A Review of Architectures and Concepts for Intelligence in Future Electric Energy Systems

Distributed generation (DG) units such as small-scale wind turbines, solar photovoltaic (PV) panels and microturbines have been increasingly installed in microgrids. Since the renewable energy sources (RESs) such as PV systems have reverse-peak power generation, demand response methods have been widely used in the microgrids to achieve peak shaving. Considering DG and demand response, microgrids can be operated in a cost-efficient and secure way. By utilizing a price-based demand response (PBDR) method and dispatching microturbines, this paper develops a two-stage optimal coordination method for microgrids. In a day-ahead stage, the PBDR for the whole day is optimized with consideration of the dispatch of the microturbine power generation. Then, in an intraday stage, the microturbines are dispatched to follow the RES variations. The proposed method is tested on a 33-bus microgrid and the simulation results demonstrate high efficiency in operating cost reduction.

Due to the transition of traditional power system to smart structure, integration of renewable energy sources is of great importance. It is performed by using distributed generators and Micro grid. Integration of renewable sources is very useful for the reliability enhancement of distribution system as energy can be supplied locally at distributed level. Therefore, this chapter provides an overview of various reliability methods which are utilized for finding the impact of renewable energy generation on distribution system reliability assessment. These renewable energy sources are integrated in the distribution system at distributed and Micro grid level. Various characteristics of renewable energy sources are discussed to model them. A general problem of reliability assessment in terms of reliability indices is also discussed.

Due to the transition of traditional power system to smart structure, integration of renewable energy sources is of great importance. It is performed by using distributed generators and Micro grid. Integration of renewable sources is very useful for the reliability enhancement of distribution system as energy can be supplied locally at distributed level. Therefore, this chapter provides an overview of various reliability methods which are utilized for finding the impact of renewable energy generation on distribution system reliability assessment. These renewable energy sources are integrated in the distribution system at distributed and Micro grid level. Various characteristics of renewable energy sources are discussed to model them. A general problem of reliability assessment in terms of reliability indices is also discussed.

This article details the design of an advanced smart grid model that utilizes an enhanced optimal variation strategy through the integration of renewable energy sources. A key innovation presented here is the development of a renewable energy-based smart grid system that incorporates an Artificial Super Intelligence Network (ASIN) to maintain a stable voltage profile and balanced reactive power levels throughout the grid. This goal is achieved by deploying solar energy source, along with ASI technique, for effective reactive power control using Electric Spring technology. The smart grid’s power demands are met by managing the reactive power levels through the integration of these renewable sources. A Feed Forward Neural Network is utilized to optimize power calculations, determining voltage profiles and power loss based on system load. The Electric Spring serves as an optimal VAR compensating device, ensuring that reactive power remains within permissible limits across the smart grid. The proposed system enhances the voltage profile, reduces power loss, and maintains reactive power balance in the grid. The implementation of this approach is carried out in a MATLAB/Simulink environment, where performance is analysed for different scenarios. The solar energy-powered smart grid effectively achieves its objectives in these cases. Notably, the integration renewable energy sources with the ASI Network results in an improved voltage profile of approximately 98.45%, with the profile rating increasing from 1.05 to 1.06 p.u. Additionally, real power loss is minimized from 3.75 MW to 3.52 MW.

A central issue that was recently discussed within the power systems community is how the COVID-19 pandemic, and possibly other future pandemics, will affect the integration of renewable energy sources in the long-term. An interesting idea that may shed light on this question is the one of “economic shocks”, according to which, if the integration of renewable sources can be described as a dynamic system operating on time-scales of years, then several months of low consumption may be viewed as a negative impulse signal (a shock), which causes reactions and counter-reactions that evolve in a closed feedback loop. In this paper we explore this idea by means of a regression model, which attempts to reflect the relations between fossil-fuel based generation and day-ahead electricity prices and demand in the European market. The results point out to an interesting phenomenon of instability in fossil-fuel based generation following a shock in consumption, which may support the claim that pandemics and other economic shocks may promote the future integration of renewable energy sources.

