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The paper describes two main approaches of periodic control under variable frequency conditions: frequency adaptive multioscillatory control (FAMOSC) and fractional delay repetitive control (FDRC). The methods are applied in the control system of a grid-tie converter to increase the quality of phase currents in case of distorted grid voltages. The paper compares structures, performance and implementation of FAMOSC, FDRC and the conventional approach of repetitive and multioscillatory control. Performances of the control systems are illustrated with experiments on a laboratory test bench. The article describes tuning process of FDRC and FAMOSC with the usage of Particle Swarm Optimization algorithm. A detailed analyse and research of the techniques in terms of computational complexity is presented. Practical hints for implementation and resource optimization of both techniques on DSP are included. For FAMOSC a fast implementation of prewarping is proposed.

Electrical distribution networks are often inadequate to comply with the increasing load demand and to enable new installation of distributed energy resources. This inadequacy may result in upgrading existing transformers of in disconnecting the entire load during demand peaks, and into wasting a portion of the total renewable energy produced during favorable weather conditions. Increasing the capacity of electrical distribution network components is therefore mandatory in order to avoid these negative circumstances; however replacing lines and transformers is costly, and often the benefits are not worth the investments. Fortunately, the capacity of distribution networks can be unlocked by managing the electrical components by their dynamic ratings, allowing operating them even beyond their rated ampacity for a limited interval of time. This paper proposes a new risk-based procedure to manage distribution transformers by their dynamic rating. Probabilistic forecasts of loads and ambient temperatures are the inputs of the procedure, which are obtained in this paper from quantile regression forests. The procedure quantifies, in a probabilistic framework, the insulation thermal ageing due to the transformer (over)load in terms of the cost sustained for rewinding the transformer. The corresponding estimated risk is made available to the distribution system operator, who may therefore take a decision comparing it to an arbitrary level of risk coverage, favoring either the power delivery to customers or the reduction of the transformer ageing rate; this level is formulated in this paper having an intuitive physical meaning, thus enabling its setting also by non-expert operators. Comprehensive numerical experiments based on actual data are presented under different configurations and scenarios, in order to validate the proposal from an energetic and economic point of view.

Forward contracts are one of the prevalent and useful tools for managing the risks associated with the volatility of the electricity market prices. Forward contracts and day-ahead electricity market are executed simultaneously, and hence, they affect each other. This paper proposes a comprehensive supply function equilibrium model to consider the mutual interactions between forward contracts and the associated day-ahead electricity market in a power system. Negotiation between each producer and consumer in forward market is taken into account in the model. In order to consider the risk management behaviors of all market players in the model, a new risk management method is presented. The proposed risk management method takes into account the concerns of market players about the future prices of day-ahead market over the delivery period. The model proposed in this paper is applied to a test system with forward and day-ahead markets. The results are compared with the case that there is no forward contract in the power system. Impacts of growing the concerns of producers and consumers about the future, impacts of increasing demand uncertainty, impacts of improving bargaining power of consumers in contracting period and impact of contracting obligations for producers on the simulation results are discussed. The proposed risk management method is compared with CVaR method and its efficiency is evaluated. Finally, applicability of the proposed model to real size power systems is examined.

Short-term load forecasting (STLF) is the foundation of safe and stable operation for power systems. In recent years, large amount of intermittent wind power has integrated into the power system, which significantly increases the uncertainties of power load forecasting. Along with the gradual increase for the proportion of wind power in the power grid, the frequency stability problem attributed to wind power connection attracts increasing attention from various aspects. Fully considering the impact of the wind power factor, a method of probability density forecasting based on Least Absolute Shrinkage and Selection Operator-Quantile Regression (LASSO-QR) is proposed in this paper. Firstly, the significant explanatory variables are screened out from the historical power load and wind power factors based on LASSO algorithm via generalized cross validation (GCV), and the LASSO-QR model is established. Secondly, in combination with kernel density estimation (KDE) method, short-term power load probability density forecasting based on LASSO-QR is implemented utilizing Epanechnikov kernel function. Thirdly, the paper appraises the exactitude of the prediction interval (PI) in accordance with two criteria, prediction interval coverage probability (PICP) and prediction interval normalized average width (PINAW). Two real datasets from Ontario of Canada in summer and winter, are exploited to validate the LASSO-QR method. Fully considering the impact of wind power factor on the power load, experiment results demonstrate that the LASSO-QR method can construct more accurate PI and obtain more precise probability density forecasting results than quantile regression (QR). Contrastive analysis with the existing state-of-the-art methods further verifies superiority of the method proposed, which reduces the nondeterminacy of the prediction process to avoid large prediction errors and economic losses.

Distributed generation entities such as renewable energy sources have posed great challenges on power system economic dispatch because of their output variability and stochasticity. Accordingly, operators need to lessen unpredictable changes in scheduled generation settings by fully utilizing available forecast information in the decision-making process. This paper proposes a closed-loop algorithm for solving economic dispatch at runtime while reducing potential deviations of generation schedules. At first, a traditional centralized approach that addresses the economic dispatch problem is presented with discussions on potential enhancement enabled by model predictive control (MPC) techniques. The MPC application makes it possible for operators to address the concern of variability and stochasticity. This paper develops a dual decomposition-based distributed model predictive control (DDMPC) strategy that is compatible with consensus techniques. Different advantages of the proposed DDMPC are highlighted throughout the paper and are analyzed through simulations. The simulation results validate the advantages of the proposed DDMPC approach by comparing it with traditional techniques for economic dispatch and by another distributed method based on MPC.

The control mode adopted by a modular multilevel converter (MMC) in an HVDC transmission system directly affects both dynamic and steady-state characteristics of the system. This paper, benefiting from a comprehensive dynamic-phasor based state-space model of MMC, presents a comparative analysis on operational stability of the MMC-HVDC station in PV-control mode (i.e., in active-power and AC-voltage-control mode) and PQ-control mode (i.e., in active- and reactive-power-control mode). Firstly, corresponding to the MMC rectifier /inverter in PV- and PQ-control modes, four linearized small-signal models are developed in MATLAB, and validated by electromagnetic transient (EMT) simulations in PSCAD/EMTDC. Then, based on eigen-analysis, the impact of AC-system strength, quantified by the short-circuit-ratio (SCR) and impedance-angle, on the small-signal stability for a MMC rectifier /inverter under PV- and PQ-control are fully compared. Finally, based on the participation factor analysis and parametric sensitivity analysis, this paper digs more deeply into the essential state-variables and critical control-parameters that significantly contribute to the instability of the MMC system under a very weak AC-grid condition. The results show that the stability-margin of the MMC system, either rectifier or inverter, is essentially different when under PV- and PQ-control. This paper provides an effective approach, through adjusting the most sensitive control-parameters, to mitigate the MMC system instability at weak AC-grid conditions, which is a valuable guidance for parametric selection and adjustment in practical engineering.

