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This paper reviews renewable energy integration with the electrical power grid through the use of advanced solutions at the device and system level, using smart operation with better utilisation of design margins and power flow optimisation with machine learning. This paper first highlights the significance of credible temperature measurements for devices with advanced power flow management, particularly the use of advanced fibre optic sensing technology. The potential to expand renewable energy generation capacity, particularly of existing wind farms, by exploiting thermal design margins is then explored. Dynamic and adaptive optimal power flow models are subsequently reviewed for optimisation of resource utilisation and minimisation of operational risks. This paper suggests that system-level automation of these processes could improve power capacity exploitation and network stability economically and environmentally. Further research is needed to achieve these goals. [ABSTRACT FROM AUTHOR]

The integration of the Internet of Things (IoT) with renewable energy technologies is revolutionizing modern power systems by enhancing efficiency, reliability, and sustainability. This paper examines the role of the IoT in optimizing the integration and management of renewable energy sources, such as solar and wind power, into the electrical grid. The IoT enables real-time monitoring, data analysis, and automation, facilitating advanced load management, demand response, and energy storage solutions. Key advancements in IoT technologies, including smart grids and energy management systems, are discussed, highlighting their impact on improving grid stability and promoting the use of renewable energy. The paper also finds some challenges such as data security, privacy, and the need for standardized communication protocols. Furthermore, it finds how the IoT optimizes electric vehicle performance through advanced battery management, real-time energy consumption monitoring, and improved interaction with the electrical grid. Future research directions emphasize the potential of the IoT to further enhance renewable energy integration through artificial intelligence and machine learning, driving the transition towards a more sustainable and resilient energy future. [ABSTRACT FROM AUTHOR]

With the increase in the proportion of photovoltaic and wind power access, the scale and form of distribution networks are becoming more and more complex. The traditional single distribution network vulnerability assessment method is difficult to use to identify the vulnerable links in the distribution network. Therefore, this paper proposes a method for identifying and evaluating vulnerable links in distribution networks based on minimum discriminant information. First, considering the influence of distributed grid connection, an improved probabilistic power flow calculation method is proposed, which improves the calculation efficiency and accuracy. Second, considering the correlation degree, transmission capacity, and voltage stability of branches in the distribution network, the identification index of vulnerable lines is defined. Based on power quality and operating state, the identification index of vulnerable nodes in a distribution network is defined. Finally, based on the indicators of vulnerable nodes and vulnerable lines, the vulnerable links in the distribution network are comprehensively evaluated based on the principle of minimum discriminant information, and the vulnerable links of the entire distribution network are evaluated according to different degrees of vulnerability. The rationality and effectiveness of the proposed method are verified via an example analysis of actual power grid data. [ABSTRACT FROM AUTHOR]

Variable renewable energy sources (VRESs) are essential for decarbonizing the energy sector, but they introduce significant uncertainty into power grids. This uncertainty necessitates increased flexibility to ensure reliable and efficient grid operations, impacting both short-term strategies and long-term planning. Effective management of VRESs is particularly challenging for distribution system operators (DSOs) due to limited grid measurement and other data, complicating state estimation. This paper proposes a tractable framework that operates under low-observability conditions. The framework uses conservative linear approximations (CLAs) to manage grid constraints efficiently, requiring only the ranges of power injections typically available to operators. The objectives are twofold: first, to determine the amount and location of flexibility needed to prevent voltage violations and, second, to establish voltage measurement thresholds to trigger flexibility activation. Key contributions include the formulation of optimization problems to mitigate voltage issues, the introduction of flexibility provision triggered by voltage thresholds, and novel algorithms for determining flexibility and trigger points. The framework's efficacy is demonstrated on IEEE 33-bus and UK 124-bus test systems, showing it can effectively mitigate grid voltage problems despite limited data. [ABSTRACT FROM AUTHOR]

With a substantial fraction of renewable energy integrated into the electrical grid, the new power system urgently requires grid planning scheme displaying adaptability to different energy types and their volatility. Considering the indeterminacy of renewable energy generation output and the different attitudes of decision-makers towards its risk, this paper proposes an adaptability assessment methodology for power grid planning schemes considering multiple decision psychology. First, an evaluation indicator framework is established based on the adaptive requirements of the grid planning for novel power system, and the weights of indicators are calculated based on an improved AHP-CRITIC combination weighting method. Second, improved cumulative prospect theory (ICPT) is adopted to improve to the calculation method of the distance between the evaluation program and the positive and negative ideal programs in the GRA and TOPSIS, which effectively characterize the different decision-making psychologies, and a combination evaluation model is constructed based on a cooperative game (CG), namely, an adaptability evaluation model of grid planning schemes for novel power systems based on GRA-TOPSIS integrating CG and ICPT. Finally, the proposed model serves to evaluate grid planning schemes of three regions in China's 14th Five-Year Plan. The evaluation results show that the adaptability of the schemes varies under different decision-making psychologies, and under the risk-aggressive and loss-sensitive decision-making psychologies, grid planning scheme of Region 1 with the greatest accommodation capacity of renewable energy is preferable. [ABSTRACT FROM AUTHOR]

This paper deals with the optimal scheduling of the resources of a renewable energy community, whose coordination is aimed at providing flexibility services to the electrical distribution network. The available resources are renewable generation units, battery energy storage systems, dispatchable loads, and power-to-hydrogen systems. The main purposes behind the proposed strategy are enhancement of self-consumption and hydrogen production from local resources and the maximization of the economic benefits derived from both the selling of hydrogen and the subsidies given to the community for the shared energy. The proposed approach is formulated as an economic problem accounting for the perspectives of both community members and the distribution system operator. In more detail, a mixed-integer constrained non-linear optimization problem is formulated. Technical constraints related to the resources and the power flows in the electrical grid are considered. Numerical applications allow for verifying the effectiveness of the procedure. The results show that it is possible to increase self-consumption and the production of green hydrogen while providing flexibility services through the exploitation of community resources in terms of active and reactive power support. More specifically, the application of the proposed strategy to different case studies showed that daily revenues of up to EUR 1000 for each MW of renewable energy generation installed can be obtained. This value includes the benefit obtained thanks to the provision of flexibility services, which contribute about 58% of the total. [ABSTRACT FROM AUTHOR]

As renewable energy becomes more widespread, the uncertainty of its output poses serious challenges for peak and frequency regulation of the power system. Evaluating a grid's capacity to integrate renewable energy sources can provide an early-warning and decision-making basis for grid operation and scheduling. This paper presents a method for evaluating the hosting capacity of renewable energy, considering frequency security constraints. Introducing the system frequency nadir constraint into a system ensures that the frequency does not drop to a dangerous level in the event of power disturbances. The analytical characterization relation equation for the system frequency nadir constraint is constructed based on polynomial chaos expansion (PCE) theory. Furthermore, with the goal of minimizing the reduction in renewable energy, considering multiple flexible resources, like demand response (DR), Combined Heat and Power (CHP), energy storage, and Power-to-Gas (P2G), a renewable energy hosting capacity evaluation model that considers frequency security and flexibility resources is established. Finally, based on the concept of the feasible region, the maximum hosting capacity of a system's renewable energy is visualized using the progressive vertex enumeration method. It identifies the safe operating region for renewable energy output that meets the safety constraints of power grid operations. The simulation results were validated using a modified IEEE 39 bus system. [ABSTRACT FROM AUTHOR]

