With the advancement of emerging power-to-gas (P2G) technologies, the integrated power and gas distribution system (IPGDS) with bidirectional energy conversion is becoming a promising measure to promote the integration of renewable-based distributed generation. This study proposes the linear network model for the IPGDS and takes the reactive power consumption of P2G into account. The linear model considering the network constraints of the IPGDS is implemented combining the Wendroff difference for gas network equations and the pyramidal approximation for power network equations. With the proposed linear network model, the economic dispatch of the IPGDS is studied considering distribution network reconfiguration. Both the overall positive role of P2G and the negative effect of P2G's reactive power consumption are analysed. The former helps to mitigate the voltage violations and to improve economic efficiency, while the latter reduces these benefits. Case studies in the integrated 33-bus power and 12-node gas distribution system validate the effectiveness and applicability of the proposed linear network model of the IPGDS and the necessity of considering P2G's reactive power consumption.

With the rapid development of artificial intelligence, adopting advanced deep reinforcement learning (DRL) methodologies to solve the optimisation problem in power systems has become more effective. This study proposes a novel energy control method associated with DRL to solve the economical optimisation problems in an integrated energy system with wind power and power-to-gas technology. To consider the randomness of wind power and the flexibility of upper-level energy prices, the economical optimisation problem is formulated as a finite Markov decision-making process. Cycling decay learning rate deep deterministic policy gradient (CDLR-DDPG) algorithm is proposed to obtain the optimal operation strategy. A comparison among different benchmark methods is provided to demonstrate the superiority of CDLR-DDPG algorithm in optimising an economical problem for the considered system.

Power-to-gas (P2G) provides a promising solution to accommodate wind power in recent years, which accelerates the integration of the power system and gas network, as well as the development of the integrated demand response. This study proposes a two-layer scheduling framework to coordinate P2G and FlexGas as demand response in the integrated power and gas system (IPGS) under wind power uncertainties. Firstly, the model for FlexGas technology is developed, enabling the end-users to switch between natural gas and electricity to produce heat. In the upper-layer optimisation, considering the optimal use of the linepack storage of the natural gas system, a two-stage stochastic scheduling model for the IPGS is established. In the lower-layer optimisation, the aggregated model reflecting the heterogeneity of the FlexGas users is derived. Simulation results on the integrated IEEE 39-bus power system and 27-node gas system show that the coordinated demand response can reduce the wind curtailment and improve economic efficiency for the IPGS. Moreover, the two-layer scheduling framework is validated to be effective and computationally efficient.

Developing integrated energy systems have been considered a feasible pathway to renewable-powered energy systems. The power to hydrogen technology is recognised as a promising method to enhance the economics of integrated energy systems and help reduce renewable curtailments. However, oxygen-enriched gas, which is the by-product of power to hydrogen processes (electrolysation), has not been fully utilised yet. It can be purified to produce medical oxygen at a low cost and may further increase the economics of integrated energy systems. Particularly, at this very moment, the consideration of the combined production of hydrogen and medical oxygen also has the potential to relieve the shortage of medical oxygen due to the outbreak of the 2019 novel coronavirus (COVID-19). This study proposes a model for the operation of integrated energy systems that consider the combined production of hydrogen and medical oxygen. This model is formulated as a convex mixed-integer optimisation problem that balances the electricity, heat and hydrogen demands every hour in a 24-hour period and balances oxygen demand on a daily basis. A test case of Taizhou City has been studied and results show that the combined production of hydrogen and medical oxygen improves the integrated energy system economics.

New challenges regarding system stability and efficiency arise when power systems operate with a high penetration level of inverter-based renewable sources (IBRSs) and few synchronous generators. Since IBRSs have been on the rise, to secure the stable operation of future power systems, IBRSs will be required to support systems without having to rely on remaining synchronous generators. Also, to efficiently manage the uncertainty of renewable production, power-to-gas technology can provide the required flexibility. This study proposes modelling and a control coordination scheme (CCS) of a wind-to-hydrogen (W2H) set to optimise electricity production from a variable-speed wind turbine generator (WTG) while helping balance between supply and demand in a system. To achieve this, a grid-forming (GFM) inverter-based WTG is modelled and a set of electrolyser and fuel cell is integrated at the DC circuit of a GFM-WTG to be coordinated. Furthermore, the CCS offers an opportunity to reduce the investment cost for deploying a W2H set by utilising the control capabilities of a WTG and reducing the need for an additional device. The performance of the proposed W2H set with the CCS was verified considering the variations in system load and wind speed by using Power System Computer Aided Design (PSCAD)/ElectroMagnetic Transients including Direct Current (EMTDC).

