Dual-stage day-ahead optimized performance of renewable-based microgrids

In distributed networks, wind turbine generators (WTGs) are to be optimally sized and positioned for cost-effective and efficient network service. Various meta-heuristic algorithms have been proposed to allocate WTGs within microgrids. However, the ability of these optimizers might not be guaranteed with uncertainty loads and wind generations. This paper presents novel meta-heuristic optimizers to mitigate extreme voltage drops and the total costs associated with WTGs allocation within microgrids. Arithmetic optimization algorithm (AOA), coronavirus herd immunity optimizer, and chimp optimization algorithm (ChOA) are proposed to manipulate these aspects. The trialed optimizers are developed and analyzed via Matlab, and fair comparison with the grey wolf optimization, particle swarm optimization, and the mature genetic algorithm are introduced. Numerical results for a large-scale 295-bus system (composed of IEEE 141-bus, IEEE 85-bus, IEEE 69-bus subsystems) results illustrate the AOA and the ChOA outperform the other optimizers in terms of satisfying the objective functions, convergence, and execution time. The voltage profile is substantially improved at all buses with the penetration of the WTG with satisfactory power losses through the transmission lines. Day-ahead is considered generic and efficient in terms of total costs. The AOA records costs of 16.575M$/year with a reduction of 31% compared to particle swarm optimization. © 2023 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

Operating the Power Grid During a Pandemic: COVID-19 Experiences

In early 2020, COVID-19 started to impact society at a global scale. The World Health Organization declared COVID-19 a pandemic on 11 March 2020, and the world faced the most significant health problem of the last 100 years. The pandemic and its lockdown measures caused significant disruptions to society and the economy. Electricity is essential to modern society and the power grid is considered the most critical infrastructure, with essentially all other infrastructure dependent on it. Maintaining grid reliability and resilience was paramount during the pandemic. © 2003-2012 IEEE.

The oil and gas cybersecurity enigma

The digitization of the oil and gas industry creates potentially detrimental opportunities for terrorists, criminals, insiders, and activists to exploit. Due to the COVID-19 pandemic, working remotely has become the norm, and remote collaboration has been enabled by such Internet-based applications as Microsoft Teams, Zoom, and others. Remote employees may be more casual with cybersecurity, which further increases the risk of cyberattacks. Successful cyberattacks against oil and gas assets or operations have the capacity to cripple economies, disrupt power grids, and initiate political or public unrest and chaos. Cybersecurity defense should be as central to our organizational culture as turning on our workplace computer. We discuss the most likely weak points in our systems and possible solutions. © 2022 by The Society of Exploration Geophysicists.

Artificial Intelligence Assisted Smart Photovoltaics

The paper discusses research efforts in combining recent progress in Artificial Intelligence with automated management of solar energy generated in grid-connected photovoltaic (PV) systems along with their operation- and-maintenance (O&M) and their smart on-grid integration control. The outlined research aligns with the strategy of the European Union joining Digital and Green agendas as two major pillars for the COVID-19 economic recovery in the EU and is a part of the EU funded standardization action under the H2020 StandICT programme coordinated by the author and hosted by the Smart Energy Standards Group of the European Information Technologies Certification Institute (EITCI SESG) in cooperation with the European Solar Network. It also contributes to one of the four primary objectives of the European Green Deal, i.e. to achieve a fully integrated, interconnected and digitalized EU energy market by increasing research oriented towards technical reference standardization aimed at consolidation of the expert community and the technology uptake. © 2021. The Authors. Published by International Solar Energy Society Selection and/or peer review under responsibility of Scientific Committee.

Microclimate Monitoring System Design for the Smart Grid Analysis and Constructive Parameters Estimation

This paper describes a microclimate monitoring system consisting of a LoRaWAN network of wireless climate sensors, a data collector and analytical software. The system is a part of the ICS RAS SmartGrid Centre project for predicting building energy consumption. During the design phase, the authors considered the concept of comfort, which is involved in setting control objectives for HVAC plants. It was necessary to overcome some characteristics of the LoRaWAN protocol, such as floating data transmission period and limited intensity of sensor communication. These have been overcome by post-processing the data with Python software, using libraries numpy and scipy. The collected data was passed through an interpolation filter for synchronization, and the resulting data is freely available in dataset format on our website for all interested researchers. Additionally, weather data was collected using a local meteostation to be considered as external disturbances in analysis problems. This paper also considers an approach to passive identification of the thermal protection parameters of a building. The coronavirus lockdown period was chosen to assume the impact of visitors negligible. The parameters are supposed to be estimated by correlation analysis. The estimates obtained should be compared with the values calculated according to ISO and Russian construction standards for diagnostic reasons. © 2022 Elsevier B.V.. All rights reserved.