Micro-grids (MGs) are appropriate solutions to various problems in power systems. Different types of energy sources such as renewable energy sources, combined heat and power (CHP) plants and distributed energy resources can be integrated in MGs. Local generation of mentioned energy systems can help system operators to satisfy energy demands with no need to the purchased power from grid. In this paper, a new optimization model based on mixed-integer non-linear programming (MINLP) is proposed to solve economic dispatch of MG containing CHP units, conventional power generators, heat-only units, wind turbines (WTs), photovoltaic (PV) system and battery storage system under uncertainties. The main goal of proposed paper is to find the optimal solution of economic dispatch of MGs in power systems in which technical constraints like AC power flow limitations are taken into account. In the proposed paper, the effects of dual dependency of produced heat and power by CHP units as well as the impact of electrical energy storage and heat buffer tank are studied in the optimal solution of economic dispatch of MGs. Uncertainties of renewable generation units, price of grid power and load are taken into account using scenario-based method, robust optimization approach and information gap decision theory (IGDT), respectively. The proposed model is studied regarding a 14-bus test system in various cases and the results are presented to evaluate the performance of employed methods.

This paper investigates the optimal grid reconfiguration (OGR) strategy in the smart grids with the random behavior of the many electric vehicle mobility (EVM) fleets and wind energy uncertainty. The increased utilization of EVMs in the power system with stochastic volatile behavior along with the high penetration of wind energy sources (WESs) can create new challenges in the system that will affect the system flexibility greatly. Here, the electric vehicle is mobile and there are distributed devices with deferrable options to supply energy at various times and locations. Accordingly, in this paper, the OGR is used as the remedial action to enhance the system flexibility to handle uncertainties. The main aim of this paper is to increase system flexibility and reduce expected operating costs by the coordination between EVM fleets, OGR and WESs’ uncertainty. Beside, this paper provides a novel method to evaluate the system flexibility while explicitly considering thermal unit generation and the EVM fleets. Numerical tests demonstrate the effectiveness of the proposed approach for analyzing the impact of EVM fleets on the system flexibility and hourly wind energy dispatch.

The increasing penetration of renewable energy resources (RERs) is challenging power grid planning and operation in maintaining grid reliability. Potential power grid reliability and stability issues may arise when large-scale RERs are connected to a weak power grid. These issues may become more significant due to the mutual interactions among RERs that are interconnected electrically close through a power network. Weakness analysis based on grid strength assessment is useful for identifying the potential weak grid issues. However, when taking into account the impact of the interactions among RERs, the weakness analysis becomes computationally challenging. Different combinations of points of interconnections (POIs) of RERs may have different impacts on grid strength at each POI. Due to the combination nature, such weakness analysis may be time-consuming when identifying the weakest combination of POIs from a large number of potential candidates in realistic power grids. To address this concern, the impact of the power network structure on grid strength is analyzed in this paper. It is found that the impact mainly depends on the impedance ratios at POIs. The findings can be summarized as two criteria to develop a recursive method for fast identification of the weakest combination in this paper. The efficacy of the proposed method is demonstrated through case studies on the IEEE 39-bus system and a realistic power grid.

In the paper results of the examination of ageing of stator insulation of rotating electrical machine are presented. Results of experiments given within this paper have been recorded over the 20 years’ period. The paper has predominantly experimental character. The experimental procedure has been improved over time and the obtained results were repeatable with a measurement uncertainty less than 5%. The experiments were performed on the samples taken from coil windings of standard type and whole coil windings. The samples are taken from the coil winding characteristic parts. The tests were carried out on the new and on the samples (coil windings) that were in use for several years. Under the well-controlled laboratory conditions, the impact of the technological process for the coil winding production, the time of use and the combined strain (temperature, humidity, mechanical strain and overvoltage strain) was tested on the conductor insulation of the coil winding. The parameters considered in this examination are the polarization index, the coefficient of proportionality and the lifetime exponent. By comparing results obtained on the samples with the results obtained on the whole coil windings, the effect of spatio-temporal increase in probability was noticed. From presented results, it can be concluded how the synergy of technological process of coil winding production, the time and the conditions of exploitation affect the rotating electrical machine lifetime.

Power to gas system is a new technology that enables integration of gas and electricity via an interface called electrolysis process. This system can produce methane by consuming electrical energy. These systems can inject limited volume of hydrogen to natural gas system directly, as well. On the other hand, security of networked energy hubs depends on contingencies which occur in main electrical lines or gas pipes and force the system to shed electrical or thermal load. This paper studies the role of power to gas unit presence on security and operation cost of networked energy hubs for the first time. This study shows that methanization capability of power to gas units can be so beneficial for system in hours which system’s main natural gas pipes have been lost by providing the lacked necessary natural gas energy. In addition, positive impact of power to gas on reducing the curtailment of wind based generation has been shown in this paper. In other words, proposed method brings out an alternative for provision of security of natural gas based thermal demands, using power to gas technology. The simulations which have been handled by GAMS software, validates the proposed method by illustrating the considerable decrement in operation cost of system which belongs directly to demand securities provision cost.

Under the current grid operation mode, reasonable integration of wind power is conducive to the exertion of its value. In this paper, the line flow transmission margin value considering wind power integration is assimilated into the locational marginal price (LMP). Accordingly, the LMP includes four components: energy consumption, network loss, congestion and line flow transmission margin. Based on the LMP difference of load nodes before and after wind power integration and the idea of power flow tracing, the specific values of different grid-connected wind farms at each node are evaluated, namely, the energy value and the network value of wind power. The load nodes that have a critical impact on wind power accommodation for each wind farm are identified. Moreover, the reserve cost caused by the uncertainty of wind power is considered, in which the maximum total value of all wind farms is set as the optimal objective. Finally, this paper analyses the LMP, value and accommodation of a single wind farm in detail through a microgrid system and an IEEE 118-bus system with multiple wind farms to verify the proposed method.

Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are revised according to their specific roles to provide a sound basis for novice researchers to undertake ongoing research on microgrids.