Power-to-gas (P2G) and gas-fired generation units (GFGUs) enable the bidirectional energy flow of integrated energy systems (IESs). The static security of IES should be analysed considering the interdependence between energy systems. In this study, the static security of IES is analysed, and a novel static security control strategy to improve the security of IES after N−1 contingency is proposed considering P2G. First, electricity–gas IES model is presented, and the multi-energy flow of IES is solved by the Newton–Raphson method. Then, N − 1 static security analysis is carried out for the electricity system and natural gas system. Based on the obtained Jacobian matrix during the energy flow calculation process after N − 1 contingency, variable sensitivity matrixes of voltage, gas pressure, branch power flow and pipeline flow to control variables are derived. Furthermore, a static security control strategy for IES based on the sensitivity matrices is developed to regulate operation statuses of P2G and GFGU and compressor outlet pressure to mitigate the violation of security constraints. The performance of the proposed analysis method and control strategy is evaluated by IES 4-12 and IES 118-48 test systems. The results demonstrate that the proposed control strategy can mitigate security risks of IES after N − 1 contingencies.

Different energy systems are generally planned and operated independently, which result in the low energy utilisation, weak self-healing ability and low system reliability. Therefore, an adaptive clustering-based hierarchical layout optimisation method is proposed for a large-scale integrated energy system, considering energy balance, transmission losses and construction costs. First, an adaptive clustering partition method based on energy balance and load moments is proposed to determine the optimal location of energy hubs and to allocate each distributed generation and load to different energy hubs, forming multiple regional integrated energy systems adaptively. Then, the proposed hierarchical layout optimisation model is formulated as to find the modified minimum spanning tree of the regional integrated energy system and multi-regional integrated energy systems, respectively, to construct an economical and reliable interconnection network. Finally, the effectiveness of the optimisation model and strategy is verified by simulations.

Due to the interaction between the planning and operation of micro energy network, considering the operation optimization can better play the role of micro energy network. But due to the influence of various uncertainties, the deterministic programming solution may be sub-optimal. In this context, the two-stage stochastic programming of micro energy network is of great significance. In this paper, from the perspective of electric energy, the closely related P2G, storage system and fuel cell are modeled as a whole, so that the model is simplified to a certain extent. Stochastic scenarios that considers multiple uncertain factors are constructed considering the correlation between electricity demand, wind speed and solar radiation intensity. And a two-stage stochastic programming model of micro energy network is established. Through the case study, the influence of P2GSS on micro energy network planning under uncertainty environment as well as the difference between stochastic programming and deterministic programming of micro energy network is analyzed. The simulation results show that P2GSS can reduce the economic cost and CO₂ emission of micro energy network planning solution. Through the comparison of different planning schemes, it can provides a reference for the planning and construction of the micro-energy network.

This study proposes an integrated energy system (IES) model consisting of natural gas system, electricity system, and power-to-gas stations (P2GSes), and then uses a centralised coordinated method to plan the IES. P2GSes can convert excessive renewable energy to natural gas and provide a promising approach to large-scale energy storage and long-distance energy transmission in the form of gas. However, considering the carbon emission of natural gas utilisation and high cost of P2G process, new embedded P2GSes will pose a threat to the economic and environment-friendly operation for the existing integrated energy system. Therefore, a more comprehensive P2G revenue objective, which is comprised of a secondary reserve service model, wind power integration model and carbon trading market participating model, is proposed in this study. The potential of P2GSes to provide the capacity of absorbing wind power and carbon reduction is innovatively and thoroughly evaluated in this study. The effectiveness of the proposed model is verified on an IES containing a coupled 24-bus electricity and 20-bus natural gas system. Simulation results show that it is optimal for the P2GSes revenue model to possess both capacities of absorbing wind power and converting the acquired power into natural gas as much as possible.