Power grids are progressing, and the possibility of incorporating DC grids toward hybrid AC/DC grids is gaining increasing relevance, as several technologies available nowadays are operating natively in DC. This paper proposes a topology of a full-controlled bidirectional dual-stage interleaved converter for interfacing hybrid AC/DC grids. The topology is based on a dual-stage architecture, constituted by an AC/DC converter and by a DC/DC converter, both based on interleaved power converters. On the AC side, which is connected to the main AC power grid, the proposed dual-stage architecture operates with sinusoidal current in phase or phase opposition with the voltage, meaning a bidirectional operation. In addition, it has the possibility of interfacing with other AC loads, such as domestic electrical appliances, or with an AC microgrid. The DC link, formed by the AC/DC power stage, is interfaced with a DC power grid, which provides numerous advantages, e.g., for interfacing battery electric vehicles directly charged in DC, as well as other DC loads, such as renewable energy sources. The DC/DC power stage is considered for interfacing with an energy storage system, which is capable of bidirectional power exchange with the DC grid or with the AC grid through the AC/DC power stage. A complete laboratory prototype was designed and developed, with the unified control algorithms implemented on a digital signal processor. The experimental results validated the operation of the full-controlled bidirectional dual-stage interleaved converter based on the specifications for the hybrid AC/DC grid, such as bidirectional operation, synchronization with the AC power grid, predictive current control, interleaved operation on both AC/DC and DC/DC power stages, DC-link voltage control for the DC grid, as well as the operation with different power levels. [ABSTRACT FROM AUTHOR]

To advance carbon neutrality policies, many countries are increasingly integrating Renewable Energy Sources (RESs) into their energy mix. However, for harnessing natural energy in power generation, RESs present challenges in output control, potentially leading to power imbalances. Such imbalances, when coupled with an excessive reliance on unpredictable RES, may necessitate the curtailment of grid-integrated renewable generation, halting production despite available capacity. This paper proposes strategies to mitigate the economic and operational efficiency impacts of increased RESs on the power grid. It focuses on the optimal operation of Battery Energy Storage Systems (BESSs) and Power to Gas (P2G) technology, which flexibly converts surplus electricity into hydrogen. By employing Mixed Integer Linear Programming (MILP) for optimization and Stochastic Programming (SP) for the management of the uncertainty of renewable energy output, this paper evaluates the anticipated benefits of BESS and P2G applications. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) play a crucial role in the global transition towards decarbonization and renewable energy resources (RERs). As EVs gain popularity, this has resulted in various challenges for the power grid, such as an intensified peak-to-valley load differential, causing transformer overloading. Vehicle-to-grid (V2G) technology has emerged as a promising solution due to its controllable charging and discharging capabilities. Mature business schemes can incentivize the development of V2G technology. However, the business schemes of V2G technology are still unclear. Therefore, this paper provides a comprehensive review of the business schemes associated with V2G technology, especially focusing on its feasibility and challenges with respect to the electricity market. In this paper, several business schemes with respect to the electricity market are explored by conducting extensive literature reviews, including peak-to-valley arbitrage, the spot market, demand–response (DR), frequency regulation, voltage regulation, spinning reserve, and black start. Next, application scenarios and real-world use cases of the V2G technology's business schemes are investigated. Furthermore, the challenges faced by the V2G technology's business schemes are assessed by considering the technical, economical, and social aspects. By identifying these challenges, it is important to highlight the existing shortcomings and areas of interest for V2G technology's research and development. This review contributes to a deeper understanding of V2G technology and its implications for the energy sector. [ABSTRACT FROM AUTHOR]

This paper's research question is to evaluate the potential impact of large numbers of battery electric vehicles (BEVs) on the future electric grid, and whether the flexibility of BEV charging can induce enough system benefits to remunerate BEV users for the change in their recharging pattern. The considered scenario refers to the Italian situation and what might occur through the year 2040, where a share of BEV stock of 40% can be foreseen, as well as significant increases in PV and wind generation. Although this study is focused on Italy, its results are applicable, with minor differences, to several EU countries. This paper first shows that the future impact of increasing penetration of BEVs appears to be compatible with the expected growth of generation from renewable energy sources (RES) and the corresponding reduction in fossil fuel-based generation. It also gives an estimate of the CO2 emission reduction resulting from these changes, considering an unmanaged BEV charge profile and two different managed profiles that shift the car's charging period to hours of the day when they have no negative impact on the grid and maximize the utilization of RES. Finally, it shows an evaluation of the economic benefits of displacing private car charging ranging from 4 to 10 cEUR/kWh, which could be used as tariff incentives to stimulate this displacing in recharging time. [ABSTRACT FROM AUTHOR]

This document discusses the challenges of achieving high-power quality in modern power grids with a large share of distributed power production, particularly due to the integration of renewable energy sources (RES). The variable nature of RES can lead to disturbances and power quality degradation. The document highlights the importance of voltage source converters and control systems in enabling the flexible operation of RES. It also mentions the concept of microgrids, which are closely connected to power quality and other factors such as the Internet of Things and cyber security. The document includes eight research papers covering various topics related to power quality analysis and control of renewable energy sources in power grids. These topics include power factor correction, supercapacitor parameters identification, pulse width modulation, disturbance analysis, vibration analysis of motors, control of converters, phasor measurement units, and optimization of controller parameters. The document concludes by expressing gratitude to the authors, staff, and reviewers involved in the research papers. [Extracted from the article]

The increasing penetration of renewable energy sources (RESs) in transmission and distribution systems presents several challenges for grid operators. In particular, the unpredictable behavior of RESs can disrupt the balance between energy production and load demand, potentially affecting the stability of the entire system. Grid-connected energy storage systems (ESSs) offer a possible solution to manage the uncertainty associated with RESs. In fact, ESSs exchange power with the grid through the adoption of suitable energy management strategies, which are typically implemented by power electronics-based grid interfaces. Unlike other current source converter (CSC) solutions described in the literature, which only interface with a single energy storage device, this paper introduces a novel topology for a three-phase delta-type current source converter (D-CSC), which is capable of integrating three independent ESSs using the same number of semiconductors as traditional CSC solutions. Thus, it considerably enhances the flexibility of a power conversion system (PCS) without increasing the number of converter components. In addition, an innovative energy management control strategy is also introduced. This strategy enables the D-CSC to compensate for energy imbalances arising between the three ESSs, which might be caused by several factors, such as different aging characteristics, converter component tolerances, operating conditions, and temperature drifts. Hence, the D-CSC-based interface is capable of proper grid operation even if the three ESSs have different characteristics, thus opening the possibility of employing this converter to integrate both first and second-life devices. First, the topology of the proposed D-CSC is introduced, followed by a detailed mathematical description of its control strategy. The proper grid operation of the D-CSC was tested under different scenarios, considering the grid integration of three independent superconducting magnetic energy storage systems in a marine vessel. The proposed D-CSC is compared to traditional CSC solutions, highlighting the superior performances of the novel converter topology in terms of efficiency, total harmonic distortion of the output currents, and overall cost reduction for the PCS. [ABSTRACT FROM AUTHOR]