The pseudonym-based smart meter privacy-preserving schemes allow the fine-grained metering data to be preserved, which in turn enables many advanced measures to be applied into the electricity market, such as Incentive-Based Demand Response (IDR). However, in the currently known pseudonym-based privacy-preserving schemes that are compatible with IDR, there are two aspects that can be improved further. Firstly, the computational costs needed by the pseudonym registration protocol of these schemes are expensive that user devices are needed to run it efficiently, so this procedure is not transparent to customers. Secondly, customer’s involvement may cause the renewal procedure to be delayed and also weaken the effect against de-pseudonymization attack. Aiming at these two aspects, a user-transparent renewal scheme is proposed in this paper. In this scheme, the computational costs are reduced based on the restrictive blind signature, and the pseudonym renewal procedure can run in the smart meter without requiring any user’s intervention, i.e., this procedure is user-transparent. Furthermore, the user-transparent renewal scheme allows more stringent pseudonym renewal rules to be applied, so a coordinated renewal rule is proposed in this paper. Instead of allowing a customer to renew the pseudonym independently, all customers are required to renew their pseudonyms for every several days and the renewal procedure is conducted coordinately, which makes sure the pseudonyms getting renewed in time and also minimizes the information an attacker can get during the process. The scheme is proven to be secure in theory and the computational costs in main steps of this scheme are given. All show that the scheme proposed is effective.

This paper studies the stability issues of the Double Fed Induction Generator (DFIG) based wind farm in the power system with variable wind speed in strong and weak grid. With the intermittent generation of the wind power, it experiences instability and malfunction. The nature of Electromechanical Modes of Oscillations (EMOs) for DFIG incorporated into the multi-machine system under various conditions is explored considering system uncertainties. In this paper, the impact of Power System Stabilizer (PSS) and Static Series Synchronous Compensator (SSSC) on the stability of wind power system is analyzed by utilizing modified IEEE 14-bus test system. The rotor speed deviation is the objective function for particle swarm optimization and is formulated based on the transient and small signal stability. The transient and small signal stability investigations are performed by using time domain simulation and eigenvalue analysis respectively. The sensitivity analysis is carried out with degree of compensation of SSSC and coefficient of damping gain of PSS as sensitivity parameter. The performance of the modified test system is examined for transient and small signal stability for DFIG based wind farm for variable wind speed and grid strength considering different combinations of PSS and SSSC. From the results, it is noticed that oscillations in the system are minimized, damping, transient and small signal stability are enhanced and also the capability of synchronous generator and DFIG under extreme disturbance is intensified by optimization the coordinated controllers’ parameters. The analyses also show that damping ratio is improved for most of the EMOs. Sensitivity analysis identifies EMOs that have detrimental and beneficial impacts on the system.

In this paper, a new approach for designing groudging grid is proposed. The design is based on constracting an auxiliary annular grounding grid and transforming the lingtning rod’s grounding poing from main grounding grid to auxiliary grounding grid. Modal analysis and softwave simulataes is employed to obtain the transformed lightning current (and the voltage) and the reduced ressitance. The dual port model is used to calculate the impedance value of the grounding grid. The calculation results of the model are compared with the standard grounding body model EMF. At the same time, the relationship between the induced voltage of each point of the grounding grid and the distance of the lightning current injection point is studied by using the dual port model. The reduced resistance is simulated by building annular grounging grid model and square grounging grid model and making a comparison in performance betwen them. Farther, when there is a lingtning event, instead of providing a low impedance path by the main grounding grid, the design provide anther path by the auxilary grounding grid, which can transfer the lightning current into the auxilary grounding grid. All the model analysis and simulation results are presented and discussed in the paper.

As known, after AC transmission line fault occurs, LCC-HVDC inverter station has three different statuses: no commutation failure, single commutation failure and continuous commutation failure. And the different statuses of inverter station could lead to wrong operation of traditional protection principles (such as current differential protection and directional pilot protection). Firstly, the paper establishes inverter station’s equivalent model under different statuses and analyzes relationship between voltage and current vectors. Secondly, the paper analyzes the adaptability of conventional protection principles including current differential protection and directional pilot protection. Thirdly, using empirical mode decomposition algorithm, novel pilot protection principle suitable for AC transmission line which is connected to inverter station is proposed. The novel protection principle is only based on power frequency current signal of two ends, and it requires no time synchronization system. Eventually, a PSCAD/EMTDC simulation model of ± 800 kV LCC-HVDC and 500 kV AC transmission system is established. And the simulation results prove that the novel protection principle is immune to inverter station working status, fault resistance and fault type.

As known, hybrid high-voltage direct current (HVDC) is wide applied in power system. Because two converter stations are line commutated converter based HVDC (LCC-HVDC) type and voltage source converter based HVDC (VSC-HVDC) type respectively, the HVDC transmission line (HVDC-TL) has special travelling wave (TW) propagation characteristic. Especially, due to the capacitance installed at VSC-HVDC station, the relay at VSC-HVDC side cannot detect voltage TW (VTW) signal. Meanwhile, TW protection is widely applied in HVDC transmission system, but it has no fault direction recognition ability. Hence, the paper proposes a novel TW directional pilot protection. Firstly, the paper analyzes the special propagation characteristics of TW along HVDC-TL. Secondly, the paper proposes novel fault direction discrimination criterions based on the integration of instantaneous power and current at LCC-HVDC side and VSC-HVDC side, respectively. Meanwhile, faulty pole selection criterion is also proposed based on the ratio of positive pole current to negative pole current. Thirdly, based on PSCAD/EMTDC, a simulation model of ± 400 kV LCC-VSC-HVDC transmission system is established. And the simulation results prove that the proposed protection method is immune to fault location, fault resistance and fault type.

Modern distribution systems are mainly characterized by the behavior of non-linear consumer loads and their stochasticity, intermittency of renewable energy resources; and recurrent operation of Volt/VAr control devices. Conservation voltage reduction (CVR) has been adopted by most of the distribution utilities around the world as a viable technique for peak load shaving and long-term energy savings. Due to the diversified and inherent characteristics associated with the modern distribution systems with high levels of solar-PV penetration, achieving significant voltage reduction, high power factor, minimum number of tap changer operations and low power losses could be challenging. This paper has addressed the issue of VAr management in urban distribution systems while implementing CVR in the presence of highly intermittent solar-PV. Three conventional Volt/VAr control strategies were used to identify the specific technical aspects associated with CVR and VAr management in distribution systems in the presence of high solar-PV penetration. A case study on an urban distribution system with high penetration of solar-PV has been conducted in this paper. It is revealed that a carefully designed Volt/VAr control strategy is required for successful implementation of CVR under high penetration of solar-PV.

