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The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

To achieve the optimum performance of electric transmission power system performance, the possibility of generators’ failure and the consequences are amongst the most important and real assumptions which should be taken into consideration. This paper aims to recognize the most influential factors on generators’ failures that can have a deep effect on the total cost and environmental issues. The integrated proposed approach is useful for investigating the generators’ failure effects on the performance of electric power transmission grids from the economic and environmental perspectives. In other words, the cost and pollution minimization policies are considered to decrease the unfavorable generators’ failure effects on electric power flow.

The data used in this study are gathered from a real case in USA in first step, the influential generator points that their failure has a significant effect on the objective function, have been recognized. Then, different failure scenarios are defined, and the optimum values in each of these scenarios through the GAMS modeling software are found. Consequently, by using a two-level factorial design approach, the critical generators across the power grid are determined.

The results show that by using such information, it is possible to detect the significant nodes in the power system grid and have a better maintenance plan. In addition, by means of this analysis and changing the capacity of main generators, it is possible to significantly reduce the operation costs. By comparing the indexes in case of the generator’s location, it seems that some of them are critical because of their capacity and position in the network (as their failure causes infeasibility in the model). Also, some of these deficiencies caused considerable index changes and critical consequences.

The integrated proposed approach is useful for investigating the generators’ failure effects on the performance of electric power transmission grids from the economic and environmental perspectives. In other words, the cost and pollution minimization policies are considered to decrease the unfavorable generators’ failure effects on electric power flow.

This paper endeavors to recognize the most influential factors on generators’ failures that can have a deep effect on the total cost and environmental issues.

The integrated proposed approach is useful for investigating the generators’ failure effects on the performance of electric power transmission grids from the economic and environmental perspectives. In other words, the cost and pollution minimization policies are considered to decrease the unfavorable generators’ failure effects on electric power flow.

This paper aims to reduce the impact of disordered charging of large-scale electric vehicles (EVs) on the grid. EV is great significance for environmental protection, energy conservation and emission reduction to replace fuel vehicles with EVs. However, as a kind of random mobile load, large-scale integration into the power grid may lead to power quality problems such as line overload, line loss increase and voltage reduction. This paper realizes the orderly charging of electric vehicles and the safe operation of the distribution network by optimizing the dispatching scheme.

This paper takes the typical IEEE-33 node distribution system as the research object, adopts the improved particle swarm optimization algorithm and takes the minimum operation cost, the minimum environmental pollution, the minimum standard deviation of daily load, the minimum peak valley difference of load, the minimum node voltage offset rate and the minimum system grid loss rate as the optimization objectives.

Controlling the disordered charging of large-scale electric vehicles by optimizing the dispatching algorithm can realize the full consumption of renewable energy and the safe operation of the power grid.

Results show that the proposed scheme can realize the transfer of charging load in time and space, so as to stabilize the load fluctuation of distribution grid, improve the operation quality of power grid, reduce the charging cost of users and achieve the expected research objectives.

High packet error rates and variable link capacity due to harsh electric power system environments make reliable communication a challenging task for WSN in smart grid. Therefore, to increase network reliability and hence, to improve smart grid system performance, there is an urgent need for reliable communication protocols. The purpose of this paper is to propose an Adaptive Forward Error Correction (AFEC) mechanism for different smart grid environments, including 500 kV outdoor substation and underground transformer vaults, to address these challenges.

This paper presents the comparative performance evaluations of proposed AFEC mechanism for different smart grid environments. Simulation experiments have been performed by extending the ns‐2 network simulator. It also introduces existing and potential smart grid applications, research challenges, and opportunities of smart grid.

Comparative performance evaluations show that the proposed AFEC mechanism achieves high communications reliability without causing unnecessary network overhead. Also the advantages of existing smart grid applications have been presented.

The paper shows that high communications reliability without causing unnecessary network overhead has been achieved. Also comprehensive reviews of WSN smart grid applications have been presented.

This paper aims to address a central concern in modeling and simulating electric grids and the information infrastructure that monitors and controls them. The paper discusses the need for and methods to construct simulation models that include important interactions between the physical and computational elements of a large power system.

The paper offers a particular approach to modeling and simulation of hybrid systems as an enabling technology for analysis (via simulation) of modern electric power grids. The approach, based on the discrete event system specification, integrates existing simulation tools into a unified simulation scheme. The paper demonstrates this approach with an integrated information and electric grid model of a distributed, automatic frequency maintenance activity.

Power grid modernization efforts need powerful modeling and simulation tools for hybrid systems.

The main limitation of this approach is a lack of advanced simulation tools that support it. Existing commercial offerings are not designed to support integration with other simulation software products. The approach to integrating continuous and discrete event simulation models can overcome this problem by allowing specific tools to focus on continuous or discrete event dynamics. This will require, however, adjustments to the underlying simulation technology.

This paper demonstrates an approach to simulating complex hybrid systems that can, in principle, be supported by existing simulation tools. It also indicates how existing tools must be modified to support our approach.

The purpose of studying the low voltage direct current (DC) microgrid, which uses computerised control system techniques, an orderly coordination control stratagem considering optimisation of a hybrid energy storage system (HESS) was projected in this paper.

The projected control stratagem was divided into three levels: topmost power dispatch level, transitional bus voltage regulation level and bottommost converter control level.

At the topmost power dispatch level, the cost of system stability was introduced, which is related with state of charge and discharging power of HESS.