As the global transition toward sustainable energy gains momentum, integrating electric vehicles (EVs), energy storage, and renewable energy sources has become a pivotal strategy. This paper analyses the interplay between EVs, energy storage, and renewable energy integration with Indonesia's grid as a test case. A comprehensive energy system modeling approach using PLEXOS is presented, using historical data on electricity generation, hourly demand, and renewable energy, and multiple scenarios of charging patterns and EV adoption. Through a series of scenarios, we evaluate the impact of different charging strategies and EV penetration levels on generation capacity, battery storage requirements, total system cost, renewable energy penetration, and emissions reduction. The findings reveal that optimized charging patterns and higher EV adoption rates, compared to no EVs adoption, led to substantial improvements in renewable energy utilization (+4%), emissions reduction (−12.8%), and overall system cost (−9%). While EVs contribute to reduced emissions compared to conventional vehicles, non-optimized charging behavior may lead to higher total emissions when compared to scenarios without EVs. The research also found the potential of vehicle to grid (V2G) to reduce the need for battery storage compared to zero EV (−84%), to reduce emissions significantly (−23.7%), and boost penetration of renewable energy (+10%). This research offers valuable insights for policymakers, energy planners, and stakeholders seeking to leverage the synergies between EVs and renewable energy integration to pursue a sustainable energy future for Indonesia. [ABSTRACT FROM AUTHOR]

With the continuous expansion of the scale of power generated by grid-connected renewable energy, the form and operation characteristics of power grids have undergone significant changes, and the power electronic characteristics of power systems are prominent, resulting in the frequent occurrence of wide-band oscillation problems when renewable energy power generation equipment is connected to a power grid. Oscillation has the characteristics of nonlinearity and has an oscillation frequency ranging from a few hertz to several thousand hertz or more, which seriously threatens the stable operation of power grids. This paper summarizes the wide-band oscillation events that occur worldwide under the background of renewable energy access to power grids, classifies the wide-band oscillation events according to the distribution of oscillation frequency bands, and sorts out the characteristics of various oscillations. From the perspectives of the source side and network side, the existing oscillation suppression measures are classified and prospected. [ABSTRACT FROM AUTHOR]

In the modern power grid, characterized by the increased penetration of power electronics and extensive utilization of renewable energy, inverter-based power plants play a pivotal role as the principal interface of renewable energy sources (RESs) and the grid. Considering the stability characteristics of grid-following (GFL) inverters when the grid is relatively weak, the application of grid-forming (GFM) controls becomes imperative in enhancing the stability of the entire power plant. Thus, there is an urgent need for suitable and effective models to study the interaction and stability of the paralleled inverters employing GFL and GFM controls. Thus, the small-signal modeling with full-order state-space model and eigenvalues analysis are presented in this paper. First, the small-signal state-space model of the individual GFL and GFM inverters is obtained, considering the control loop, interaction, reference frame, transmissions, and time delays. Then, the models of the individual inverter are extended to the hybrid inverters to study the effects of the GFM inverters on the small-signal stability of the entire system. And the impacts of the inertia and damping are analyzed by the eigenvalues of the state-transition matrix. A case comprising three parallel GFL inverters and two GFL inverters with one GFM inverter, respectively, are studied to examine the effectiveness and accuracy of the model. Finally, the stability margin obtained from the eigenvalue analysis of the entire system is verified by time-domain simulations. [ABSTRACT FROM AUTHOR]

This paper presents a theoretical analysis of the selected properties of HCNG fuel calculations and a literature review of the other fuels that allow the storage of ecologically produced hydrogen. Hydrogen has the most significant CO2 reduction potential of all known fuels. However, its transmission in pure form is still problematic, and its use as a component of fuels modified by it has now become an issue of interest for researchers. Many types of hydrogen-enriched fuels have been invented. However, this article will describe the reasons why HCNG may be the hydrogen-enriched fuel of the future and why internal combustion (IC) piston engines working on two types of fuel could be the future method of using it. CO2 emissions are currently a serious problem in protecting the Earth's natural climate. However, secondarily, power grid stabilization with a large share of electricity production from renewable energy sources must be stabilized with very flexible sources—as flexible as multi-fuel IC engines. Their use is becoming an essential element of the electricity power systems of Western countries, and there is a chance to use fuels with zero or close to zero CO2 emissions, like e-fuels and HCNG. Dual-fuel engines have become an effective way of using these types of fuels efficiently; therefore, in this article, the parameters of hydrogen-enriched fuel selected in terms of relevance to the use of IC engines are considered. Inaccuracies found in the literature analysis are discussed, and the essential properties of HCNG and its advantages over other hydrogen-rich fuels are summarized in terms of its use in dual-fuel (DF) IC engines. [ABSTRACT FROM AUTHOR]

To face the growing electricity demand, several countries have adopted the solution of clean energy and use renewable energy sources (e.g., wind and solar) to reinforce the stability of the power network, especially during peak demand periods. Forecasting wind power generation is one of the important tasks for the network regulator. This paper deals with the probabilistic forecasting of hourly wind speed time series. In this approach, instead of evaluating a single-point forecast, an intraday interval prediction is provided, which allows modeling the probability distribution of the wind speed process at any specific hour. Practically, the quantification of uncertainty might be of particular interest for risk management purposes associated with wind power generation. The definition of interval prediction is based on the notion of conditional quantiles. In this paper, we introduce a new statistical approach, which deals with the nonstationarity behavior of the wind speed process, to define the conditional quantile predictor. The proposed approach was applied and evaluated on hourly wind speed processes. The suggested methodology provides accurate single-point forecasts using the conditional median as the predictor. Furthermore, the obtained hourly interval predictions are small and well adapted to the shape of the daily wind speed curves, which confirms the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Compared with the traditional grid-following photovoltaic grid-connected converter (GFL-PGC), the grid-forming photovoltaic grid-connected converter (GFM-PGC) can provide voltage and frequency support for power systems, which can effectively enhance the stability of power electronic power systems. Consequently, GFM-PGCs have attracted great attention in recent years. When an asymmetrical short-circuit fault occurs in the power grid, GFM-PGC systems may experience transient instability, which has been less studied so far. In this paper, a GFM-PGC system is investigated under asymmetrical short-circuit fault conditions. A novel Q-V droop control structure is proposed by improving the traditional droop control. The proposed control structure enables the system to accurately control the positive- and negative-sequence reactive current without switching the control strategy during the low-voltage ride-through (LVRT) period so that it can meet the requirements of the renewable energy grid code. In addition, a dual-loop control structure model of positive- and negative-sequence voltage and current is established for the GFM-PGC system under asymmetrical short-circuit fault conditions. Based on the symmetrical component method, the composite sequence network of the system is obtained under asymmetrical short-circuit fault conditions, and positive- and negative-sequence power-angle characteristic curves are analyzed. The influence law of system parameters on the transient synchronous stability of positive- and negative-sequence systems is quantitatively analyzed through the equal area criterion. Finally, the correctness of the theoretical analysis is verified by simulation and hardware-in-the-loop experiments. [ABSTRACT FROM AUTHOR]