With the rapid development of renewable energy sources (RESs), adopting power-to-gas to improve the penetration of RESs is promising. This study designs a grid-forming application for the fuel cell/electrolyser (FC/ELZ) system to supply the frequency support for the grid as well as the voltage source. The detailed control methods including the DC, AC voltage controls and the power synchronisation control are designed for the FC/ELZ system so that it can operate independently without any other energy sources. Several simulation results are provided to demonstrate the effectiveness of the designed grid-forming application of the FC/ELZ system.

The traditional pure switched-capacitor equaliser brings the large inrush current and low energy density. This study proposes a series of resonant switched-capacitor (ReSC) voltage equaliser, which realises energy transferred directly from source cells to target cells by the series ReSC converter. The ReSC converter eliminates the inrush current and improves the capacitors’ energy density to increase the balancing speed. Meanwhile, all the switches are controlled by a pair of complementary PWM signals at a fixed operational frequency without voltage monitors. Both simulation and experiment are used to verify the system feasibility and theoretical analysis of the proposed circuit. In the same experimental condition, the proposed series resonant circuit reduces the inrush current. It improves the energy density of capacitors three times compared with the pure series switched-capacitor equaliser.

This study proposes a framework to analyse the concept of power to hydrogen (P2H) for fuelling the next generation of aircraft. The impact of introducing new P2H loads is investigated from different aspects namely, cost, carbon emission, and wind curtailment. The newly introduced electric load is calculated based on the idea of replacing the busiest international flight route in the Europe, Dublin-London Heathrow, by hydrogen fuel-powered aircraft as a high potential candidate for the next generation of air travel systems to cope with the ambitious targets set in Europe Flight Path 2050 by the Advisory Council for Aeronautics Research in Europe. The simulation is performed on a representative Irish transmission network to demonstrate the effectiveness of the proposed solution.

Integrating decarbonisation strategies for road transport and electricity is vital to minimise the overall cost of meeting the carbon target. This integration maximises the synergy across different energy sectors to improve the value and utilisation of investment, especially in low-carbon technologies across all sectors. This study presents an integrated multi-energy optimisation model to evaluate the economic performance and system implications of different road-transport decarbonisation strategies and analyse the synergy with the power sector decarbonisation. The large-scale optimisation model is formulated to consider the interactions across electricity, hydrogen, and transport sectors and used to determine the optimal solutions for investment and sector-coupling operation in the system. The proposed model is tested using a range of transport decarbonisation scenarios considering the deployment of electric or hydrogen vehicles or their combination and the integration with the power system. The studies analyse the economic performance and optimal energy system portfolios across different scenarios. The results demonstrate the importance of road-transport and power-to-gas integration in Great Britain's future energy system.

This review covers global maximum power point tracking (GMPPT) methods for photovoltaic (PV) systems under partial shading conditions. Unlike the previous review works that primarily focused on soft computing and hybrid GMPPT, this study gives exclusive attention to the improvement achieved by the conventional MPPT (perturb and observe, hill climbing, and incremental conductance). The improved methods include the popular 0.8 × V _oc model and, more recently, the skipping algorithms. In addition to providing qualitative descriptions of the available techniques, this work also attempts to provide a fair evaluation of GMPPT to determine their comparative performances. The competing algorithms, which are selected to represent every category (conventional and soft computing and hybrid MPPT), are benchmarked under carefully selected operating conditions and shading scenarios. The evaluation is focused on four main criteria: tracking accuracy, convergence time, length of voltage fluctuations, and transient efficiency during the search for the global maximum power point. The results obtained from this study can become a basis for researchers and designers to select the best MPPT technique for their respective applications.

To achieve clean and sustainable energy, the demand for renewable energy has been increasing day-by-day. As it is known the conversion efficiency of PV cells is very less, which motivates further research in the development of PV systems. Incorporating the power converters of less cost, more life-time, compact size, and preferably low complexity will address the above-mentioned limitation. To achieve optimum performance from PV systems for different applications especially in interfacing the utility to renewable energy sources, choosing an appropriate grid-tied inverter is crucial. The different types of PV inverter topologies for central, string, multi-string, and micro architectures are reviewed. These PV inverters are further classified and analysed by a number of conversion stages, presence of transformer, and type of decoupling capacitor used. This study reviews the inverter topologies for all PV architectures, which is new of its type. All the parameters such as merits, demerits, complexity, power devices of the aforementioned PV inverter are drafted and tabulated at the end of every classification. Different control strategies for balanced and unbalanced grid integration such as , , , fault ride through, and unified power flow control are discussed. This review would be helpful for researchers in this field to select a most feasible inverter for their application, as this study reviews considerable number of PV inverters on one platform.