Novel home energy management system using wireless communication technologies for carbon emission reduction within a smart grid

The article analyzes the development trends for renewable energy sources in 2010-2021. The growing use of renewable energy sources in the global energy balance in developed and developing countries was revealed. The share of renewable sources in the production of electricity in 2021 was determined. The results presented in the form of approaches to the integration of renewable sources in order to replenish the production processes for the provision of energy services are based on an extensive assessment of scientific Russian and foreign literature. Integration of renewable energy sources will contribute to the sustainability of existing technologies and risk neutralization. The integrated approach will contribute to the interconnected provision of electricity, heat, cold and mobility

Decentralisation of power generation is generally acknowledged one of characteristics of future smart grids. Different conventional and renewable energy sources will be installed in different locations but supporting the common grid network. The energy sources will work separately but with communication to optimize the power flow in the grids. Currently, solar energy is the most commonly used among the renewable energy sources, since installation of PV panel is very flexible, it can be down to few kilowatts for residential applications or up to tens Megawatts for solar farms. However, the disadvantage is that solar energy harvesting only operates during day time, and the amount of extracting energy highly depends on the weather conditions. It creates power quality issues for the future smart grids due to this unpredictable energy flows. Furthermore, emerging semiconductors is getting close to the market. The design of PV inverters will be a new era to achieve high energy efficiency and reliable. The paper will present the challenges of the future PV inverter design based on the grid-environment, the regulations and the applications. Moreover, the technology trend of improving system performance of PV inverters, including semiconductors, magnetic materials and converter topology, will be reviewed and discussed. (6 pages)

With the innovation of electrical networks to serve large cities, the concept of smart city began to be disseminated to improve energy efficiency and the integration of renewable sources in their matrix, therefore, Information and Communication Technology (ICT) plays a role central in the evolution of electrical networks to smart grids. Generally, ICT plays a crucial role in facilitating the control, management, and comprehensive monitoring of operations within smart grids. The inherent complexity of smart grids arises from the intricate interplay of various heterogeneous components, diverse types of generators, and a multitude of load variations. Despite these challenges, the integration of advanced ICT solutions continues to pave the way for enhanced efficiency and reliability in smart grid operations. This technology enables real-time data collection, communication between devices, integration of renewable energy sources, and automation of the electrical grid. By facilitating advanced monitoring, control, and data analysis, ICT makes energy distribution more efficient, reliable, and sustainable, promoting the transition to a modern and smart electricity sector. In this chapter, we will address the advantages and disadvantages of renewable sources and the crucial role of ICT in this energy transformation to control and monitor smart grids to avoid the flow of power in utility networks.

The integration of renewable energy sources coordinated with the use of energy storage systems to provide power for a local grid is the main target for microgrids. Microgrids allow better integration of renewable sources, as well as allow adequate management of the storage elements, which bring improvements in power quality of the electrical systems. This paper presents the simulation results of the operation and control of a microgrid consisting of a photovoltaic generation system with energy storage (batteries) and the load in a distribution system. This work is part of the R&D project (Copel, 2016), whose objective is the development of a control system for the management of energy resources and loads of the consumer in the context of intelligent microgrids, as support to the integration of distributed generation. The management method is based on the construction of an optimal control algorithm and a hierarchical control structure of microgrids.

The article presents the results of the analysis of a number of issues in the context of the problem of covering peak loads in the energy system of Ukraine. Information is provided on the features of the formation of these loads and their changes due to the full-scale invasion of Russia into Ukraine. The corresponding challenges associated with the integration of renewable energy sources into the energy system of Ukraine are considered. The specifics of the implementation of both traditional and innovative approaches to covering peak loads are analyzed, in particular the use of peak generating capacities, energy storage systems, smart grids and demand management, as well as the integration of renewable sources into the energy system in combination with energy storage devices or virtual power plants. The data on the comparison of the characteristics of different types of peak capacities in terms of peak load coverage efficiency are provided. Particular attention is paid to the consideration of the prospects for the development of peak load coverage technologies in Ukraine. It is indicated that in the short term, traditional approaches will have a certain advantage over innovative ones. As for innovative approaches, one of the most promising will be the use of battery systems. Approaches related to demand management and the use of renewable energy sources in combination with energy storage and virtual power plants will remain important. Based on the results of the analysis, a conclusion was made about the growing relevance of the problem of covering peak loads in the energy system of Ukraine, given the increase in these loads due to a number of reasons, including unavoidable ones. Bibl. 44, Fig. 3, Tab. 3.

This article introduces the design of an advanced smart grid model that optimizes power management through the integration of renewable energy sources. A key innovation lies in the use of a Renewable-Powered Smart Grid System driven by an Artificial Super Intelligence Network (ASIN) to ensure stable voltage profiles and balanced reactive power. The system harnesses solar and wind energy, employing ASIN techniques alongside Electric Spring technology for efficient reactive power control. The seamless integration of renewable sources allows the system to meet grid power demands while managing reactive power effectively. A Feed Forward Neural Network (FFNN) is utilized to optimize power calculations, determining voltage profiles, and minimizing power losses based on varying load conditions. The Electric Spring acts as an optimal VAR compensating device, keeping reactive power within permissible limits, thereby improving voltage stability, reducing losses, and maintaining reactive power balance across the grid. The proposed system is implemented and tested in a MATLAB/Simulink environment under three distinct scenarios. Results indicate that the hybrid energy-powered smart grid meets its performance objectives efficiently. Notably, the integration of renewable sources with ASIN enhances the voltage profile by approximately 97.70% increasing it from 1.074 to 1.083 p. u. Additionally, real power losses are reduced from 3.531 MW to 3.45 MW, demonstrating the system’s improved efficiency.