The development of electric vehicles (EVs) depends on several factors: the EV’s acquisition price, autonomy, the charging process and the charging infrastructure. This paper is focused on the last factor: the design of an EV fast-charging station. In order to improve the profitability of the fast-charging stations and to decrease the high energy demanded from the grid, the station includes renewable generation (wind and photovoltaic) and a storage system. Unlike other papers, this one uses a detailed model of the charging process that considers the arrival time and state of charge of electric vehicles. First, the Monte Carlo method is used to model the EV demand and the renewable generation. Later, a genetic algorithm (GA) optimizes the installation and operation of the EV fast-charging station. It finds the optimal solution that maximizes the profit measured by its net present value (NPV). Several cases are studied to analyse the influence of renewable energies and storage systems. The obtained results show that a mix of renewable energies and storage systems attains the best cost efficient solution.

This paper presents further contributions to smart grids cyber-physical security as a malicious data attack. The contributions are twofold. First, a formal proof of how parameter errors spread out on the measurement function having a parameter with error. The largest composed measurement error property, in its normalized form, is then demonstrated for this case of error. Second, a methodology for smart grid cyber-physical malicious data injection correction is presented. Current state of the art solutions corrects simultaneous attacks assuming measurements or parameters without error. However, how may one correct a measurement if the parameter might be simultaneously in error or the other way around? In this paper, a relaxed model strategy for such is presented. Attacks are processed simultaneously and analyzed using only the framework of measurement gross error analysis. Cyber-attack detection is made through a Chi-square (χ2) Hypothesis Testing (HT) applied to the normalized composed measurement error (CMEN). Composed errors are estimated with measurements’ innovation index (II). Cyber-attack identification is made through the largest normalized error test property. Cyber-attack correction is made considering cyber-attack type and using the composed normalized error (CNE) in a relaxed model strategy. The proposed solution works for malicious measurement and parameter data attacks. Still, the state estimation software does not need major changes. Validation is made on the IEEE 14-bus and 57-bus systems.

This paper proposes a novel simultaneous control interface and protection scheme for DC microgrids (DCµG) interconnected systems, although the interconnections could be possible via two power electronic systems such as DC/DC converter. Each DCµG presented in this paper is supplied by AC grid as well as battery bank unit, distributed generation (DG) unit and AC load unit. The proposed control interface is based on a developed suitable small signal model for each DCµG that provides proper power flow control and cancellation of interactions between DCµG. Also, the presented protection scheme for fast fault detection in DC link is based on fuzzy inference system (FIS), so that faults could be detected as quickly as possible in few milliseconds. In fact, the aim of this paper is simultaneous protection and control interface for DC multi microgrids, so that the performance of the controller and protection system is separate, yet integrated together. As such, DC multi microgrid performance under different events, such as change in active power of DGs and short circuit is not in trouble and disorder. Simulation results indicate the remarkable effectiveness of the proposed control interface and protection scheme for DCµG interconnected systems. For validation of the capability and feasibility of FIS fault detection scheme, simulated network and protection algorithm are implemented in laboratory-scale. The implementation results demonstrate that FIS protection scheme can swiftly detect faults within a few milliseconds.

DC is reappearing in the power system – it can be seen on the generation side as solar photovoltaics and wind farms with AC/DC/AC conversion; on the transmission side as HVDC lines and on the consumer side as a variety of modern electronic loads. Power distribution is an area where DC has not yet made any practically extensive appearance, this area is still in research phase. Related to DC distribution, the concept of DC microgrids is also witnessing a significant research contribution in the recent times. One of the research areas besides system control, protection etc., is the energy efficiency of the system. This paper gives an overview of the recent and relatively old research efforts in the field of efficiency/energy-savings analysis for the DC power distribution system. Furthermore, critical analysis of the previous research efforts has been provided and gap in the present body of knowledge related to this field has been identified. The requirements of a comprehensive analysis, mathematical modelling and system designing from a future study in this direction have been mentioned. The findings of this paper can serve as guidance for further investigation and research for the energy savings potential of DC power distribution networks.

The design of Shipboard Power Systems (SPSs) needs careful consideration of a variety of system specifications, operating constraints and design requirements under different operating scenarios and mission profiles to maintain a stable, reliable and economically efficient operation. Especially, for the state-of-the-art DC-based SPSs, with the extensive use of power electronic apparatus and the wide adoption of intelligent ship modernization techniques, the complexity and heterogeneity of on-board electrical systems significantly increase. Therefore, the corresponding specifications, regulations, and requirements that are tailored specifically for DC-based SPSs need to be developed to address the requirements of electric ship design, simulation, control, optimization, management, and automation. Given the limited amount of existing published works in this field, this paper aims to bring together different aspects of model-based electric ship design. It provides a thorough survey of design specification and requirement criteria along with their mathematical formulations that are of different importance, physical natures and time scales to address the transient and steady-state studies for the latest Medium-Voltage DC (MVDC) SPSs. This paper can be considered an attempt to provide a comprehensive study for the SPS research community from academia, industry, and Navy to facilitate various aspects of design, development, and deployment of the MVDC SPS applications.

The cheap quality fuel used by diesel engines in marine vessels during a stay at berth is an environmental threat, and its widespread gaseous emissions are harmful to human health. Shore to ship power technology has been an essential requirement for reducing the emissions of maritime transport at harbour areas. Although this technology has already been implemented at certain seaports in several countries like the USA, Canada, Germany, Sweden, Finland, Norway, Netherlands, and Belgium, it is facing some technical and regulation problems. Shore to ship supply can be emission-free, economical and sustainable solution while utilising the renewable energy sources such as photovoltaic and wind energies along with battery energy storages. This paper aims to provide a comprehensive review of technical aspects, practices, existing standards and the key challenges in designing and modelling of a harbour grid for shore to ship power supply. This paper presents state-of-the-art and future marine solutions, discusses shore to ship power technology while considering voltage, frequency, power and other technical requirements of vessels at onboard and onshore. Moreover, this paper contributes in designing suitable models for the harbour area smart grids that can facilitate both onshore power supply as well as charging of batteries for the future hybrid and electric vessels.

