Microgrids: Planning, Protection and Control

This Special Issue will include papers related to the planning, protection, and control of smart grids and microgrids, and their applications in the industry, transportation, water, waste, and urban and residential infrastructures. Authors are encouraged to present their latest research; reviews on topics including methods, approaches, systems, and technology; and interfaces to other domains such as big data, cybersecurity, human–machine, sustainability, and smart cities. The planning side of microgrids might include technology selection, scheduling, interconnected microgrids, and their integration with regional energy infrastructures. The protection side of microgrids might include topics related to protection strategies, risk management, protection technologies, abnormal scenario assessments, equipment and system protection layers, fault diagnosis, validation and verification, and intelligent safety systems. The control side of smart grids and microgrids might include control strategies, intelligent control algorithms and systems, control architectures, technologies, embedded systems, monitoring, and deployment and implementation

Challenges to the Integration of Renewable Resources at High System Penetration

Successfully integrating renewable resources into the electric grid at penetration levels to meet a 33 percent Renewables Portfolio Standard for California presents diverse technical and organizational challenges. This report characterizes these challenges by coordinating problems in time and space, balancing electric power on a range of scales from microseconds to decades and from individual homes to hundreds of miles. Crucial research needs were identified related to grid operation, standards and procedures, system design and analysis, and incentives, and public engagement in each scale of analysis. Performing this coordination on more refined scales of time and space independent of any particular technology, is defined as a “smart grid.” “Smart” coordination of the grid should mitigate technical difficulties associated with intermittent and distributed generation, support grid stability and reliability, and maximize benefits to California ratepayers by using the most economic technologies, design and operating approaches

Optimal Design and Operation Management of Battery-Based Energy Storage Systems (BESS) in Microgrids

Energy storage systems (ESSs) can enhance the performance of energy networks in multiple ways; they can compensate the stochastic nature of renewable energies and support their large-scale integration into the grid environment. Energy storage options can also be used for economic operation of energy systems to cut down system’s operating cost. By utilizing ESSs, it is very possible to store energy in off-peak hours with lower cost and energize the grid during peak load intervals avoiding high price spikes. Application of ESSs will also enable better utilization of distributed energy sources and provide higher controllability at supply/demand side which is helpful for load leveling or peak shaving purposes. Last but not least, ESSs can provide frequency regulation services in off-grid locations where there is a strong need to meet the power balance in different operating conditions. Each of the abovementioned applications of energy storage units requires certain performance measures and constraints, which has to be well considered in design phase and embedded in control and management strategies. This chapter mainly focuses on these aspects and provides a general framework for optimal design and operation management of battery-based ESSs in energy networks

Enabling sustainable power distribution networks by using smart grid communications

Smart grid modernization enables integration of computing, information and communications capabilities into the legacy electric power grid system, especially the low voltage distribution networks where various consumers are located. The evolutionary paradigm has initiated worldwide deployment of an enormous number of smart meters as well as renewable energy sources at end-user levels. The future distribution networks as part of advanced metering infrastructure (AMI) will involve decentralized power control operations under associated smart grid communications networks. This dissertation addresses three potential problems anticipated in the future distribution networks of smart grid: 1) local power congestion due to power surpluses produced by PV solar units in a neighborhood that demands disconnection/reconnection mechanisms to alleviate power overflow, 2) power balance associated with renewable energy utilization as well as data traffic across a multi-layered distribution network that requires decentralized designs to facilitate power control as well as communications, and 3) a breach of data integrity attributed to a typical false data injection attack in a smart metering network that calls for a hybrid intrusion detection system to detect anomalous/malicious activities. In the first problem, a model for the disconnection process via smart metering communications between smart meters and the utility control center is proposed. By modeling the power surplus congestion issue as a knapsack problem, greedy solutions for solving such problem are proposed. Simulation results and analysis show that computation time and data traffic under a disconnection stage in the network can be reduced. In the second problem, autonomous distribution networks are designed that take scalability into account by dividing the legacy distribution network into a set of subnetworks. A power-control method is proposed to tackle the power flow and power balance issues. Meanwhile, an overlay multi-tier communications infrastructure for the underlying power network is proposed to analyze the traffic of data information and control messages required for the associated power flow operations. Simulation results and analysis show that utilization of renewable energy production can be improved, and at the same time data traffic reduction under decentralized operations can be achieved as compared to legacy centralized management. In the third problem, an attack model is proposed that aims to minimize the number of compromised meters subject to the equality of an aggregated power load in order to bypass detection under the conventionally radial tree-like distribution network. A hybrid anomaly detection framework is developed, which incorporates the proposed grid sensor placement algorithm with the observability attribute. Simulation results and analysis show that the network observability as well as detection accuracy can be improved by utilizing grid-placed sensors. Conclusively, a number of future works have also been identified to furthering the associated problems and proposed solutions