Power grids all over the world are nowadays facing high penetrations of renewable power generation. The converter-based generation units play a major role in system behaviour and operation. Thereby, also the reliability of the power system is impacted in many different aspects. It has to be verified whether the frequency reliability assessment, which is often studied by simulations, is still accurate, every time a new control structure is considered. For this, the number of simulations should not be further increased if possible, in order to keep the computational efforts low. In this study, the authors verify that the assessment outcome will be accurate when the load duration curve (LDC) and wind power curve (WPC) of a system are described well enough. This is shown to be true for different frequency controls, implemented in wind power plants in the system. Besides, the effects of different LDCs and WPCs are analysed, as they can change over time. The used methodology is validated on the IEEE reliability test system (IEEE RTS).

Preservation of wind turbines (WTs) grid-connectivity during grid faults and grid-code (GC) compliant reactive power injection at PCC during voltage drops is an imperative task to perform in modern WTs. This is known as the low-voltage ride-through (LVRT) capability of WTs, emerging as an integral GC requirement. Despite current provision of LVRT in PMSG-based WTs, there is still likelihood of grid voltage drops leading to adverse effects in wind power plants. In this research, a peak current limiter has been designed for machine-side converter (MSC) of the PMSG-based WT to execute GC requirements in a reliable manner. This scheme is capable of preventing over-voltage across the dc link of back-to-back (BTB) converter and over-current in the grid-side converter (GSC). A dual current controller is utilised for regulating GSC positive- and negative-sequence components. A prominent feature of the proposed controller is its simplicity and applicability to available BTB control systems. On the other hand, the WT mechanical system operates as a storage device during voltage drops, eliminating the need for installing external apparatus such as energy storage systems and braking choppers across the dc-link. Simulation results conclude the reliable operation of the WT equipped with MSC current limitation scheme during grid faults.

Shade phenomena affect the PV module's power output, introduce multiple peak points in PV characteristics, and shorten the expected life cycle of the module. In order to prevent this issue, PV modules should reconfigure, namely, altering the electrical connections between PV modules based on the irradiance without changing their physical locations. As a result, the shading effects can distribute over the array and increase power output. This paper proposed a novel reconfiguration technique based on the simulated annealing algorithm to distribute shading impacts on 99 total-cross-tied (TCT) PV array. In this work, the proposed algorithm produces a reconfigured connection matrix for 99 TCT array that can minimize the current differences in each row and improve the power output. Various shading conditions have been taken to investigate the proposed technique by obtained global maximum power point (GMPP), current at GMPP, power loss, fill-factor, and efficiency. Further, the performance of the proposed technique is validated with other existing reconfiguration methods under partial shadings. In comparison with existing methods, the result shows that the proposed simulated annealing enhanced the power generation of the TCT array under all shading patterns.

In a DC microgrid, the anti-interference ability of bus voltage can easily become vulnerable due to low inertia caused by a large number of power electronic converters. This has already challenged the system stability and practicability in DC girds. In this study, a flexible virtual capacitance (FVC) control strategy with multiple constraints (MCs) is proposed to guarantee the security and stability of the DC microgrid, where the system stability, dynamic characteristics, actual operation requirements and realisability are considered as MCs. The FVC controller, which mainly modifies the reference current in voltage source converter by flexibly regulating virtual capacitance value, is given to provide inertial support and improve voltage quality. The stable operating boundary calculation based on small signal model and key control parameters design are further introduced into the control loop. This can ameliorate the dynamic response of the microgrid and obtain the better engineering practicability. Finally, experiment tests on a controller-level hardware-in-the-loop simulation platform are carried out to verify the validity of the proposed strategy.

Decline in photovoltaic (PV) output power is observed due to aging factors such as solder bond failure, corrosion of busbars, formation of cracks in solar cell, failures of bypass diode etc. Furthermore, these happenings reflect changes in PV module parameters such as increment in series resistance/reduction in open-circuit voltage and/or decrease in fill factor etc. However, these parameter variations can be easily examined with the module level I–V curve. This study proposes a new approach of exploring the I–V curve of the PV module using an inverter pre-startup condition, i.e. just before sending the PV power to the grid. From this pre-startup I–V curve, one of the important parameters, i.e. module series resistance is estimated. The proposed method is investigated through simulations in MATLAB/Simulink and is experimentally tested on a PV output coupled to a grid-connected micro-inverter. The key advantage of the proposed method is that it does not require any additional circuitry/sensors to extract the I–V curve. Furthermore, there is no need to disconnect the PV from its normal operation.

