Uncovering Contributing Factors to Interruptions in the Power Grid: An Arctic Case

Electric failures are a problem for customers and grid operators. Identifying causes and localizing the source of failures in the grid is critical. Here, we focus on a specific power grid in the Arctic region of Northern Norway. First, we collected data pertaining to the grid topology, the topography of the area, the historical meteorological data, and the historical energy consumption/production data. Then, we exploited statistical and machine-learning techniques to predict the occurrence of failures. The classification models achieve good performance, meaning that there is a significant relationship between the collected variables and fault occurrence. Thus, we interpreted the variables that mostly explain the classification results to be the main driving factors of power interruption. Wind speed of gust and local industry activity are found to be the main controlling parameters in explaining the power failure occurrences. The result could provide important information to the distribution system operator for implementing strategies to prevent and mitigate incoming failures.

An Intelligent Grid Network Based on Cloud Computing Infrastructures

This chapter covers important topics in development of efficient energy girds. Inefficient power generation, unbalanced consumption patterns that lead to underutilization of expensive infrastructure on the one hand, and severe overload on the other, as well as urgent issues of national and global concern such as power system security and climate change are all driving this evolution. As the smart grid concept matures, we'll see dramatic growth in green power production: small production devices such as wind turbines and solar panels or solar farms, which have fluctuating capacity outside of the control of grid operators. Small companies that specialize in producing power under just certain conditions will boom in forthcoming years. Energy is stored in the storage during low-cost periods, and the stored energy is used during high-cost periods to avoid the expensive draw from the grid. The authors evaluate the impact of large-scale energy storage adoption on grid electricity demand.

Energy flexible commercial buildings and the electricity grid

<p>New Zealand’s energy and electricity system is likely to undergo serious changes with climate change and the decarbonisation of the grid playing a significant role. Research in New Zealand around flexibly managing the electricity grid using buildings has focused on thermoelectric appliances in the residential sector while there has been limited research and quantification of the energy flexibility offered by commercial buildings. Despite this, managing the grid using energy flexible commercial buildings represents an opportunity to achieve meaningful reductions in electricity demand from buildings that are far less numerous than residential buildings. The aim of this thesis was to establish whether energy flexible commercial buildings in New Zealand can maintain the current quality of indoor thermal comfort and achieve reductions in demand that are sufficiently large that grid operators consider them significant contributors to grid management. By understanding the contribution, we can understand whether energy flexible commercial buildings are worth further investigation. In this thesis, energy flexibility means the ability for a building to manage its demand and generation according to user needs, grid needs, and local climate conditions. Energy flexibility in commercial buildings could then support the integration of more variable renewable energy sources and increase demand response capability which is a cost-effective way to manage network constraints and reduce non-renewable electricity generation. Case studies of New Zealand commercial buildings represented as Building Energy Models (BEMs) were simulated under energy flexible operation in a building performance simulation software (EnergyPlus). The selected case studies were small commercial buildings less than 1,499m² in size and which all contained heat pumps. The buildings were of office, retail, and mixed-use types. Two simple energy flexibility strategies were simulated in the buildings and the results from each building were then aggregated and extrapolated across the New Zealand commercial building stock. The strategies simply shifted and shed heating electricity demand. This was done to test whether implementing basic energy flexibility strategies have the potential to reduce electricity demand by a meaningful magnitude. At best the commercial building stock’s peak demand could reduce by 177MW by energy flexibly operating 45% of the commercial building stock, this was equivalent to around 11,700 buildings. In this scenario heating was shifted to start 150 minutes earlier in the morning. The study concluded that there is energy flexibility potential in New Zealand commercial buildings that results in demand reductions sufficiently large enough for grid operators to consider significant for grid management. This could be achieved without seriously jeopardising the current quality of indoor thermal comfort and warrants further investigation into energy flexible commercial buildings. This thesis also presented a refined methodology and energy modelling practice that could be used by other researchers to model and evaluate energy flexible buildings without the need to recreate the same methodology.</p>

Energy flexible commercial buildings and the electricity grid

<p>New Zealand’s energy and electricity system is likely to undergo serious changes with climate change and the decarbonisation of the grid playing a significant role. Research in New Zealand around flexibly managing the electricity grid using buildings has focused on thermoelectric appliances in the residential sector while there has been limited research and quantification of the energy flexibility offered by commercial buildings. Despite this, managing the grid using energy flexible commercial buildings represents an opportunity to achieve meaningful reductions in electricity demand from buildings that are far less numerous than residential buildings. The aim of this thesis was to establish whether energy flexible commercial buildings in New Zealand can maintain the current quality of indoor thermal comfort and achieve reductions in demand that are sufficiently large that grid operators consider them significant contributors to grid management. By understanding the contribution, we can understand whether energy flexible commercial buildings are worth further investigation. In this thesis, energy flexibility means the ability for a building to manage its demand and generation according to user needs, grid needs, and local climate conditions. Energy flexibility in commercial buildings could then support the integration of more variable renewable energy sources and increase demand response capability which is a cost-effective way to manage network constraints and reduce non-renewable electricity generation. Case studies of New Zealand commercial buildings represented as Building Energy Models (BEMs) were simulated under energy flexible operation in a building performance simulation software (EnergyPlus). The selected case studies were small commercial buildings less than 1,499m² in size and which all contained heat pumps. The buildings were of office, retail, and mixed-use types. Two simple energy flexibility strategies were simulated in the buildings and the results from each building were then aggregated and extrapolated across the New Zealand commercial building stock. The strategies simply shifted and shed heating electricity demand. This was done to test whether implementing basic energy flexibility strategies have the potential to reduce electricity demand by a meaningful magnitude. At best the commercial building stock’s peak demand could reduce by 177MW by energy flexibly operating 45% of the commercial building stock, this was equivalent to around 11,700 buildings. In this scenario heating was shifted to start 150 minutes earlier in the morning. The study concluded that there is energy flexibility potential in New Zealand commercial buildings that results in demand reductions sufficiently large enough for grid operators to consider significant for grid management. This could be achieved without seriously jeopardising the current quality of indoor thermal comfort and warrants further investigation into energy flexible commercial buildings. This thesis also presented a refined methodology and energy modelling practice that could be used by other researchers to model and evaluate energy flexible buildings without the need to recreate the same methodology.</p>