An assessment of high distributed PV generation on eThekwini electricity distribution network.

Masters Degree. University of KwaZulu-Natal, Durban.Small-scale Distributed Photovoltaic Generation (DPVG) continues to grow with increasing operational challenges for electricity utilities and Distribution Network (DN) operators. In Low Voltage (LV) DNs, there are well researched potential issues that arise with high Photovoltaic (PV) penetration. These include: feeder voltage rise, voltage fluctuations and reverse power flow. Among these, the most important issue is voltage rise at the LV distribution feeder. In a broader perspective, to this point in time, there has not been more detailed research on small-scale DPVG interconnections in the LV networks in South Africa (SA) and in the KwaZulu-Natal (KZN) region. There is a great need for research in this field for ensuring network efficiency, reliability and future regulatory standards. Other network systems have been studied around the world were conditions, environment, network characteristics and electricity customer loads will be different; e.g in the North-West of England, Germany, and Queensland, Australia. Hence, the main objective of this research study is to analyze the mentioned problems, identify and test the appropriate mitigation solutions, in the event of high DPVG. This study was carried out on a typical SAn LV DN model, which represents an existing housing development estate at eThekwini Municipality. Consequently the aim is to identify solutions suitable for networks in SAn or of similar architect and characteristics. As a result, a specific application is undertaken at the KZN region, which is also representative of network characteristics of SAn networks. A voltage rise, voltage fluctuation and network power loss issues were analyzed at different PV penetration levels and varying customer loads. An innovative approach of utilization of a standard central On-Load-Tap-Change (Off-LTC) transformer for voltage regulation with high DPVG was tested. Usage of this technique has not been reported in the literature to date. National standards in SA were used as a basic guide in this study and stated the possibility of grid voltage control of distributed PV inverters. Assessment of the typical LV network showed that there is indeed voltage rise and hence possible voltage fluctuation, when PV system output power varies. The Off-LTC transformer was able to maintain network voltages within the allowed operational range and reduced the magnitude of voltage rise. This implies that there is a possibility of avoiding expensive upgrades of the existing and widespread Off-LTC transformers technology

K-Means and Alternative Clustering Methods in Modern Power Systems

As power systems evolve by integrating renewable energy sources, distributed generation, and electric vehicles, the complexity of managing these systems increases. With the increase in data accessibility and advancements in computational capabilities, clustering algorithms, including K-means, are becoming essential tools for researchers in analyzing, optimizing, and modernizing power systems. This paper presents a comprehensive review of over 440 articles published through 2022, emphasizing the application of K-means clustering, a widely recognized and frequently used algorithm, along with its alternative clustering methods within modern power systems. The main contributions of this study include a bibliometric analysis to understand the historical development and wide-ranging applications of K-means clustering in power systems. This research also thoroughly examines K-means, its various variants, potential limitations, and advantages. Furthermore, the study explores alternative clustering algorithms that can complete or substitute K-means. Some prominent examples include K-medoids, Time-series K-means, BIRCH, Bayesian clustering, HDBSCAN, CLIQUE, SPECTRAL, SOMs, TICC, and swarm-based methods, broadening the understanding and applications of clustering methodologies in modern power systems. The paper highlights the wide-ranging applications of these techniques, from load forecasting and fault detection to power quality analysis and system security assessment. Throughout the examination, it has been observed that the number of publications employing clustering algorithms within modern power systems is following an exponential upward trend. This emphasizes the necessity for professionals to understand various clustering methods, including their benefits and potential challenges, to incorporate the most suitable ones into their studies