Regional PV Energy Forecasting using Distributed Data and Deep Neural Networks

Despite the COVID-19 pandemic, the global Photovoltaic market once more grew significantly in 2020, mainly on Grid-Connected Systems. The exponential increase of these systems raises new challenges for Smart Grid operators trying to predict load demand. That occurs because of the panels' output uncertainty and the leak of regional models for solar energy prediction. In this paper, we propose a distributed data approach to predict solar energy generated by Photovoltaic Systems. As input, we combine data from a community of solar panel owners and a historical weather website to build our dataset. This paper evaluates two scenarios: predicting regional next-day generation by using weather forecasting and the impact of a new system in that region. We sort the results seasonally and achieved 7% of MAE weighted percentage for summer predictions. © 2022 IEEE.

MicroGrid Designer: user-friendly design, operation and control assist tools for resilient microgrid and autonomous community

During this decade, many countries have experienced natural and accidental disasters, such as typhoons, floods, earthquakes, and nuclear plant accidents, causing catastrophic damage to infrastructures. Since the end of 2019, all countries of the world are struggling with the COVID-19 and pursuing countermeasures, including inoculation of vaccine, and changes in our lifestyle and social structures. All these experiences have made the residents in the affected regions keenly aware of the need for new infrastructures that are resilient and autonomous, so that vital lifelines are secured during calamities. A paradigm shift has been taking place toward reorganizing the energy social service management in many countries, including Japan, by effective use of sustainable energy and new supply schemes. However, such new power sources and supply schemes would affect the power grid through intermittency of power output and the deterioration of power quality and service. Therefore, new social infrastructures and novel management systems to supply energy and social service will be required. In this paper, user-friendly design, operation and control assist tools for resilient microgrids and autonomous communities are proposed and applied to the standard microgrid to verify its effectiveness and performance. © 2022

The Development and Implementation of a Microgrid SCADA System Simulator

Shifting the paradigm to decarbonized, distributed renewable future implies changes to conventional principles of power systems operation and requires the implementation of smart grid concepts. Microgrids have been widely recognized as a decentralized approach to successfully integrating renewable energy sources and end consumer empowerment. However, their implementation requires significant improvements and transformation of the distribution system in terms of increased observability and controllability, especially in the context of (near) real-time operation. Supervisory, Control, and Data Acquisition Systems (SCADA) enable system and infrastructure automated monitoring and control and serve as a foundation for advanced management and application of optimization-driven operation. Moreover, the development and testing of the functions mentioned above is a complex task, and today there is still a lack of holistic simulation tools, even though well-established power system simulators exist. The main objective of this paper is to introduce a novel simulation tool developed to simulate the SCADA system used in the Smart Grid Laboratory of the Faculty of Electrical Engineering and Computing for control, integration, and interactions between a microgrid's components. This paper includes simulator system architecture design, implemented functionalities, and future directions. Simulator testing shows successful communication, measurement generation, and meaningful response to commands and reference signals, proving correct functionality. Besides significant value in testing SCADA functionality, designing such a simulator has been of great benefit during restricted access to real-world devices in the Smart Grid Laboratory during the COVID-19 pandemic lockdown. © 2022 Croatian Society MIPRO.

Construction Plan for Backup Dispatch of Regional Power Grid

Emergencies such as the COVID-19 and natural disasters have brought severe ordeals to the current grid emergency dispatch system, and there is an urgent need to improve and consummate the existing backup dispatch system. This paper firstly analyzes the existing three kinds of backup dispatch systems and their advantages and disadvantages, and then compares in detail the construction of national dispatch, provincial dispatch, and prefectural dispatch, and points out several existing problems of backup dispatch at all levels under the current emergency system. In order to gradually solve these problems, a backup dispatch system combining emergency and disaster recovery has been proposed based on the two-place three-center mode, it gradually realizes the prevention of risks from social security incidents such as public health incidents and serious natural disasters. © 2022 IEEE.