Distributed Generation (DG) systems are typically interfaced with distribution lines by modern power converter devices, which their controllers and dynamic behaviours are significantly influenced by unbalanced grid faults. The active and reactive power control with positive-negative sequences (PNS) is one of fundamental of power converter control under grid fault conditions. This paper proposes a reference current generator (RCG) based flexible power control strategy to enable regulation of active and reactive power with minimizing active and reactive power oscillations. Current limitation control is embedded into the RCG in order to keep maximum current injection in safety limitation for overcurrent protection under grid faults and harmonic distortions. The proposed control strategy has been also accomplished maximum active power and minimum reactive power transfer capability to electric grid. The analytical expression of active and reactive power oscillations depending on flexible control parameters are comprehensively investigated as theoretically and examined with simulations. Fractional order proportional integral (FOPI) controller is preferred to minimise steady state error of AC current regulation and provide faster processing time instead of conventional PI and proportional resonant (PR) controllers. An important contribution for similar previous studies is that PNS voltage and current components are separated by dual average filter based phase locked loop (DAPLL) which is firstly proposed in this paper. The performance of proposed controller is compared with multiple complex-coefficients filter (MCCF-PLL) based controller. Theoretical analysis and simulation results verify the correctness and effectiveness of the proposed solution.

Energy supply capability evaluation is of great significance to the planning and construction of integrated energy systems. In existing energy supply capability evaluation methods for the integrated energy systems, N-1 security at peak load is treated as a rigid constraint. It is not conducive to the effective utilization of equipment, and the impact of integrated demand response is not fully considered. To address these problems, this paper proposes a new evaluation method for the energy supply capability of regional electricity-heating energy systems, which models reliability as a flexible constraint and considers integrated demand response. First, this paper defines the energy supply capability of regional electricity-heating energy systems. Considering the structures of electricity and heat distribution networks, a reliable energy supply interval model is constructed. The maximum energy supply capability can be described by the boundary of the energy supply interval. Secondly, the impact mechanism of integrated demand response and multi-energy load transfer on reliability is extensively studied. A solution method of reliable energy supply interval boundary is proposed. On this basis, a fast reliability evaluation method for operating points is proposed. It then quantifies the load that the system can increase or need to reduce under a certain reliability constraint. In the case study, a real regional electricity-heating energy system is used to validate the proposed method. It is found that both relaxing reliability constraints or increasing integrated demand response participation can enhance energy supply capability of integrated energy systems.

Despite the fast, reliable and multi-purpose operation of MAS-based protection schemes, the inherent delay or failure of communication system must not affect the vital role of fault clearing, i.e., the ever-increasing renewables in distribution networks as well as network size increase has resulted in a heavy communication burden yielding to delay or even failure in communication. This fact will necessitate having an auxiliary algorithm to save protection system against any load curtailment. To affordably achieve this goal, this paper proposes a self-healing approach having the ability to temporarily replace the common MAS algorithms during emergency conditions. Accordingly, this paper, first, classifies the protection tasks into two hierarchical control levels; the first is responsible for clearing the fault while the second pursues some technical or economical goals. Next, using some less-considered capabilities of the common relays, a penetration-free algorithm is proposed to perform the first-control-level duties without MAS aid. Finally, the effectiveness of the proposed is proved on a practical distribution network. In general, this method can be a complement for the common MAS-based protection schemes to avoid any electricity interruption due to protection failure.

Subsynchronous Resonance (SSR) is a big concern for generator protection in power systems, especially with the wide deployments of series compensated lines. However, detecting SSR in an accurate and fast manner is a very challenging task. Various detection schemes were proposed over the years and they are summarized in this paper. Existing detection signal input options and signal processing techniques are reviewed. Furthermore, this paper proposes a new real time scheme based on Artificial Neural Network (ANN), Wavelet Transform (WT) and Short Time Fourier Transform (STFT) for accurate and comprehensive SSR detection. In the proposed method, signatures are extracted from the electrical and mechanical signals in the first step. Then an algorithm is designed to rank all the signatures and pick up the best performing subset of signatures. ANN is built from signatures contained in the best performing subset. IEEE second benchmark model for SSR study is used to simulate the signals for study in EMTP-type simulation environment. Test results with the generated signals show that the new SSR detection scheme achieves desirable speed, dependability and security for SSR detection. Further research will be done to apply the selected techniques and signatures in microprocessor relays.

This paper analyzes the problem of selecting the optimal access point in power grid for the offshore wind farm (OWF), which is increasingly integrated into the onshore power system by use of voltage-source converter based high voltage direct current (VSC-HVDC) transmission. The development of the selecting method includes three steps. First, three major factors, which have significant impacts on deciding the optimal location of the onshore VSC, are introduced, i.e., voltage support from onshore VSCs, voltage fluctuation caused by the change of wind power and construction costs of the VSC-HVDC transmission system. Secondly, three evaluation indexes that are corresponding to the three factors are put forward. Thirdly, in the face of this multi-objective programming problem, a linear weighted model is proposed in this paper and the comprehensive weight method based on the theory of information entropy and the analytic hierarchy process (AHP) method is adopted to get the weight coefficients. The method is carried out in a practical power system in China. The results demonstrate that the proposed methodology is an effective way for selecting the optimal access point of the OWF.

DC distribution networks and micro grids are gaining importance enabling the integration of hybrid distributed generation, energy storage units, modern loads including electric vehicles and different micro grid topologies, thus permitting the consequent development of DC Distribution Systems (DCDS). For maximum utilization of distribution network without compromising the security and reliability of the supply system, determination of critical loading is crucial. With this objective, this paper proposes a modified DC continuation power flow based approach for determining the loadability limit of the active DCDS. DC-DC converters play an important role in bus voltage regulation and system loadability. Impact of these converters must be accounted in any analysis and planning of active DCDS. In this paper, two different mathematical models of lossless DC-DC converters are developed to account them in power flow model of the system. The proposed approach can be applied to both radial and meshed DCDS. Impacts of integration of converters in the system are illustrated by results of two realistic DCDS and results are compared with the corresponding AC Distribution Systems (ACDS).