The complexity of modern power grids, caused by integrating renewable energy sources, especially inverter-based resources, presents a significant challenge to grid operation and planning, since linear models are unable to capture the complex nonlinear dynamics of power systems with coupled muti-scale dynamics, and it necessitate an alternative approach utilizing more advanced and data-driven algorithms to improve modeling accuracy and system optimization. This study employs the sparse identification of nonlinear dynamics method by leveraging compressed sensing and sparse modeling principles, offering robustness and the potential for generalization, allowing for identifying key dynamical features with relatively few measurements, and providing deeper theoretical understanding in the field of power system analysis. Taking advantage of the this method in recognizing the active terms (first and high order) in the system's governing equation, this paper also introduces the novel Volterra-based nonlinearity index to characterize system-level nonlinearity. The distinction of dynamics into first-order linearizable terms, second-order nonlinear dynamics, and third-order noise is adopted to clearly show the intricacy of power systems. The findings demonstrate a fundamental shift in system dynamics as power sources transit to inverter-based resources, revealing system-level (second-order) nonlinearity compared to module-level (first order) nonlinearity in conventional synchronous generators. The proposed index quantifies nonlinear-to-linear relationships, enriching our comprehension of power system behavior and offering a tool for distinguishing between different nonlinearities and visualizing their distinct patterns through the profile of the proposed index. [ABSTRACT FROM AUTHOR]

The integration of renewable rnergy sources (RESs) into the power grid involves operational challenges due to the inherent RES energy-production variability. Imbalances between actual power generation and scheduled production can lead to grid instability and revenue loss for RES operators and aggregators. To address this risk, in this paper, we introduce a mutually beneficial bilateral trading scheme between a RES and a DR aggregator to internally offset real-time energy imbalances before resorting to the flexibility market. We consider that the DR aggregator manages the energy demand of users, characterized by uncertainty in their participation in DR events and thus the actual provision of flexibility, subject to their offered monetary incentives. Given that the RES aggregator faces penalties according to dual pricing for positive or negative imbalances, we develop an optimization framework to achieve the required flexibility while addressing the trade-off between maximizing the profit of the RES and DR aggregators and appropriately incentivizing the users. By using appropriate parameterization of the solution, the achievable revenue for the imbalance offsetting can be shared between the RES and the DR aggregators while keeping users satisfied. Our analysis highlights the interdependencies of the demand–production energy imbalance on user characteristics and the RES and DR aggregator profits. Based on our results, we show that a win–win outcome (for the RES and DR aggregators and the users) is possible for a wide range of cases, and we provide guidelines so that such bilateral agreements between RES and DR aggregators could emerge in practical settings. [ABSTRACT FROM AUTHOR]

The large-scale centralized development of wind and PV power resources is the key to China's dual carbon targets and clean energy transition. The vast desert–Gobi–wilderness areas in northern and western China will be the best choice for renewable energy development under multiple considerations of resources endowment, land use constraints, technical conditions, and economic level. It is urgent to carry out a quantitative wind and PV resource assessment study in desert–Gobi–wilderness areas. This paper proposed a multi-dimensional assessment method considering the influence of the power grid and transportation infrastructure distributions, which includes three research levels, namely, the technical installed capacity, the development potential, and the development cost. Nine main desert–Gobi–wilderness areas were assessed. The wind and PV technical installed capacities were 0.6 TW and 10.7 TW, and the total development potentials were over 0.12 TW and 1.2 TW, with the full load hours of 2513 and 1759 and the average development costs of 0.28 CNY/kWh and 0.20 CNY/kWh. Finally, this paper proposed the meteorological–electrical division distribution. A case study in the Kubuqi and Qaidam Deserts was carried out on wind–wind and wind–PV collaborative development across different meteorological–electrical divisions, which can reduce by 58% the long-term energy storage capacity and decrease the total system LCOE from 0.488 CNY/kWh to 0.445 CNY/kWh. [ABSTRACT FROM AUTHOR]

As the climate crisis worsens, power grids are gradually transforming into a more sustainable state through renewable energy sources (RESs), energy storage systems (ESSs), and smart loads. Virtual power plants (VPP) are an emerging concept that can flexibly integrate distributed energy resources (DERs), managing manage the power output of each DER unit, as well as the power consumption of loads, to balance electricity supply and demand in real time. VPPs can participate in energy markets, enable self-scheduling of RESs, facilitate energy trading and sharing, and provide demand-side frequency control ancillary services (D-FCAS) to enhance the stability of the system frequency. As a result, studies considering VPPs have become the focus of recent energy research, with the purpose of reducing the uncertainty resulting from RESs distributed in the power grid and improving technology related to energy management system (EMS). However, comprehensive reviews of VPPs considering their formation, control techniques, and D-FCAS are still lacking in the literature. Therefore, this paper aims to provide a thorough overview of state-of-the-art VPP technologies for building sustainable power grids in the future. The review mainly considers the development of VPPs, the information transmission and control methods among DERs and loads in VPPs, as well as the relevant technologies for providing D-FCAS from VPPs. This review paper describes the significant economic, social, and environmental benefits of VPPs, as well as the technological advancements, challenges, and possible future research directions in VPP research. [ABSTRACT FROM AUTHOR]

The number of electric vehicles (EVs) is growing exponentially, which presents the power grid with new challenges to turn their reliance to renewable energy sources (RESs). Coordination between the available generations from RESs and the charging time should be managed to optimally utilize the available generation from RESs. The dispatch scheduling of EVs can significantly reduce the impact of these challenges on power systems. Three different technologies can be used to manage the dispatch of EV batteries which are unregulated charging (UC), unidirectional grid-to-vehicle (G2V), and bidirectional vehicle-to-grid (V2G) technologies. This study aims to address the primary reason for EV owners' disbelief in the accuracy of battery wear models, which is impeding their involvement in V2G technology. This paper introduces a novel accurate EV battery wear model considering the instantaneous change in the operation of the EV battery. Moreover, an effective musical chairs algorithm (MCA) is used to reduce everyday expenses and increase revenue for V2G technologies in a short convergence time with accurate determination of optimal power dispatch scheduling. The results obtained from these three strategies are compared and discussed. The salient result from this comparison is that V2G technology increases wear and reduces the battery lifespan in comparison with the UC and G2V. The yearly expenses of G2V are reduced by 33% compared to the one associated with the UC. Moreover, the use of V2G technology provides each EV owner with USD 3244.4 net yearly profit after covering the charging and wear costs. The superior results extracted from the proposed model showed the supremacy of V2G usage, which is advantageous for both EV owners and the power grid. [ABSTRACT FROM AUTHOR]