Power grid data intelligent management and application under the background of big data

With the popularization of new technologies such as big data, cloud computing and the Internet of things in the construction of smart grid, power data is showing explosive growth. Traditional power enterprises rely on manpower to collect data and recover arrears. During the period of COVID-19, the closed management of government departments, the arrears of electricity customers and no power outages made the recovery work more difficult. In this paper, through the mining and analysis of customers' historical payment data, historical electricity and other data, using the deep learning algorithm in the field of artificial intelligence, this paper constructs a mathematical model and formulates the prevention and control strategy of electricity charge recovery risk of business travel alienation. The application results show that the new strategy can effectively reduce the amount of customer arrears and comprehensively improve the lean, digital and intelligent management level of power supply enterprises. © 2022 IEEE.

The Significance of Dissemination Activities at Mediterranean University in the frame of project 'Electrical Energy Markets and Engineering Education (ELEMEND)'

Engineering and science curricula are revamped to address sustainability as a cross cutting horizontal issue in order to have an impact on how students appreciate, understand and think critically about complex environmental, social and economic problems. Key to maximizing impact is the dissemination of a novel practice as well as its outcomes and outputs. The target of the ERASMUS+ project 'Electrical Energy Markets and Engineering Education - ELEMEND' is the capacity building of academic and teaching staff, students, electro engineering staff, employers as well as the general public. ELEMEND also aspires to create a favorable environment for energy related business and to modify the electricity user's behavior in the Western Balkan Countries in line with technological developments in smart grids. In order to ensure the sustainability of the ELEMEND results, a Dissemination and Exploitation Plan was elaborated by each of partner university taking into account all relevant stakeholders and key actors. In particular, we examine how the dissemination plan of Mediterranean University (MU), a partner university of the ELEMEND project, sets the targets to be achieved through the dissemination activities which make the project's objective and results visible and usable to all potential stakeholders. We focus on the dissemination activities of the Mediterranean University, we analyze applied methods and forms, we provide examples of how Mediterranean University pursued dissemination targets under Covid-19 conditions. © 2021 IEEE.

COVID-19 Impact Assessment of Energy Consumption on Kerala State Electricity Board Power Utility Grid

Electricity demand have dropped sharply in general as governments around the world executed the lockdown restrictions. The load compositions and the daily load profiles have also changed. Utilities are basically engaged in providing various power requirements accordingly for different types of tariffs. The various tariffs are applicable to consumers like Domestic, Industry, Agriculture, Government sources, Commercial, Public lighting etc. The COVID-19 Pandemic have affected the energy consumption of various tariff categories in different ways. Since the COVID-19 Pandemic deprived most of the Industrial and Commercial establishments of their functioning, their energy consumption drastically came down whereas the domestic energy consumption increased. This paper attempts to compare assess the energy consumption data of various categories during the pandemic period and how it has affected the Utilities sale of KSEB Power Utility Grid. © 2021 IEEE.

Load-Altering Attacks Against Power Grids under COVID-19 Low-Inertia Conditions

The COVID-19 pandemic has impacted our society by forcing shutdowns and shifting the way people interacted worldwide. In relation to the impacts on the electric grid, it created a significant decrease in energy demands across the globe. Recent studies have shown that the low demand conditions caused by COVID-19 lockdowns combined with large renewable generation have resulted in extremely low-inertia grid conditions. In this work, we examine how an attacker could exploit these scenarios to cause unsafe grid operating conditions by executing load-altering attacks (LAAs) targeted at compromising hundreds of thousands of IoT-connected high-wattage loads in low-inertia power systems. Our study focuses on analyzing the impact of the COVID-19 mitigation measures on U.S. regional transmission operators (RTOs), formulating a plausible and realistic least-effort LAA targeted at transmission systems with low-inertia conditions, and evaluating the probability of these large-scale LAAs. Theoretical and simulation results are presented based on the WSCC 9-bus and IEEE 118-bus test systems. Results demonstrate how adversaries could provoke major frequency disturbances by targeting vulnerable load buses in low-inertia systems and offer insights into how the temporal fluctuations of renewable energy sources, considering generation scheduling, impact the grid’s vulnerability to LAAs. Author

Enable a Carbon Efficient Power Grid via Minimal Uplift Payments

The COVID-19 has slowed down the global economic growth. Meanwhile, it also significantly cuts the global carbon emission, which provides a golden opportunity for the whole world to combat the climate change together. While the former policies (e.g., the CAFE standards, renewable portfolio standards, etc.) have reduced certain level of fossil fuel consumption, the most effective measures (such as carbon tax, cap-and-trade programs) are still far from ready for global implementation. This paper investigates an alternative way to achieve a more carbon efficient power grid using the uplift payment scheme. Specifically, we propose an effective algorithm to guarantee the carbon efficiency with the minimal uplift payments. We also submit that this scheme provides more flexibility to realize carbon reduction than carbon tax, which is exemplified by thorough numerical studies. Furthermore, we show that the stability of the power grid can be ensured under our uplift payment scheme, both from theoretical analysis and numerical studies. The results strengthen our belief that our uplift payment scheme is practicable for electricity market. IEEE