The large-scale wind energy conversion systems (WECSs) based on doubly-fed induction generators (DFIGs) are very popular in recent years due to the numerous technical and economic benefits. With the increasing penetration level of wind energy, the latest grid codes require the DFIG-based WECSs to remain connected to the grid under grid fault scenarios and deliver the required reactive power into the grid. However, the direct connection of the stator of the DFIG to the grid makes it prone to grid disturbances, especially to voltage sag. This study proposes a modified demagnetisation control strategy to enhance the low-voltage ride-through (LVRT) capability of the DFIG under grid faults. The proposed control strategy is implemented in a coordinated approach by using the existing demagnetisation control and the addition of an external resistance in the stator side of the DFIG. The demagnetisation control damps the direct current component of the stator flux and the external resistance accelerates the damping of the transient flux by decreasing the time constant and hence, enhancing the LVRT capability of DFIG. The effectiveness of the proposed control strategy is demonstrated under both symmetrical and asymmetrical grid faults simulated system through MATLAB/Simulink®. The comparative results justify the merits of the proposed methodology.

For large offshore wind turbines, pitch control is usually used for regulating generated power to the rated value and for mitigating the dynamic loads that at the wind speeds above the rated speeds. However, tracking the pitch angle accurately and quickly can hardly be realised due to complex operating environments, uncertain system parameters, various disturbances, and coupled effects between wind, wave, and turbine structure. In this study, an individual pitch control system based on a neural adaptive strategy is proposed to address the problems related to uncertain system parameters and various disturbances. The proposed control method can achieve zero error tracking for the pitch angle in a predefined finite time. The design and stability analysis for the proposed method is elaborated. A simulation model is established in Matlab/Simulink, and by comparing it with the traditional proportional–integral–derivative control method, the merit of the proposed control scheme is verified.

In this study, the stability analysis and controller design of a hydropower unit's governing system (HUGS) were studied based on a Takagi–Sugeno (T–S) fuzzy model and constant sampled-data control. First, according to the T–S fuzzy theory, the non-linear Francis hydro-turbine governing system under rigid water hammer is linearised and then the approximate linear system was obtained. Second, a fuzzy sampled-data controller was designed in the case of periodic sampling, and the closed-loop sampling system was discretised. After constructing the Lyapunov function and using the forward difference method, the stabilisation condition was given with less conservatism in a symmetrical linear matrix inequality form. Finally, the numerical simulation results showed that under four different sampling periods, the HUGS can quickly achieve stability and that it has different stability performance. In addition, the superiority of the controller was verified in comparison with traditional proportional–integral–derivative control and fuzzy control techniques.

Deploying the cloud energy storage system (CESS) is an economic and efficient way to store excess photovoltaic generation and participate in demand response without personal investment on pricy energy storage equipment. It is a shared battery energy storage system (BESS) for local residential and small commercial consumers, which is designed and controlled by the CESS operator. Based on the profit purpose, the CESS operator not only pursues the most economic operating strategy, but also tries to minimize the total investment on the design stage. This paper considers the investment on the batteries, power conversion system, reactive power compensation equipment and the cost including battery degradation cost and operation cost. The electricity price uncertainty and the voltage deviation of the CESS node caused by power exchange are also considered. Moreover, the cases of a largely centralized energy storage system and multiple distributed energy storage systems are all modelled. Finally, an original robust cooptimization model is transferred to a mixed integer linear programming model (MILP) and solved in GAMS. Numerical results based on historical data from 300 residential consumers in Australia present that the battery degradation cost and price uncertainty can't be neglected.

