures rehabilitated in the past decade stand out as iconic structures in their own setting and will now continue to provide service into the foreseeable future. Innovative bespoke engineering, three-dimensional finite-element modelling techniques and laboratory research and testing were used to confirm the theoretical hypothesis. This achieved a significant increase in the lifespan of these structures that would otherwise have been deemed life-expired. This paper gives an overview of each of the projects, describing the existing structure and the challenges overcome in their design, repair and rehabilitation.

Walking the Wall

Walking the Wall

Incorporating Forecasts of Rainfall in Two Hydrologic Models Used for Medium-Range Streamflow Forecasting

This study reports on the performance of two medium-range streamflow forecast models: (1) a multilayer feed-forward artificial neural network; and (2) a distributed hydrologic model. Quantitative precipitation forecasts were used as input to both models. The Furnas Reservoir on the Rio Grande River was selected as a case study, primarily because of the availability of quantitative precipitation forecasts from the Brazilian Center for Weather Prediction and Climate Studies and due to its importance in the Brazilian hydropower generating system. Streamflow forecasts were calculated for a drainage area of about 51,900 km(2), with lead times up to 12 days, at daily intervals. The Nash-Sutcliffe efficiency index, the root-mean-square error, the mean absolute error, and the mean relative error were used to assess the relative performance of the models. Results showed that the performance of streamflow forecasts was strongly dependent on the quality of quantitative precipitation forecasts used. The artificial neural network (ANN) method seemed to be less sensitive to precipitation forecast error relative to the distributed hydrological model. Hence, the latter presented a better skill in flow forecasting when using the more accurate perfect precipitation forecast. The conceptual hydrological model also demonstrates better forecast skill than ANN models for longer lead times, when the representation of the rainfall-runoff process and of the water storage in the watershed becomes more important than the flow routing along the drainage network. In addition, results obtained by incorporating a quantitative precipitation forecast in both models performed better than the current streamflow obtained by the Brazilian national electric system operator using statistical models which do not utilize information on precipitation, whether observed or forecast. (Less)

Inclusão de restrições dinâmicas no problema de planejamento de potência reativa

Este artigo apresenta uma nova metodologia para o planejamento da operação dos Sistemas Elétricos de Potência (SEP), na qual restrições dinâmicas de impactos em geradores são incorporadas ao problema de Fluxo de Potência Ótimo (FPO). Neste novo modelo, o transitório no instante da contingência é incorporado ao FPO como uma restrição operacional a fim de manter os impactos nos eixos dos geradores nos níveis recomendados pelo Operador Nacional do Sistema (ONS). Desta forma o tradicional problema de planejamento de potencia reativa incorpora os impactos nos eixos dos geradores do SEP quando ocorre uma contingência. O problema é formulado usando a metodologia primal-dual de pontos interiores associada à técnica de decomposição matemática de Benders. Estudos de casos com os sistemas IEEE-14 e IEEE-118 são realizados para mostrar o desempenho da metodologia proposta.

Previsões de Curto Prazo de Vazão Afluente ao Reservatório de Furnas Utilizando Redes Neurais Artificiais

This study presents the evaluation of the performance of a streamflow forecast model based on a feedforward multilayer artificial neural network. Available rainfall forecasts were considered as additional inputs to the model. The Furnas dam, in the Rio Grande basin, was selected as the case study, primarily because of the availability of short-term rainfall forecast data produced in a previous study using an ETA model. Streamflow forecasts have a twelve day horizon at daily intervals (lead times from 1 to 12 days). A new methodology for training and validating the Artificial Neural Network is proposed based on perfect rainfall forecasts (considering observed rainfall as a forecast). Results show that benefits could be achieved in inflow forecasts to Furnas dam by incorporating rainfall forecasts. Improvement in inflow forecasts using the proposed model depends on quality of rainfall forecasts. However, forecast performance was better than the current streamflow forecasts produced by the Brazilian national electric system operator. The performance of the streamflow forecast model using ETA rainfall forecast and perfect forecast were similar up to the fifth lead time. Meanwhile, quality of streamflow forecasts improves when using perfect rainfall forecast from lead time six to twelve, compared to that using ETA forecast

An optimization problem in the electricity market

New types of optimization problems are faced by the generating companies that operate on deregulated electricity markets. The characteristics of these problems depend on the various market structures. In the framework of the recently settled Italian electricity market, one of these new problems is the transition from hourly energy programs, defined by the market, to more detailed power generation dispatches, defined for intervals of 15 min. Such a more detailed plan is needed on the one hand by the national system operator (Terna, Rete Elettrica Nazionale) for the assessment of power system stability and security, and on the other hand by the power plant operators for its implementation. The transition procedure should respect the hourly energy constraints and take the main operating constraints of the generating units into account. The paper presents possible solutions of the problem through linear optimization models and reports computational results on real-world instances.

Flexibility valuation in the Brazilian power system: A real options approach

This paper presents a valuation study of operational flexibility in the complex Brazilian Power System. Thermopower plants represent operational flexibility for the national system operator provided they can be dispatched in dry periods to supply part of the load when reservoir waters are too low. Deficit costs can be avoided as a result. We have adopted a real options approach to calculate the fair value of a financial subsidy to be paid to thermal generators for their availability to the system. A financial subsidy is mandatory for their economic feasibility and, therefore, for increased thermopower capacity in the Brazilian Power System. This is why this policy is currently being studied by Brazil's federal government. In order to illustrate our modeling we have run the model for the southeast subsystem. We found a flexibility value of US$4.52 billion, which represents US$497/MW per year. This means that a 100 MW thermopower plant should receive US$49,700 for each year of its economic lifetime as a fair premium incentive to investments.