Resilience in the Home Office through a Scaled-down Microgrid

Having power sources close to the end user establishes resilience in the event of power outages. In order to effectively mitigate any risk of losing power and productivity, major office buildings usually have some sort of backup generation to sustain a business. Homes generally do not have a robust back-up power system, so when a person is working from home and the power goes out, productivity stops. Therefore, a new power grid solution is needed. Coming from the metric prefix atto, meaning 10-18, an atto-grid provides power to a singular room or section of room which makes it even smaller than a picogrid. This atto-grid powers the typical load of a standard, single-person office: a printer, a laptop, a phone, and a lamp. The atto-grid project was proposed by Dr. Robert Kerestes from the Electrical and Computer Engineering department at the University of Pittsburgh as part of a senior design course, and required distributed generation, connection to the building electrical grid, and a monitoring system for volts, amps, and watts. With these requirements in mind, the senior design team was able to design the atto-grid with two types of distributed generation, an inverter, manual switches and contactors for isolation, and accessible outlet receptacles for users to supply power to their at-home office load. An economic cost-benefit analysis was conducted as well for the purpose of determining the atto-grid's availability to different income levels. For hardware, results of tests on power quality and uptime will be presented;for software, metrics covering response time and accuracy will be analyzed and discussed. Finally, the budget, timeline, and expectations from the department faculty and domain advisors are discussed. Throughout the design process and semester, the design team learned technical and practical lessons that were brought up due to the semester coinciding with the COVID-19 pandemic. Despite technical and practical challenges, the team delivered on all requirements from the senior design curriculum, as well as the technical requirements based on the project proposal. The team acknowledges ways to improve the design if constraints were different, such as time, budget, and skillset. Finally, this paper will discuss feedback received from faculty and domain advisors throughout the semester, as well as reflect on progress and achievements for the atto-grid project. © American Society for Engineering Education, 2021

Data Communication Interfaces in Smart Grid Real-time Simulations: Challenges and Solutions

This paper presents the challenges and also suggests solutions associated with developing data communication interfaces between real-time digital simulator (RTDS) and hardware or software devices under study. While RTDS supports a wide range of standard and well-established communication protocols, employing such communication protocols generally increases the cost of the educational project as these standard communication protocols require licenses as well as third-party hardware and software devices to act as gateways. The need for these licenses and third-party hardware and software devices adds to the total cost of the project and also requires additional training. This paper provides two sets of cost-effective data interface solutions for local and remote networks based on the lessons learned from different projects that the authors were involved with. These practical solutions are especially useful for projects that involve multiple partners located remotely that are facing logistic challenges due to the Covid-19 pandemic. © 2021 IEEE.

Experimental and numerical assessment for HVAC management in an industrial building: A preliminary optimization

COVID-19 em ergency has ca used major changes in everyday life in the la st m onths, a nd it a lso affected the management of buildings. In particular, indoor a ir quality and ventilation ha ve been considered to play a key role in the spreading of the infection, causing national and interna tional subjects to draw up specific guidelines on ventilation and air recirculation rate in AHUs. The pa per deals with the “Loccioni Leaf Lab”, a n industria l building that hosts offices a nd workers operating on test benches. The building features high performance envelope, solar photovoltaic systems, groundwater heat pumps a nd a high -technology control a nd monitoring system and it is connected to a thermal and electric smart grid. A va lidated m odel of the building, im plem ented with the software DesignBuilder a nd EnergyPlus, wa s used to carry out numerical sim ula tions to optimize the m anagement of the HVAC through the Building Management System. Different working conditions have been sim ulated, a nd the numerical output has been used together with experimental data collected from the Company monitoring system. Ithas been possible to investigate how the extra ventilation required by the new guidelines would affect the tota l energy consumption a nd to compare, in term s of energy efficiency, the different HVAC m a nagement stra tegies tha t could be used to ensure occupants hea lth safety and indoor air qua lity. © 2021 Institute of Physics Publishing. All rights reserved.