The ultra-low-frequency oscillation (ULFO) occurred in the hydro-dominant Yunnan power grid during its asynchronous interconnection with the China southern power grid in 2016, with the oscillation frequency at about 0.05 Hz. In view of this practical engineering problem, this paper analyzes the mechanism of this problem and puts forward the corresponding suppression measures. First, this paper utilizes the classical control theory to reveal the mechanism of the ULFO and analyze the effect of the governor parameters on the ULFO. According to the analysis, the ULFO will occur when the installed capacity of the hydro-power units is too large and the ratio of the hydro-power governor’s proportional parameter to the integral parameter is too small. Secondly, a new method to tune the governor parameters is proposed, the parameters tuned by this method can avoid the recurrence of the ULFO under different operation conditions. Finally, simulation verifications are run in a three-machine system and the Yunnan power grid using PSS/E (Power System Simulator/Engineering). The simulation results verify the effectiveness of the analysis and the measure.

The voltage source converters (VSCs) are the most important dynamic components in a VSC-based DC/AC power system. The renewable power generation, VSC-based HVDC lines and multi-terminal DC (MTDC) network are connected to the AC power system via the VSCs. This paper reviews the recent main research progress and conclusions on the small-signal stability of the VSC-based DC/AC power system. The review covers the study on the small-signal stability of a grid-connected single VSC system, an integrated VSC-HVDC/AC power system and the MTDC/AC power system. It is explained in the paper why the study so far on the small-signal stability of the VSC-based DC/AC power system has been focused on examining the dynamic interactions between the converter control and the phase locked loop (PLL), between the multiple VSCs as well as between the VSCs and synchronous generators (SGs). The paper is concluded by summarizing the main factors affecting the small-signal stability of the VSC-based DC/AC power system. Gaps of study are listed and analyzed to call upon further investigation in order to fully reveal the mechanism about why the VSC-based DC/AC power system may loss the small-signal stability.

This work presents a new methodology for the classification and substitution of power transformers in substations. The paper proposes the use of the operational vulnerability indicator, which consists of two groups of criteria, technical condition and operational condition. This indicator allows identifying which power transformers from a set of substations have priority for substitution, considering technical-operational information available in the substations. The technical condition is composed by the parallelism index, reserve transformer availability, nominal power and transformation ratio. Through criteria such as the parallelism index developed for this work, it is possible to identify the percentage of the load that is assured by a transformer in parallel at the moment of a contingency. The operational condition representing the physical situation of the power transformer, typically found in the literature as health index. It assesses factors such as deterioration of the cellulose paper that makes up the insulation and oil, age of the equipment and loading factor, resulting in a life expectancy for the power transformer. The operational vulnerability indicator can be used as an important guide for the strategic planning of the resource application of electric power companies. The methodology is verified through a case study involving real data from 7 substations and 39 power transformers, belonging to a Brazilian electricity company. In the validation of the method, the effectiveness of the proposed method is compared with the ranking obtained through the traditional health index.

IEC61850 protocols aim to reduce the data management with a bandwidth that does not present any issues. Fast tripping protection schemes using IEC 61850 will lead to network flooding, high delay, and reduced network security. The study provides propagation characteristics of traveling wave with extra high-speed busbar protection in compliance with IEC 61850 technique. This paper analyzes the process bus and suggests two methods in order to achieve the intended fast protection with IEC 61850. The simulation of the suggested methods based on the OPNET Modeler has proven that these methods can solve the network flooding problem in Ethernet and band-limited channels such as WLAN. This study will pave the way for researchers to reuse the traveling waves for fast protection with IEC 61850. In this paper, the simulation results of the case study busbar protection using transient signal (traveling wave) based on IEC 61850 network system configurations using OPNET Modeler simulation software were presented and the influence of data rate, a number of MUs sharing process bus and delay characteristics of these system configurations were evaluated.

Control of integrated utility grid plays important role, as renewable energy sources are rapidly increasing with installation of different Distributed Generation (DG) systems. Issues arising during the operation like interruption, disorder and uncertainty of network to be resolve. One of the situations is island state, and require to secure human beings and converter devices those are working in integrated energy sources environment. Fuzzy sets are to be identifying this state and these are updating with device control parameters of network like voltage, frequency. This paper presents a k-nearest neighbour Machine Learning ( k n n − M L ) to obtain Upper Limit (UL) Lower Limit (LL) of parameters for continuous fuzzy based state estimation. Also proposed k n n − M L helps to overcome existing challenges and motivate to better recognition of integrated network state. Outcomes of the paper, to update device control at every Abnormal Mode (AM) of operation and as when system parameter changes at different conditional operating modes. Non Detection Zone (NDZ) is also effectively reduced as per with knn parameter in both [LL, UL] mismatch cases. Mismatch cases of 50% to lower value of 10% is also successful tested with proposed method and a proper trip signal has been generated even at lower mismatch conditions. Effective outcome has been obtained with k n n − M L soft computing algorithm.

This paper proposes a comprehensive framework to investigate the potential role of grid-connected battery swapping station (BSS) with vehicle-to-grid (V2G) in improving the economy and reliability of the distribution system. For this aim, we first develop an empirical operating model considering operating characteristics of the distribution system with the BSS explicitly. Then, on this basis, a rolling optimization scheduling model of the distribution network is established. In particular, a refined BSS model including a new calculation method of available generation capacity (AGC) is included. Finally, a quantitative method to quantify the effect of BSS on reliability and economy of distribution networks is proposed. Compared with existing works, the main contribution of this paper is threefold. (i) A battery-level BSS operational model including AGC calculation is proposed to fully explore the V2G potential of the BSS. (ii) A rolling optimization scheduling model is established, which fully exploits the potential interaction between economy and reliability of system operation. (iii) An assessment framework is proposed to analyze the special value of BSS resources from aspects of both economy improvement and reliability enhancement, which can provide more practical instruction for BSS planning. Numerical studies are conducted based on IEEE 33-bus distribution network to verify the accuracy and efficiency of our approach. The simulation results show that if V2G of the BSS is orderly exploited and managed, the net profit of the distribution system will increase by 11.97%, and system expected energy not supplied (SEENS) will decrease by 14.34%. The reliability and economy are two contradictory factors, the dispatch model we proposed can achieve better economy with the same reliability level. The location of the BSS also has important effect of the economy and reliability of distribution system. © 2017 Elsevier Inc. All rights reserved.