In order to solve the problem of randomness and volatility caused by the rapid growth of renewable energy (RE), energy storage systems (ESSs)—as an important means of regulation—can effectively improve the flexible regulation capacity of power systems utilizing a high proportion of RE. Most of the current ESS capacity configuration procedures are carried out based on the typical scenario method or time series production simulation. This method tends to determine the size of the ESS configuration through multiple trial simulations. Uncertainty of simulation prediction data can result in the existence of an excess capacity or lack of configured capacity. In addition, this method reflects the ESS demand under specific targets, but it fails to fully utilize RE generation characteristics. The configuration process lacks the mathematical mechanism of RE consumption, and the calculation process is too complicated. In view of the shortcomings of traditional ESS optimal configuration methods, this paper examines the mathematical mechanism of RE consumption and proposes the ESS optimal configuration analysis method based on "equal area criterion". First, the principle of RE consumption is analyzed and the "RE consumption characteristic curve" is proposed according to RE characteristics. In addition, a working principle diagram of RE consumption, including ESS, is constructed to visually show the consumption capacity of RE and the working position of ESS. Then, the ESS optimal configuration process, based on the "equal area criterion", is proposed to achieve an accurate match between ESS capacity demand and RE consumption targets. Finally, the power grid of a region in China is taken as an example. We prove that the proposed method can save 1.41 × 103 MWh of ESS capacity and provide a more "mathematical" and "convenient" systematic solution for RE consumption and ESS optimization compared to the production simulation method. [ABSTRACT FROM AUTHOR]

This paper presents the VCHP platform as a solution to address PV curtailment and line congestion in scenarios of increasing renewable energy penetration. Solar PV generation profiles and load profiles were generated for three scenarios (2025, 2030, and 2035) using data provided by KPX. Modifications were made to the IEEE 30 Bus model to accurately reflect the Korean power system, including the introduction of PCA and LCA at relevant buses. Line congestion was evaluated using metrics such as TUR, STUR, and TLR. The research findings indicate that integrating the VCHP platform in all scenarios effectively alleviates line congestion, as shown by the TUR remaining below 1. Importantly, the reduction in line losses exceeds the decrease in power flow, demonstrating the effectiveness of VCHP in reducing power losses. The results suggest that as renewable energy sources increase, line congestion issues may arise in the existing power system. However, integrating the proposed VCHP platform is a valuable solution for effectively utilizing surplus PV energy and improving the stability of the power grid. The adoption of such a platform can significantly enhance the operation and management of the power system. [ABSTRACT FROM AUTHOR]

Changes are being implemented in the electrical power grid to accommodate the increased penetration of renewable energy sources interfaced with grid-connected inverters. The grid-forming (GFM) control paradigm of inverters in active power grids has emerged as a technique through which to tackle the effects of the diminishing dominance of synchronous generators (SGs) and is preferred to the grid-following (GFL) control for providing system control and stability in converter-dominated grids. Therefore, the development of the GFM control is important as the grid advances towards 100% inverter-based grids. In this paper, therefore, we aim to review the changing grid scenario; the behaviour of grid-connected inverter control paradigms and major GFM inverter controls, including their modifications to tackle low inertia, reduced power quality, fault-ride through capability, and reduced stability; and the state-of-the-art GFM models that are pushing the universality of GFM inverter control. [ABSTRACT FROM AUTHOR]

The energy transition hinges on the effective integration of renewable energy sources into the power grid. Islands can provide invaluable insights into the challenges and opportunities of integrating variable renewable energy into the grid due to their relatively small power systems, isolated grids, and diverse availability of renewable energy resources. This paper presents a study on the system benefits and challenges of marine energy integration in insular power systems, focusing on the Orkney Islands as a case study. A microgrid modeling approach that optimizes the mix of renewable sources and energy storage systems for future scenarios considering strategic time horizons (2030, 2040, and 2050) was employed. Results suggest that integrating ocean energies, namely, wave and tidal energy, yields notable benefits compared to traditional renewable energy sources exclusively. These benefits encompass reduced installed capacity, minimized energy storage requirements, lower excess generation, and overall cost-saving. [ABSTRACT FROM AUTHOR]

Grid-forming converters are considered a key technology for electrical grids with a high share of renewable energy. However, there is a lack of a general, robust and verifiable definition of what constitutes this behaviour. Therefore, this paper presents three simple scenarios that enable such a definition. They are based on simple black-box simulations that allow manufacturers to protect their development work. It can be shown that grid forming can be clearly distinguished from grid-following controls by their grid behaviour in the proposed scenarios. Extensive results illustrate this and also provide suggestions to deepen the understanding of grid-forming grid behaviour and its impact on system inertia. These findings should inspire the development of a clear definition and ultimately new requirements for converter systems. [ABSTRACT FROM AUTHOR]

The electrification of the transportation sector contributes to a cleaner environment in non-interconnected island (NII) systems or standalone islands. Moreover, e-mobility can significantly contribute to achieving very high renewable energy source (RES) penetration levels in islands, allowing a reduction both in the emissions due to the conventional generation and the system's cost. Ιncreased RES penetration, however, can pose technical challenges for an island's system. In order to overcome these challenges, new technologies like grid-forming converters are important. Moreover, the provision of new ancillary services in relation to battery storage systems might be considered, while novel control and protection schemes are needed to ensure secure operation. E-mobility can also contribute to solving technical problems that arise from very high RES penetration by providing frequency containment reserves or reactive power compensation. Since EV charging demand introduces modifications in the system's load curve, e-mobility may affect the power grid for long-term planning and short-term operation, i.e., line loading and voltages. The application of specifically developed smart charging methodologies can mitigate the relevant grid impact, while effective exploitation of EV–RES synergies can achieve higher RES penetration levels. This paper examines how e-mobility can contribute to increasing RES penetration in islands while considering the technical issues caused. In particular, this paper takes into account the distinct characteristics of NIIs towards the identification of solutions that will achieve very high RES penetration while also addressing the relevant technical challenges (voltage control, frequency control, short circuit protection, etc.). The effect of e-mobility in the power grid of NII systems is evaluated, while smart charging methodologies to mitigate the relevant impact and further increase RES penetration are identified. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive overview of the microgrid (MG) concept, including its definitions, challenges, advantages, components, structures, communication systems, and control methods, focusing on low-bandwidth (LB), wireless (WL), and wired control approaches. Generally, an MG is a small-scale power grid comprising local/common loads, energy storage devices, and distributed energy resources (DERs), operating in both islanded and grid-tied modes. MGs are instrumental to current and future electricity network development, such as a smart grid, as they can offer numerous benefits, such as enhanced network stability and reliability, increased efficiency, an increased integration of clean and renewable energies into the system, enhanced power quality, and so forth, to the increasingly growing and complicated power systems. By considering several objectives in both islanded and grid-tied modes, the development of efficient control systems for different kinds of MGs has been investigated in recent years. Among these control methods, LB communication (LBcom)-based control methods have attracted much attention due to their low expenses, recent developments, and high stability. This paper aims to shed some light on different aspects, a literature review, and research gaps of MGs, especially in the field of their control layers, concentrating on LBcom-based control methods. [ABSTRACT FROM AUTHOR]