Determination of Maximum Acceptable Standing Phase Angle across Open Circuit Breaker as an Optimisation Task

There are several threats that require the control of the conditions of switching operations in the transmission grid. They result mainly from the negative effects of the high-value current, which may appear after the breaker is closed. Problems considering closing the power circuit breakers on a large standing phase angle (SPA) are often formulated by grid operators. The literature most often discusses the problem of SPA reduction, which allows the system to be restored without the risk of damaging the turbogenerator shafts. This reduction can be achieved by various operational solutions; most often, it is the appropriate adjustment of active power generation, sometimes backed up by partial load shedding. The subject of the presented article is a slightly different approach to the SPA problem. The method of determining the maximum value of SPA for which the connection operation allows to avoid excessive transitional torques was presented. With this approach, finding the maximum value of SPA between the two considered system nodes is treated as an optimisation task. In order to solve it, the original heuristic optimisation method described in the article was applied.

Modeling the Impact of Electric Vehicle Charging Infrastructure on Regional Energy Systems: Fields of Action for an Improved e-Mobility Integration

Since e-Mobility is on the rise worldwide, large charging infrastructure networks are required to satisfy the upcoming charging demand. Planning these networks not only involves different objectives from grid operators, drivers and Charging Station (CS) operators alike but it also underlies spatial and temporal uncertainties of the upcoming charging demand. Here, we aim at showing these uncertainties and assess different levers to enable the integration of e-Mobility. Therefore, we introduce an Agent-based model assessing regional charging demand and infrastructure networks with the interactions between charging infrastructure and electric vehicles. A global sensitivity analysis is applied to derive general guidelines for integrating e-Mobility effectively within a region by considering the grid impact, the economic viability and the Service Quality of the deployed Charging Infrastructure (SQCI). We show that an improved macro-economic framework should enable infrastructure investments across different types of locations such as public, highway and work to utilize cross-locational charging peak reduction effects. Since the height of the residential charging peak depends up to 18% on public charger availability, supporting public charging infrastructure investments especially in highly utilized power grid regions is recommended.

Research and Application of Standard Oil Dispensing System for Dissolved Gases in Transformer Oil

Measuring the content of dissolved gas components in transformer insulating oil by gas chromatography is an important means to judge the internal potential faults of oil filled electrical equipment in the process of operation supervision. The necessary work skills of power grid operators include the ability to detect the content of dissolved gas in transformer oil and judge the operation state of transformer. This paper introduces a preparation method and equipment of transformer standard oil. It can quickly prepare standard oils with various gas component contents. The standard oil quantity value is accurate, the data stability period is greater than 90 days, and the uncertainty is less than 5%. The equipment can be used for training and evaluation of transformer oil gas chromatographic analysis practitioners and calibration of transformer oil on-line gas chromatograph.

Towards online optimization for power grids

In this note, we discuss potential advantages in extending distributed optimization frameworks to enhance support for power grid operators managing an influx of online sequential decisions. First, we review the state-of-the-art distributed optimization frameworks for electric power systems, and explain how distributed algorithms deliver scalable solutions. Next, we introduce key concepts and paradigms for online optimization, and present a distributed online optimization framework highlighting important performance characteristics. Finally, we discuss the connection and difference between offline and online distributed optimization, showcasing the suitability of such optimization techniques for power grid applications.

p-Multilevel Preconditioners for HHO Discretizations of the Stokes Equations with Static Condensation

We propose a p-multilevel preconditioner for hybrid high-order (HHO) discretizations of the Stokes equation, numerically assess its performance on two variants of the method, and compare with a classical discontinuous Galerkin scheme. An efficient implementation is proposed where coarse level operators are inherited using $$L^2$$ L 2 -orthogonal projections defined over mesh faces and the restriction of the fine grid operators is performed recursively and matrix-free. Both h- and k-dependency are investigated tackling two- and three-dimensional problems on standard meshes and graded meshes. For the two HHO formulations, featuring discontinuous or hybrid pressure, we study how the combination of p-coarsening and static condensation influences the V-cycle iteration. In particular, two different static condensation procedures are considered for the discontinuous pressure HHO variant, resulting in global linear systems with a different number of unknowns and matrix non-zero entries. Interestingly, we show that the efficiency of the solution strategy might be impacted by static condensation options in the case of graded meshes.

PRONÓSTICO DE DEMANDA DE ENERGÍA ELÉCTRICA USANDO PROCESOS GAUSSIANOS: UN ANÁLISIS COMPARATIVO

Abstract—Load demand forecasting is an essential component for planning power systems, and it is an invaluable tool to grid operators or customers. Many methods have been proposed to provide reliable estimates of electric load demand, but few methods can address the problem of predicting energy demand from a probabilistic point of view. One of them is the Gaussian processes (GP) that considering an adequate covariance function are suitable tools to carry out this load forecasting task. In this article, we show how to use Gaussian processes to predict elec- trical energy demand. Additionally, we thoroughly test various covariance functions and provide a new one. The performance of the proposed methodology was tested on two real data sets, showing that GPs are competitive alternatives for short-term load demand forecasting compared to other state-of-the-art methods