This paper presents a multi-stage day-ahead and real-time optimization algorithm for scheduling of system’s energy resources in the normal and external shock operational conditions. The main contribution of this paper is that the model considers the non-utility electricity generation facilities capacity withholding opportunities in the optimal scheduling of system resources. The real-time simulation of external shock impacts is another contribution of this paper that the algorithm simulates the sectionalizing of the system into multi-microgrids to increase the resiliency of the system. The optimization process is categorized into two stages that compromise normal and contingent operational conditions. Further, the normal operational scheduling problem is decomposed into three steps. At the first step, the optimal day-ahead scheduling of system resources and the switching of normally opened switches are determined. At the second step, the optimal real-time market scheduling is performed and the switching of normally closed switches is optimized. At the third step, different extreme shock scenarios are simulated in the real-time horizon and the effectiveness of sectionalizing the system into multi-micro grids are assessed. Finally, at the contingent operational conditions, the optimal topology of the system and scheduling of energy resources are determined. The proposed method was successfully assessed for the 33-bus and 123-bus test systems. The algorithm were reduced the expected cost of the worst-case contingencies for the 33-bus and 123-bus systems by about 97.89% and 88.11%, respectively. Further, the average and maximum values of the 123-bus system capacity-withholding index for real-time conditions reduced by about 67.40% and 71.05%, respectively.

The integration of advanced Information and Communication Technologies (ICTs) in the conventional electric power grid is evolving into a Cyber-Physical Power System (CPPS). The seamless integration of control, communication, and computing operations allow CPPS to be fully monitored and controlled. Threats, vulnerabilities, and catastrophic attacks will intrude as CPPS monitoring, protection, and control functions advance. For the CPPS to operate safely, securely, and efficiently, sustainable cybersecurity solutions must be developed, and the power grid's reliability and resilience must be maintained even when exposed to unfavorable network conditions. While more distributed and renewable energy sources are connected to the grid, cybersecurity helps to ensure the supply of electricity is sustainable and of high quality. The validation of such sustainable cybersecurity analysis goes beyond the traditional power grid network analysis, which means that the test should integrate the physical and cyber system behavior and respond to the network attacks. To analyze the cybersecurity and cyberattacks in the practical CPPS, comprehensive and realistic CPPS testbeds are needed. The heterogeneous nature of the CPPS concept urges multidisciplinary testbeds with various functions and capabilities to evaluate the new cyber-attacks, vulnerabilities, and threats in CPPS. Using this CPPS testbed framework, the different types of cyber-attack can be detected, and detection algorithm can be evaluated, and helps to enhance the development of sustainable cybersecurity defenses for realistic CPPS environment with the increasingly dense integration of distributed energy resources (DERs). This Part-I paper review the CPPS testbeds in the view of the physical power system layer, sensing layer, communication layer, control layer, application layer, test platforms, and research goals with the fusion of cyber and physical systems. In addition, this review presented an overview, structure, and application-based evaluation of existing testbeds from the industry and institutions. The various research areas in CPPS are reviewed first to show the research trends on different aspects of CPPS which have gained significant attention in the past decade. The necessity of testbeds for cyberattacks and sustainable cybersecurity analysis in CPPS are then described. Finally, the NIST framework for CPS, CPPS domains, and research areas are presented. Further the Part-II paper will review the classification, overview, and assessment of CPPS testbeds.

This paper first analyzes the impact of the volatility of distributed power generation (DG) output on distribution network planning. This impact mainly includes three aspects: system equivalent load forecasting, distribution network planning decision, and stable operation of the system. To reduce the impact of this instability, this paper takes the wind power system as an example, and establishes the corresponding relationship model of the output state-year output scenario. Secondly, combined with the life cycle theory and multi-scene partitioning, a comprehensive decision-making objective function of the distribution network planning scheme for a single area considering investment operation costs, additional backup costs, energy-saving, and environmental protection benefits, and system reliability costs were established. Because of the many parameter calculations and selection judgments involved in the decision model, an intelligent decision framework based on Dempster-Shafer evidence theory and Multi-agent system (DS-MAS) is proposed after the decision target is established, that is, which can automatically select the fitting selection analysis parameters according to different conditions. Finally, the effectiveness of the model is verified by a practical example.

The paper analyzes grid strength and grid impedance for systems with significant penetration of power electronics. The work shows that the traditionally employed Thévenin equivalent cannot capture the different saturation states of power converters and therefore some classical definitions of grid strength based on short-circuit power at the point of connection fail to describe the system behavior. The paper proposes to map the impedance for all the different possible voltages at the point of connection and analyzes how the impedance depend on the voltage and angle of derivation for different possible simplified systems (grid-following converter in parallel with a Thévenin equivalent and grid-forming converter) considering the different saturation states of the converter. Numerical results and case studies are included as examples of the conducted analysis.

In recent years, the penetration of decentralized wind power generation in distribution networks has increased rapidly, and the uncertainties in wind power generation has posed great challenges on the operation of distribution networks. To this end, this paper establishes a distributed coordinated optimization model of integrated electricity-gas distribution networks considering power-to-gas (P2G) units and gas turbines to deal with the uncertainties of wind power output. First, this paper uses chance constraints to deal with the uncertainties of wind power output and converts it into a linear model that is easy to be solved. Secondly, considering the electricity distribution network and gas distribution network as different stakeholders, optimization models are established with the objectives of minimizing their respective operating costs, and the established models are solved in a distributed manner through the analytical target cascading (ATC). Finally, an integrated electricity-gas distribution system composed of the IEEE 33-node distribution network and 24-node natural gas network is used for simulation, which validate the proposed model and method.

This paper intends to give an effective hybrid planning of distributed generation and distribution automation in distribution networks aiming to improve the reliability and operation indices. The distribution automation platform consists of automatic voltage and VAR control and automatic fault management systems. The objective function minimizes the sum of the expected daily investment, operation, energy loss and reliability costs. The scheme is constrained by linearized AC optimal power flow equations and planning model of sources and distribution automation. A stochastic programming approach is also implemented in this paper based on a hybrid method of Monte Carlo simulation and simultaneous backward method to model uncertainty parameters of the understudy model including load, energy price and availability of network equipment. Finally, the proposed strategy is implemented on an IEEE 69-bus radial distribution network and different case studies are presented to demonstrate the economic and technical benefits of the investigated model. By allocating the optimal places for sources and distribution automation across the distribution network and extracting the optimal performance, the proposed scheme can simultaneously enhance economic, operation, and reliability indices in the distribution system compared to power flow studies.