The integration of large-scale wind and photovoltaic power into modern power grids leads to an imbalance between the supply and demand for resources of the system, where this threatens the safety and stable operation of the grid. The traditional mode of grid dispatch and the capability of regulation of conventional thermal power units cannot satisfy the demands of grid connection for large-scale renewable energy, where the system requires the compensation and coordinated dispatch of flexible power sources. In light of this problem, this paper establishes a model to quantify the uncertainty in the forecasted outputs of wind and photovoltaic power. This is used to develop forecasts of the output of wind and photovoltaic power for several groups of scenarios, and predictions with the best complementarity are selected as a typical set of scenarios by means of their generation, reduction, and combination. By taking full advantage of the complementarity in the rates of regulation of conventional thermal power and concentrating solar power (CSP), a coordinated model of dispatch for wind power, photovoltaic power, CSP, and thermal power is established for a number of typical combinations of scenarios. The influence of uncertainty in the outputs of wind and photovoltaic power on the dispatch of the power grid is examined, and different modes of dispatch are formulated through simulations to analyze the superiority of the dispatch strategy proposed in this paper in terms of abandoned wind quantity, abandoned solar quantity, and the cost of dispatch. [ABSTRACT FROM AUTHOR]

The transmission and distribution systems are essential in facilitating power flow from the source multiple loads over large distances with high magnitudes of voltages and currents. Hence, the monitoring and control of various components of these structures are crucial. Traditionally, this was implemented by sensing only the grid current and grid voltage parameters through coils, clamps, or instrument transformers. However, these have bulky structures that restrict them to the substation and have installation and maintenance issues due to their direct contact with high voltage conductors. Currently, the power grid is undergoing various developments e.g., penetration of renewable energy sources, remote control, and automation, bidirectional power flow, etc. These developments call for compact and energy-efficient sensors to sense multiple grid parameters such as the magnetic field data, temperature, humidity, acoustics, etc., to enable real time, wide area monitoring and the predictive maintenance of the power grid. The goal of this paper is to summarize the advancements in sensing technologies on transmission and distribution systems over a decade and to explain their role in the forthcoming expansion of the power grids. This paper aims to outline the current state-of-affairs of sensor technology as well as to fill research gaps by exploring their limitations. [ABSTRACT FROM AUTHOR]

The electricity market has increasingly played a significant role in ensuring the smooth operation of the power grid. The latest incarnation of the electricity market follows a bottom-up paradigm, rather than a top-down one, and aims to provide flexibility services to the power grid. The blockchain-based local energy market (LEM) is one such bottom-up market paradigm. It essentially enables consumers and prosumers (those who can generate power locally) within a defined power network topology to trade renewable energy amongst each other in a peer-to-peer (P2P) fashion using blockchain technology. This paper presents the development of such a P2P trading-facilitated LEM and the analysis of the proposed blockchain-based LEM by means of a case study using actual German residential customer data. The performance of the proposed LEM is also compared with that of BAU, in which power is traded via time-of-use (ToU) and feed-in-tariff (FiT) rates. The comparative results demonstrate: (1) the participants' bill savings; (2) mitigation of the power grid's export and import; (3) no/minimal variations in the margins of energy suppliers and system operators; and (4) cost comparison of Ethereum versus Polygon blockchain, thus emphasising the domineering performance of the developed P2P trading-based LEM mechanism. [ABSTRACT FROM AUTHOR]

Renewables are the greener substitute for the conventional polluting sources of generating energy. For their successful integration into the power grid, accurate forecasts are required. In this paper, we report the lessons acquired from our previous works on generating time-series ARIMA-based forecasting models for renewables. To this end, we considered a consistent dataset spanning the last four years. Assuming four different performance metrics for each of the best ARIMA-based models of our previous works, we derived a new optimal model for each month of the year, as well as for the two different methodologies suggested in those works. We then evaluated the performance of those models, by comparing the two methodologies: in doing so, we proposed a hybrid methodology that took the best models out of those two methodologies. We show that our proposed hybrid methodology has improved yearly accuracy of about 89.5% averaged over 12 months of the year. Also, we illustrate in detail for the four years under study and each month of the year the observed percentage of renewables and its corresponding accuracy compared to the generated forecasts. Finally, we give the implementation details of our open-source REN4KAST software platform, which provides several services related to renewables in Germany. [ABSTRACT FROM AUTHOR]

With the large-scale access of renewable energy, the randomness, fluctuation and intermittency of renewable energy have great influence on the stable operation of a power system. Energy storage is considered to be an important flexible resource to enhance the flexibility of the power grid, absorb a high proportion of new energy and satisfy the dynamic balance between the supply and demand of a system. At present, the cost of energy storage is still high, and how to achieve the optimal energy storage configuration is the primary problem to be solved. Therefore, the current research progress in energy storage application scenarios, modeling method and optimal configuration strategies on the power generation side, grid side and user side are summarized in this paper. On this basis, the shortcomings that still exist of energy storage configuration research are summarized, and the future research direction for energy storage configuration is prospected. This review can provide reference for the latest development and future research and innovation direction for energy storage configuration. [ABSTRACT FROM AUTHOR]

The forthcoming surge in electric vehicle (EV) adoption demands the comprehensive advancement of associated charging infrastructure. In this study, an exploration of EV charging's impact on the power distribution system is conducted via the simulation of a parking lot equipped with six distinct types of EVs, each showcasing unique charging curves, charging power, and battery capacities. A charging profile is synthesized and compared with laboratory-obtained data to ascertain the implications on the grid. To further understand the effects of smart parking on the power distribution system, a mathematical algorithm was created and applied to a segment of an urban electrical grid that includes 70 private residences. Basic electrical parameters were computed using the node voltage method. Four scenarios were simulated: (1) the existing distribution system, (2) the current system plus smart parking, (3) the current system plus 50% of houses equipped with 3.5 kW photovoltaic installations, and (4) the current system plus photovoltaics and smart parking. This paper examines the core distribution system parameters, namely voltage and current, across these four scenarios, and the simulation results are extensively detailed herein. [ABSTRACT FROM AUTHOR]

CO2 net neutralization by 2050 is a global target. Renewable energy and nuclear power generation are emerging as major power sources for CO2 net neutralization. Therefore, this paper comprehensively reviews the load-following operation method of nuclear power plants as a method to compensate for intermittency, which is the biggest weakness of renewable energy. First, this paper looks at the types of SMRs and elaborates the concept and necessity of load following. The comprehensive requirements for the load-following operation of an SMR, i.e., planned operation, automatic generation control, governor-free operation, cooperative control of the reactor and turbine generator, unit control of a multiple-module SMR, cogeneration, etc., are studied. Finally, the interaction between an SMR and the power grid during load-following operation and other technical issues are also reviewed. This paper can be used as a guide for load-following operations or as a guide for requirement analysis when developing a comprehensive control system of load following in SMR fleets. [ABSTRACT FROM AUTHOR]