Furthermore, the cost of system stability and HESS depreciation was compared with commercial price, and HESS switches its operating mode to discharge more at higher price or charge more at lower price to ensure the DC microgrid in economic operation. At the transitional bus voltage regulation level, DC bus gesturing is used as a control signal to achieve an autonomous decentralised operation of DC microgrid. The Matlab/Simulink simulation inveterate that the economical and autonomous decentralised operation can be achieved through the control stratagem.

This study aims to provide a solution of the power flow calculation for the low-voltage ditrect current power grid. The direct current (DC) power grid is becoming a reliable and economic alternative to millions of residential loads. The power flow (PF) in the DC network has some similarities with the alternative current case, but there are important differences that deserve to be further concerned. Moreover, the dispatchable distributed generators (DGs) in DC network can realize the flexible voltage control based on droop-control or virtual impedance-based methods. Thus, DC PF problems are still required to further study, such as hosting all load types and different DGs.

The DC power analysis was explored in this paper, and an improved Newton–Raphson based linear PF method has been proposed. Considering that constant impedance (CR), constant current (CI) and constant power (CP) (ZIP) loads can get close to the practical load level, ZIP load has been merged into the linear PF method. Moreover, DGs are much common and can be easily connected to the DC grid, so V nodes and the dispatchable DG units with droop control have been further taken into account in the proposed method.

The performance and advantages of the proposed method are investigated based on the results of the various test systems. The two existing linear models were used to compare with the proposed linear method. The numerical results demonstrate enough accuracy, strong robustness and high computational efficiency of the proposed linear method even in the heavily-loaded conditions and with 10 times the line resistances.

The conductance corresponding to each constant resistance load and the equivalent conductance for the dispatchable unit can be directly merged into the self-conductance (diagonal component) of the conductance matrix. The constant current loads and the injection powers from dispatchable DG units can be treated as the current sources in the proposed method. All of those make the PF model much clear and simple. It is capable of offering enough accuracy level, and it is suitable for applications in DC networks that require a large number of repeated PF calculations to optimize the energy flows under different scenarios.

To improve power system peak dispatching ability, connecting energy-storage device such as electric vehicle (EV) and regenerative electric heater (REH) to power grid is a good choice.

This paper establishes a multi-energy combined peak dispatching system MCPDS which includes EV, REH and wind power. The matter-element extension model based on improved variable weight theory is applied to evaluate MCPDS synthetic benefit.

The research shows that the MCPDS established in this paper performs excellently in security benefit, economic benefit, social benefit and environmental benefit.

With the assistance of energy storage devices such as EV and REH, the electrical system peak dispatching ability and power system operation efficiency has improved. More devices with energy-storage ability should be introduced into electrical power system to improve its synthetic benefit.

The need to address energy management as a significant innovation in the smart grid is emphasized to enable a more effective penetration of renewable energy to achieve energy savings and CO₂ emission reductions. The purpose of this study is to propose a holistic, flexible decision framework for energy management in a smart grid.

According to the situation actor process−learning action performance (SAP−LAP) model, the variables have been identified after a comprehensive analysis of the literature and consideration of the opinions of domain experts. However, the importance of each SAP−LAP variable is not the same in real practice. Hence, focus on these variables should be given based on their importance, and to measure this importance, an interpretive ranking process based ranking method is used in this study. This helps to allocate proportionate resource to each SAP−LAP variable to make a better decision for the energy management of the smart grid.

This study ranked five actors based on their priorities for energy management in a smart grid: top management, generator and retailor, consumers, government policy and regulation and technology vendors. Furthermore, actions are also prioritized with respect to performance.

The SAP−LAP model conveys information about the state of energy management in India to actors who may proceed or manage the flow of electricity. Additionally, this study aids in detecting vulnerabilities in the current energy generation, transmission and distribution technique. The synthesis of SAP results in LAP, which assists in recommending improvement actions learned from the current situation, actors and processes.

The SAP−LAP model is a revolutionary approach for examining the current state of energy management in a unified framework that can guide decision-making in conflicting situations, significantly the contradictory nature of India’s renewable energy and power sectors.

It is very indispensable for the various control centers of multi-transmission system owners (TSOs) grids to coordinate their reactive power optimization (RPO) efforts. However, such coordinated equilibrium point is comparatively hard to achieve unless one TSO control center could obtain all grids’ information in detail, which may lead to confidential issue and heavy communicating load. The purpose of this paper is to propose a solution to optimizing the reactive power control efforts among multi-TSOs grids with a mathematic interconnection model and reasonable communication cost.

Based on the interconnected power network equation, the stability-related optimum reactive power injection and the power-loss-related optimum reactive power injection were derived, respectively. Furthermore, according to the decomposition-and-coordination-based computing methodology, a coordinated RPO model for interconnected TSOs was designed, taking into consideration both the static voltage stability and economy.

The extreme values for the indicator L of power grid voltage stability and active power loss function were found and proved to be minimums. According to these extreme values, an expression for the reactive power injection at interconnected nodes between TSOs grids was obtained, and a coordinated strategy of RPO was established, which could take the static voltage stability and economy into consideration without confidential concern.

The existence of minimum values for indicator L of voltage stability and power loss was demonstrated, respectively. And the method presented in this paper can ensure the safety of information among different TSO grids, i.e. avoiding confidential issues. In particular, the coordinated control method can be implemented on the local power grid without knowing all of the parameters of its interconnection.