Recently, the blockchain technology has attracted widespread attention due to its advantageous features, e.g., decentralization, transparency, traceability, and immutability. To make full use of renewable energy resources, new generation energy systems advocate the deep integration of information technology in real-world energy projects, among which blockchain has become one of the most used technologies. However, with the continuous development of related studies and projects, blockchain has begun to expose more and more limitations. As a result, the application of energy blockchain, i.e., blockchain applied in energy systems, is facing various challenges caused by these limitations. This paper briefly reviews popular application scenarios of energy blockchain, analyzes generic limitations of blockchain and their impacts on energy systems, and looks into possible directions that could deal with these limitations for future blockchain-based energy systems. We argue that blockchain is not a panacea for energy systems because blockchain’s component technologies have their own generic issues, and that the application of energy blockchain should be accompanied with improvement measures that conform to practical requirements of energy systems. As far as we know, this paper is one of the few works that deeply analyze the shortcomings of the blockchain technology and potential countermeasures in the energy field.

With the development of the active distribution system with multi-microgrids, increasingly numbers of distributed energy resources are integrated into the distribution network through multi-microgrids. As a result, the economic dispatch problem presents high dimensional complexity. Hence, this paper proposes a decomposition and coordination calculation method to reduce the computational dimension and improve the calculation accuracy. In this paper, the active distribution system with multi-microgrids is divided into two parts: one is the outer power grid and the other is the inner power grid, and the optimal value is obtained by applying the differential evolution algorithm. To improve the efficiency of the traditional network loss calculation, the network loss sensitivity is adopted to calculate the network loss. In order to verify the effectiveness of the proposed method, the test model is constructed based on the IEEE 33 node and 69 node distribution systems. The simulation results show that the proposed method can obtain the global optimal solution, and its economy is better than the overall centralized calculation method. This method is conducive to the subsequent application in the actual power grid system.

New energy centers such as wind power and photovoltaic power generation are generally too far away from the load center. Half wavelength AC transmission technology can solve this problem. However, harmonics may be generated when new energy is connected to half wavelength transmission system. Harmonics will do harm to the normal operation of power grid. Therefore, this harmonic resonance problem is studied in this paper. Firstly, this paper expounds the principles of classical resonance analysis method and modal analysis method, and explains the advantages of modal analysis method through analysis and calculation. Then, the grid connected resonance of large-scale wind farm and photovoltaic power station connected to half wavelength transmission system is studied by modal analysis method. The effects of transmission line length, the number of groups of wind power and photovoltaic inverters on typical modal harmonic resonance are analyzed. The results show that the length of half wavelength transmission line and outgoing line only affect the low-frequency harmonic resonance of some modes; The length of collector cable has an effect on the harmonic resonance of each typical mode; The number of wind power and photovoltaic inverter groups has an impact on the harmonic resonance of some modes, but will not change the location of resonance.

Traditional integrated energy market has problems such as single transaction type, opaque dispatch subsidies, and lack of institutions that can provide professional and fair services in the integrated energy market. Therefore, based on the smart contract of blockchain, this paper designs the cloud service platform for integrated energy market. The participants in the integrated energy market are divided into integrated energy suppliers and integrated energy users. The two can use the Digital Currency Electronic Payment (DCEP) to trade energy (carbon) in the blockchain smart contract provided by cloud service platform, as well as implement decentralized intelligent dispatch by using blockchain Internet of things technology. The smart contract designed by Antchain is used to simulate the energy trading and dispatch process of cloud service platform, and the verifiable simulation results are given. It is proved that the integrated energy market cloud service platform based on the blockchain smart contract designed in this paper can effectively realize not only the security and convenience of energy trading, but also the efficiency and intelligence of energy dispatch.

The active role of distribution system operators (DSOs) coordinated with the transmission system operator (TSO) is highlighted by increasing the competition of new parties in energy markets. Besides, combined heat and power (CHP) units are the primary heat supplier in district heating systems, and their electricity production is strongly coupled with heat productions. This paper evaluates an integrated model for scheduling electricity and heat with considering TSO–DSO cooperation to increase the operating efficiency in the day-ahead horizon. Also, this paper considers the cooperation of the electrical TSO, electrical DSOs, and district heating systems’ operators. The proposed model facilitates energy transactions between systems by considering intermediary variables. The share of each market party is calculated using intermediary variables and locational marginal prices of electrical and heating systems, and the values are compared to the cases with the isolated operating of energy systems. Also, the model considers thermal energy storage systems (TESs) and the heat transaction capability between neighbor systems, and the feasible convex region is used for the operation of CHP units. The DC power flow equations are used at the transmission level, while the AC power flow is used for distribution grids. The AC power flow equations are relaxed into the second-order cone programming (SOCP) formulation, which results in a mixed-integer second-order cone programming (MISOCP) problem. The proposed model is applied to the modified IEEE 24-bus test system, which contains electrical and heating systems at the distribution level. The result shows that the proposed model successfully reduces the operational costs and energy prices compared to the isolated scheduling of energy systems. Also, the model facilitates energy trading between market parties.

Wind power forecasting plays a vital role in enhancing the efficiency of power grid operation and increasing the competitiveness of power market. In this paper, a novel hybrid forecasting model is developed by using the decomposition strategy, nonlinear weighted combination, and two deep learning models to overcome the drawbacks of the linear weighted combination and further enhance wind power forecasting accuracy and stability. Firstly, the variational mode decomposition (VMD) technique is employed to decompose the original wind power series to extract local features. Then, the long short-term memory neural networks (LSTM) and deep belief networks based on particle swarm optimization (PSO-DBN) are utilized to construct sub-series prediction models. Finally, the multiple sub-series forecasting models are integrated by a nonlinear weighted combination method based on PSO-DBN to construct a hybrid model for short-term wind power forecasting. To verify the performance of the developed forecasting model, wind speed data of 10 min from a wind farm in Shaanxi Dingbian, China are selected as case studies. The results show that the proposed method in this paper is more effective than other existing methods.

Dynamic pricing strategy will play an increasingly important role in solving the contradiction between power supply and demand under the current electricity market environment. The performance of different users varies from the same pricing strategy, which further to exacerbate the difficulty of the optimal power dispatching. Therefore, a non-cooperative Stackelberg model based game theory is developed in this paper, which considers both the impact on load fluctuations in power grid and users’ dissatisfaction with electricity consumption. Firstly, users are divided into different types by induction and classification in this model to realize the comprehensive consideration of different types of electricity users. Secondly, two utility functions are set up in this model. The utility function of power supply side is set to represent the benefit obtained in the process of power supply by the power company. The utility function of the power demand side is set to express the dissatisfaction degree of electricity users. The developed model is solved by using the NSGA-Ⅱ algorithm in this paper. Finally, the developed model is applied to the actual case and the sensitivity analysis of relevant parameters is carried out to verify its effectiveness.