The frequency stability of interconnected power systems becomes quite challenging when incorporating renewable energy sources (mostly wind power). Distributed model predictive control (DMPC) is an effective method to maintain stable grid frequency and realize power system load frequency control (LFC). This paper proposes a two-layer robust DMPC for the LFC of an interconnected power system. In the scheme, the wind power penetrating the power grid is largely affected by the environment condition, and it is taken as an uncertain disturbance to the power system. The two-layer robust DMPC consists of a nominal DMPC controller and an ancillary DMPC controller. The nominal DMPCs coordinate with each other in achieving the systemwide LFC objective, where the systemwide objective is a strict convex combination of the local LFC objectives. The nominal optimization problems are solved supposing the wind power fluctuation is zero. The ancillary DMPC generates the actual control signal for each generation unit based on signals which are transmitted from the nominal DMPC controller. The simulation on a four-area interconnected power system demonstrates the effectiveness of the proposed algorithm in alleviating the frequency deviation caused by varying the load and uncertain wind power fluctuation. [ABSTRACT FROM AUTHOR]

Considering the increasing amounts of renewable energy generation and energy storage required to meet ambitious environmental goals, it is clear that the next generation of power grids will be dominated by converter-connected devices. In addition, the increasing share of loads connected via power electronics and the general transition to non-synchronous grids with distributed generators make dc microgrids an attractive future alternative. However, achieving optimal utilization of distributed generators in such cases is a complex task, as the performance depends on both the grid and control design. In this paper, we consider such a case where the optimal utilization of distributed generators is achieved by optimal power sharing while taking into account the grid topology, the available generators, and the way they are controlled. For the latter, we consider a droop-based decentralized control scheme whose primary objective is to achieve voltage regulation in the allowable operating range. A novel mixed-integer optimization approach is proposed to identify the optimal converter size and location in the network so that the microgrid can operate safely and with optimal use of the available resources. Time-domain simulations are used to validate the proposed approach and demonstrate its robustness to uncertainty in generator availability. [ABSTRACT FROM AUTHOR]

The transportation sector is a significant source of greenhouse gas emissions. Electric vehicles (EVs) have gained popularity as a solution to reduce emissions, but the high load of charging stations poses a challenge to the power grid. Nuclear-Renewable Hybrid Energy Systems (N-RHES) present a promising alternative to support fast charging stations, reduce grid dependency, and decrease emissions. However, the intermittent problem of renewable energy sources (RESs) limits their application, and the synergies among different technologies have not been fully exploited. This paper proposes a predictive and adaptive control strategy to optimize the energy management of N-RHES for fast charging stations, considering the integration of nuclear, photovoltaics, and wind turbine energy with a hydrogen storage fuel cell system. The proposed dynamic model of a fast-charging station predicts electricity consumption behavior during charging processes, generating probabilistic forecasting of electricity consumption time-series profiling. Key performance indicators and sensitivity analyses illustrate the practicability of the suggested system, which offers a comprehensive solution to provide reliable, sustainable, and low-emission energy to fast-charging stations while reducing emissions and dependency on the power grid. [ABSTRACT FROM AUTHOR]

The reasonable allocation of the battery energy storage system (BESS) in the distribution networks is an effective method that contributes to the renewable energy sources (RESs) connected to the power grid. However, the site and capacity of BESS optimized by the traditional genetic algorithm is usually inaccurate. In this paper, a power grid node load, which includes the daily load of wind power and solar energy, was studied. Aiming to minimize the average daily distribution networks loss with the power grid node load connected with RESs, a site selection and capacity setting model of BESS was built. To solve this model, a modified simulated annealing genetic algorithm was developed. In the developed method, the crossover probability and the mutation probability were modified by a double-threshold mutation probability control, which helped this genetic method to avoid trapping in local optima. Moreover, the cooling mechanism of simulated annealing method was presented to accelerate the convergence speed of the improved genetic algorithm. The simulation results showed that the convergence speed using the developed method can be accelerated in different number BESSs and the convergence time was shortened into 35 iteration times in view of networks loss, which reduced the convergence time by about 30 percent. Finally, the required number of battery system in BESS was further built according to the real batteries grouping design and the required capacity of BESS attained using the developed method. [ABSTRACT FROM AUTHOR]

The application of fuzzy hybrid methods has significantly increased in recent years across various sectors. However, the application of fuzzy hybrid methods for modeling systems or processes, such as fuzzy machine learning, fuzzy simulation, and fuzzy decision-making, has been relatively limited in the energy sector. Moreover, compared to standard methods, the benefits of fuzzy-hybrid methods for capturing complex problems are not adequately explored for the solar energy sector, which is one of the most important renewable energy sources in electric grids. This paper investigates the application of fuzzy hybrid systems in the solar energy sector compared to other sectors through a systematic review of journal articles published from 2012 to 2022. Selection criteria for choosing an appropriate method in each investigated fuzzy hybrid method are also presented and discussed. This study contributes to the existing literature in the solar energy domain by providing a state-of-the-art review of existing fuzzy hybrid techniques to (1) demonstrate their capability for capturing complex problems while overcoming limitations inherent in standard modeling methods, (2) recommend criteria for selecting an appropriate fuzzy hybrid technique for applications in solar energy research, and (3) assess the applicability of fuzzy hybrid techniques for solving practical problems in the solar energy sector. [ABSTRACT FROM AUTHOR]

Recently, there has been a rise in the integration of renewable energy sources into power grids. As a result of this, there is a need to carry out new studies in order to understand the dynamics of power grids during disturbances that is mainly caused by the stochastic nature of wind energy. The operation of modern power grids that are tied to wind farms follows a stipulated grid requirement or grid codes, considering the allowable threshold frequency variation during grid dynamics. This paper presents a comparative study of two frequency control schemes considering grid frequency stability using two frequency control topologies. A novel dynamic flywheel scheme with a doubly fed induction generator (DFIG) variable-speed wind turbine with the coordinated control of excess kinetic energy and mechanical torque during operation was the first scheme, and a control strategy of an energy capacitor system (ECS) with a squirrel cage induction generator fixed-speed wind turbine (FSWT) was the second scheme. The salient part of this study was that the DFIG maximum point power tracking for effective smoothing of the output of the wind generator in the first scheme was designed based on the control strategy of its reference power to achieve smoothing of the wind power at the terminals of the wind generator. The model system employed in this work was a wind farm that is tied to a conventional power grid made of steam and hydro synchronous turbines. For an effective and fair comparison of results, the same natural wind speed was used in PSCAD/EMTDC for both schemes. When no control, Scheme 1, and Scheme 2 were implemented, the frequency dips were 47.20, 49.99, and 49.99 Hz with overshoots of 50.500, 50.005, and 50.001 Hz and recovery times of over 600.00, 0.01, 0.01 s, respectively, for the frequency variable. [ABSTRACT FROM AUTHOR]