Identifying the flexibility potential of Dutch industrial parks using synthetic profiles

The Earth has had its resources aggressively exploited in the last decades. Alongside the depletion of its fossil-fuels reserves the planet has been experiencing a large amount of greenhouse gases (GHG) emissions into the atmosphere. These emissions are leading to a phenomenon denominated global warming. In order to mitigate the consequences of global warming (melting of ice glaciers that cause the levels of the ocean to rise, extreme weather events, etc.) measures against climate change need to be taken. The Netherlands signed a national determined contribution with a target of reducing the country’s dependence on fossil fuels. These ranged from a larger percentage of renewable energy in energy supply, through the electrification of heating, to widespread adoption of electric vehicles. Renewable energy sources are, however, intrinsically intermittent. To make proper use of these new sources without massive changes in the current electricity system the use of flexibility is highly recommendable. Without the proper use of flexibility, there are risks of congestion in the electricity grid. The process of generating electricity from a source of renewable energy does not necessarily guarantee a cleaner energy mix. It also depends on when, where, and the flexibility sources available. As the sector that has the highest energy consumption is the industry (commercial buildings included), the focus of this thesis is to assess the flexibility potential of industrial areas. The goal is to fulfil as much as possible of the industrial area with renewable electricity, while ensuring any surplus in production is used by flexibility, thus preventing the need for congestion management on a distribution network level. To this end, measured data from companies from the industrial park of Reiderland (Groningen, the Netherlands) were analysed. Two flexibility sources are chosen: electric vehicles and heat pumps. They were selected due to their importance in the electrification of energy system by replacing two major traditionally fossil-fuel powered streams: transport and heating. This thesis answers the following main research question: “In what way can a synthetic load profile, that can be applied to multiple types of businesses with minor changes, be used to assess the flexibility potential, given a certain amount of available RES?”. For this purpose, the companies are further divided into categories and normalised to make possible the creation of generic, wide-applicable synthetic profiles. Different aspects of the main research question are addressed through a set of sub-questions. After the generic profiles for different types of industry are obtained, a fictitious industrial park is created through the selected profiles for each category. There is not enough data to develop a wide-applicable profile for the companies in the industry category (that probably depend on the kind of product they manufacture). Hence, with more data (not only from the industry category) the model can be greatly improved. For the first comparison, a 400kW photovoltaic (PV) system (the only source of renewable energy used) is applied to the fictitious industrial park. Thus, the times when flexibility would be required to cope with the energy surplus of the system, how much energy surplus there is in a year, and an example of how to use this surplus are presented. Two different ways to visualise the PV surplus energy are displayed: the subtraction from the total electricity consumed by the fictitious industrial park, and as a ratio of PV energy generated over total electricity consumption. When the ratio is larger than one it means that there is an energy surplus in that period, when it is between zero and one it means that is only feeding the fictitious park and indicates with what percentage of the energy is being fed by the solar system. The 400kW allows the production of over 25MWh of PV surplus energy, enough to charge the most popular fully electric vehicle in the Netherlands 441 times. Finally, a sensitivity analysis, varying the size of the PV system, is conducted. It was found that by increasing the number of PV panels, the amount of surplus energy rises almost exponentially. With 80% the system is able to provide over 7 times the amount of surplus energy the original system provides, whereas with 20% less it generates around less than one third of the original systemObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.2 - Per a 2030, augmentar substancialment el percentatge d’energia renovable en el con­junt de fonts d’energiaObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura::9.2 - Promoure una industrialització inclusiva i sostenible i, a tot tardar el 2030, augmentar de manera significativa la contribució de la indústria a l’ocupació i al producte interior brut, d’acord amb les circumstàncies nacionals, i duplicar aquesta contribució als països menys avançat