The increase and integration of renewable energy sources in electrical power systems implies an increase in uncertainty variables, both in costs and production, of economic dispatch (ED) and currently have a significant influence on wholesale electricity markets (MEM). Uncertainty costs refer to the quantification of additional expenses or economic losses associated with the variability inherent in the generation of renewable energy, such as wind, solar, or hydroelectric. Therefore, this article presents deterministic equations related to cost overestimation and underestimation, as well as CVaR, to model and evaluate the stochasticity of risks associated with the integration of renewable sources, allowing system operators and planners to make informed decisions. To mitigate or use said risks in energy systems with high penetration of elements, mainly smart networks. In this study, a mathematical analysis is carried out using the histogram spectrum formed by the power generated by the probability density function (PDF) for solar generation, although it is possible to consider other types of functions to determine energy generation. The objective of the proposed model is to provide another tool to the system operator for energy management and planning, which relieves a little of the weight of the computational load and at the same time presents more precision in the results by being able to work with a database. Historical data if these values are available. Commonly, for this type of analysis, values are estimated using probabilistic calculations by density functions when integrating these functions, or in other recent cases by estimating them by analytical methods of the same functions. A validation of the model is presented by comparing the result with the Monte Carlo simulation, developing the total cost of uncertainty only from "low probability generation extremes". Furthermore, the results are presented through analytical uncertainty cost functions (AUCF). This analysis includes the calculation of uncertainty costs for low and high-probability energy generation, determined by the Conditional Value at Risk (CVaR), using deterministic equations.

Nowadays, integration of renewable energy source like solar, wind etc in the grid is encouraged to reduce the losses and meet the demand. However, the integration of these renewable sources, power electronic devices, non-linear and un-balanced loads leads to the power quality issues this motivated power researchers for the development of new controllers and techniques. This paper develops a soccer-league algorithm based optimal tuned hybrid controller for the unified power quality conditioner associated with the solar power and battery-storage systems with the Boost converter and Buck Boost converter. The UPQC simultaneously performs both the functions of Shunt active power filter and series active power filter. The proposed optimally designed controller adapts both the properties of fuzzy logic-controller and SOL algorithm tuned proportional-integral controllers. The K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> , K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> values of shunt and series controllers are treated as control variables, which are optimally tuned by SOL to satisfy the objective function. The key contributions of the proposed work are the reduction of total harmonics in current waveforms thereby enhancing the power factor, quick action to maintain the constant DC-Link capacitor voltage during the solar irradiation variations, elimination of voltage sag/swell/ large disturbance, and appropriate compensation for the un-balanced networks and loads. The performance investigation of SLOHC was carried-out with four test studies for different combinations of unbalanced/balanced loads and supply voltage of 3-phase distribution network. Comparative analysis was carried out with those of standard methods like a genetic algorithm, biogeography-based optimization, and proportional-integral controllers. The proposed method reduces the total harmonic distortion to 2.06%, 2.44%, 2.40%, and 2.32% which are much lower than those of existing methods available in literature. The design has been performed on MATLAB/simulink software.

In today's world, the need for more energy seems to be ever increasing. The high cost and limited sources of fossil fuels, in addition to the need to reduce greenhouse gasses, have made renewable energy sources (RES) attractive in today's world economy. However, the fluctuating and intermittent nature of these RES causes variations of power flow that can significantly affect the stability and operation of the electrical grid. In addition, the power output of these RES is not as easy to adjust to changing demand cycles as the output from the traditional power sources. To overcome these problems, energy from these RES must be stored when excess is produced and then released, when production levels are less than the required demand. Therefore, in order for RES to become completely reliable as primary sources of energy, energy storage systems (ESS) is a crucial factor. The impact of the ESS in future grid is receiving more attention than ever from system designers, grid operations and regulators. Energy storage technologies have the potential to support our energy system's evolution, they can be used for multiple applications, such as: energy management, backup power, load leveling, frequency regulation, voltage support, and grid stabilization. In this work, an overview of the current and future energy storage technologies used for electric power applications is carried out. Furthermore, an assessment of the dynamic performance of energy storage technologies for the stabilization and control of the power flow of emerging smart grid will be presented. The EES can enhance the operation security and ensure the continuity of energy supply in future smart grids.