Microgrid technology has recently gained global attention over increasing demands for the inclusion of renewable energy resources in power grids, requiring constant research and development in aspects such as control, protection, reliability, and management. With an ever-increasing scope for maximizing renewable energy output, there is also a need to reduce the curtailment of power on both the generation and demand sides by increasing forecasting accuracies and using resources more effectively. This paper proposes a dual-stage dispatch employing a novel "split-horizon" strategy, in a bid to enhance energy management in a standalone microgrid. The split-horizon is essentially the considered time horizon split into equal operational periods of the dual-stage dispatch. The proposed strategy utilizes a custom-designed novel variant of the inertia-weight-based particle swarm optimization (PSO), termed customized PSO, to perform the optimal schedule and dispatch operation by benefitting from the simplicity of PSO and customization as per the considered objectives. A modified IEEE 34-node test system is derived into a standalone microgrid with added distributed energy resources to test the proposed strategy, while another standalone microgrid, a modified IEEE 69-node test feeder, is also considered for scalability. Furthermore, the validation of the strategy is performed appropriately with a case study while also validating the proposed optimization algorithm. It is observed that the proposed energy management strategy provides approximatelya 7% reduction in costs. [ABSTRACT FROM AUTHOR]

The EU policymakers have adopted legislation to support communities taking responsibility for the energy transition. However, their development and integration are still in their early stages: many studies are performed without considering the overlapped social, economic, political, electrical, and information technology tasks simultaneously. This paper is the first to look at energy communities in their entirety, from the roles of the actors to the organisation, regulation, technical solution, and the market, to the use and business cases. The waterfall methodology was used throughout the work. The results show that energy communities can be viable by becoming reliable players so DSOs can better integrate the acquired flexibility and other services into their processes without compromising power supply. Their technical integration requires a coordinated operation and control of the entire power grid, including transmission and distribution, and the end-users, as proposed by the LINK holistic solution. The suggested fractal-based market structure, with the national, regional and local markets harmonised with the grid, facilitates the direct participation of small customers and distributed resources to the energy market. The results of this work may help policymakers, regulators, and industry representatives define new energy policies and processes related to research and development programs for implementing fully integrated renewable energy communities. [ABSTRACT FROM AUTHOR]

New techniques and approaches are constantly being introduced to analyze and enhance the transient stability of renewable energy-source-dominated power systems. This review article extensively discusses recent papers that have proposed novel and innovative techniques for analyzing and enhancing the renewable source-dominated power system's transient stability. The inherent low-inertia characteristics of renewable energy sources combined with fast-acting power electronic devices pose new challenges in power systems. Different stability concerns exist for grid-following and subsequent grid-forming converter/inverter connections to power grids; hence, distinct solutions for enhancing the transient stability have been devised for each. Moreover, the fundamental concepts and characteristics of converter/inverter topologies are briefly discussed in this study. Recent discussions and reviews of analysis and enhancement techniques in transient stability could lead to new ways to solve problems in power systems that rely primarily on renewable energy sources. [ABSTRACT FROM AUTHOR]

Since the power grid grows and the necessity for higher system efficiency is due to the increasing number of renewable energy penetrations, power system operators need a fast and efficient method of operating the power system. One of the main problems in a modern power system operation that needs to be resolved is optimal power flow (OPF). OPF is an efficient generator scheduling method to meet energy demands with the aim of minimizing the total production cost of power plants while maintaining system stability, security, and reliability. This paper proposes a new method to solve OPF by using incremental particle swarm optimization (IPSO). IPSO is a new algorithm of particle swarm optimization (PSO) that modifies the PSO structure by increasing the particle size, where each particle changes its position to determine its optimal position. The advantage of IPSO is that the population increases with each iteration so that the optimization process becomes faster. The results of the research on optimal power flow for energy generation costs, system voltage stability, and losses obtained by the IPSO method are superior to the conventional PSO method. [ABSTRACT FROM AUTHOR]

Inverters are playing an increasingly important role in the electrical utility grid due to the proliferation of renewable energy sources. Obtaining inverter models with accurate parameters is, therefore, essential for grid studies and design. In this paper, a methodology to estimate the output impedance and parameters of a residential grid-tied inverter is proposed. The methodology is first verified through simulation. A sensitivity analysis is conducted to determine the influence of the filter and controller parameters on the output impedance of the inverter. The simulated output impedance, voltage, and current are used in a parameter estimation methodology to obtain filter and controller parameters. It is shown that up to seven parameters can be estimated accurately. The proposed methodology is further investigated through a practical experiment. Two perturbation sources, the pseudo-random binary sequence perturbation and pseudo-random impulse sequence perturbation, are used, in turn, to perturb a residential grid-tied inverter that delivers up to 1.6   k W with the aim of obtaining its output impedance. The output impedances obtained through both pseudo-random sources are compared. It is shown that a pseudo-random binary sequence perturbation source applied in series between the grid and the inverter under test allows for the best estimation of the grid-tied inverter's output impedance. A black-box modeling approach aimed at estimating an analytical transfer function of the output impedance from experimental data is also discussed. [ABSTRACT FROM AUTHOR]

Smart grid integrates computer, communication, and sensing technologies into existing power grid networks to achieve significant informatization-related advantages. It will provide communication between neighbors, localized management, bidirectional power transfer, and effective demand response. Smart grids (SG) replace conventional grids by integrating various operational measures, including smart automation appliances, smart meters, and renewable energy sources. Regarding energy management and resolving energy issues, SG is one of the most cutting-edge and potentially game-changing innovations. Even still, its complexity suggests that decentralization may provide significant gains. Because of its increasing digitization and interconnectedness, it is also vulnerable to cyber threats. Blockchain, in this sense, is a potential SG paradigm solution that provides several great benefits. Even though blockchains have been widely discussed to decentralize and strengthen smart grid cybersecurity, they have not yet been researched in depth from an application and architectural standpoint. Blockchain-enabled SG applications are the subject of an in-depth research investigation. Electric vehicles (EVs), home automation, energy management systems, etc., are only a few of the many examples that have prompted the proposal of blockchain designs for their respective use cases. Information communication network security is of paramount importance. However, this evolving system raises cybersecurity issues. This paper aims to guide researchers in the right manner so they may build blockchain-based, secure, distributed SG applications in the future. This article also summarizes cybersecurity threats pertaining to smart grids. It starts with a description of a blockchain followed by the blockchain infrastructure, challenges, and solutions for different smart grid applications. A look back at the tried-and-true methods of securing a power grid is offered, and then it discusses the newer and more complex cybersecurity threats to the smart grid. In addition, models of common cyberattacks are presented, and the methods of defense against them are examined. [ABSTRACT FROM AUTHOR]