This study aims to improve oscillation damping and the rate of integration of wind energy into the grid. To this end, this study focuses on selecting the optimal location of flexible alternating current transmission system (FACTS) devices, such as the static synchronous series compensator, the static synchronous parallel compensator, and the unified power flow controller (UPFC). This study proposes new methods to determine the optimal locations of FACTS devices in the transmission system. To further improve power oscillation damping and the rate of integration of wind energy, FACTS devices were combined with a multiband power system stabiliser (MBPSS) at each synchronous machine. The MBPSS is an advanced power system damping controller that offers clear advantages over conventional power system stabilisers in the damping of low-frequency oscillatory modes. A comparative study was performed on the two-zone, four-machine (Kundur) multi-machine test network containing a wind farm to select the best combination of FACTS devices with the MBPSS. The results indicate that a combination of UPFC with MBPSS is favourable in terms of improving stability and increasing the rate of integration of wind energy into the grid.

In view of the faults of the doubly-fed wind power generator system, the health situations of the system are described by the health factor functions. On this basis, the model reference adaptive fault-tolerant control method based on clustering-type fuzzy neural network is proposed. The proposed method can solve the adaptive control issues of wind power generator system with actuator faults, external interference and model uncertainties. The stability and the tracking performance of the system are guaranteed by using Lyapunov stability theorem. Finally, the effectiveness of the proposed method is proved by the fault-tolerant control of the pitch system of the doubly-fed wind power generator.

The contribution of power because of the nonconventional energy sources is enhancing day by day. This gives rise to power converter connected to the grid for an integration and to utilize the nonconventional energy sources economically and efficiently. However, this causes the distortion in the grid voltages and currents. All advanced high precision operating machines and measuring instruments are sensitive to the harmonics of the grid voltages. Therefore, this work illustrates an improved control to supress the grid voltage and current harmonics caused by an integration of non-conventional energy source and nonlinear loads. An enhanced resonant two-degree of freedom proportional–integral–derivative (ER-2-DOF-PID) controller is used to extract fundamental components from load currents. It uses a resonant controller in shunt with PI controller to suppress the multi-order harmonics and steady state error. A DC-offset is used in parallel of this combination to suppress the sub-order harmonics. To suppress the peak overshoot during the load transients and insolation changes, a 2-DOF-PID controller is used. The presented control is investigated by developing its model in MATLAB environment and this is validated on a prototype developed in the laboratory. The controller is modelled and investigated for stability analysis using a Bode mathematical tool..

Worldwide, the hosting capacity of renewable energy sources (RES) is remarkably expanded in distribution systems. One of the most auspicious RES is wind turbine systems (WTSs), which can improve the performance of distribution systems. In turn, the integration of high WTS penetrations can also deviate the system operation away from the standard condition. To tackle this issue, we propose a method for enhancing the hosting capacity of multiple WTSs considering their intermittent generations in distribution systems. The proposed method considers the operation of the on-load tap changer (OLTC), allowing to solve voltage problems efficiently. Especially, the proposed method optimises the charging/discharging power of electric vehicles (EVs), which can contribute positively to regulating WTS intermittent generation. Additionally, the reactive power support of WTSs, complying with the IEEE 1547:2018 standard, is incorporated in the planning model of WTSs. To solve such an optimisation problem, a bi-level optimisation algorithm is developed based on the gravitational search algorithm. Comprehensive simulation results are performed on the 69-bus distribution feeder interconnected to four EV stations. Based on the results, the proposed approach can efficiently enhance/increase the hosting capacity of WTSs in distribution systems, thanks to the consideration of OLTC, reactive power support of WTSs and EVs.

Due to the rapid increase in electrical energy requirements in marine power systems (MPSs), and to reduce the consumption of fossil fuel, there is an emergent need to utilise renewable energy sources (RESs) in MPSs, which has been an attractive field of research. This research aims to present a novel load frequency control (LFC) scheme for a shipboard micro-grid (SMG) system. Therefore, a MPS with photovoltaic, wind turbine, hybrid energy storage system (ESS), and diesel generator (DG) have been simulated to relate an exact mobile islanded SMG. The system is designed using the transfer function models with the above said generating units and storage systems. Grasshopper optimisation algorithm (GOA) tuned fuzzy-based proportional–integral–derivative with filter control technique has been proposed to investigate the performance of the LFC scheme for the proposed SMG system. GOA and particle swarm optimisation optimised controllers have been designed and performance evaluation has been carried out on the conventional, adaptive neuro-fuzzy inference system, and fuzzy cascaded with a conventional controller. The responses obtained from the simulations for different cases are analysed to justify the novelty and superiority of the proposed technique for frequency and power regulation.