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This paper bestows 3-phase grid interfaced solar-wind hybrid renewable energy system (RES), feeding three-phase loads. The proposed system includes solar photovoltaic, permanent magnet based synchronous generator (PMSG), DC-DC converter, maximum power point tracker (MPPT) based on incremental conductance, three phases IGBT based voltage source converter (VSC), with a third order generalized integrator (TOGI) control technique. This control technique bestows multifunctional capabilities as harmonic mitigations, load balancing, and reactive power compensation. A fundamental component of load current is extracted by TOGI based controller, and further it is utilized to provide switching pulses to VSC for power quality enrichment. The fuzzy logic-based controller is used for loss computation of VSC as well as for maintaining DC link voltage. Moreover, fuzzy logic provides better dynamic performance compared to conventional PI controller. The results are presented in many aspects for linear and nonlinear loads such as, intermittent nature of solar and wind as well as disturbances in the system. A comparative analysis between proposed TOGI based controller and conventional control algorithm has been presented. Test results are performed by using MATLAB/ Simulink environment and demonstrate, AC-grid current is maintained within the IEEE-519 standard.

With the rapid development of EV in the transportation system, its increasing influence on the power system has attracted more and more attention in recent years. Under such a background, a virtual EV energy network (VEEN) in traffic level coupled with the correspond-ing power grid is formed in this paper, considering the energy carried by EVs in a specified area as a virtual node. To further identify the vulnera-ble components in the coupled energy network, a hybrid approach based on a complex network (CN) is presented. A hybrid power transfer distri-bution factor (HPTDF) is proposed for the coupled energy network con-sidering the variation of VEENs over time. Then, the line betweenness and the modified time-varying coupling net-ability are designed to eval-uate the vulnerability of the coupled network. Furthermore, to demon-strate the applicability of the proposed models, three case studies are per-formed on the 39-bus IEEE power network coupled with a 19-node VEEN. The simulation result verifies the effectiveness of the method in terms of identifying the critical lines in a coupled energy network, and a vulnerability assessment progress by designing a slow-fast dynamic cas-cade failure simulator in this paper verifies that a VEEN layer coupling defense strategy can decrease the vulnerability of a power grid layer un-der random attacks.

This work primarily focuses on electrical characteristics of a hybrid power system (HPS) incorporating renewable energy generation (REG) (HPSREG). The major components of HPSREG are the resources coordinated with multi-unit of photovoltaic cells, multi-unit of wind turbine generators, a diesel engine generator (DEG), energy storage system (ESS) with diverse nature and an electric vehicle (EV). The performance characteristics of HPSREG are determined by constant generation of power from the various sources as well as varying load perturbations. As the variation in load demand will introduce fluctuation in frequency and power with constant generation. In few of overcome the frequency and power deviation under both the above-mentioned generation and load demand conditions, proper control technique is required. In order to control the deviation in frequency and power, an integration in the environment of fractional order (FO) calculus for proportional–integral–derivative (PID) controller and fuzzy controller, termed with FO-Fuzzy PID controller tuned with quasi-opposition based harmonic search (QOHS) algorithm has been proposed. The results acquired with the proposed FO-Fuzzy-PID controller are then analyzed along with FO-PID and PID controller route for quantify effectiveness for the same under the considered cases to determine the effectiveness of the algorithm undertaken. Sensitivity investigation is also conducted in order to show the strength of the technique under study of differences in HPSREG parameters of magnitude.

In recent years, emphasis has been placed on the design and implementation of sustainable energy system solutions to combat the adverse environmental impact of emissions from the power and transportation sectors. This study applies a systems elimination method using numerical simulation to validate and optimise recently-reported results demonstrating the benefits of photovoltaic (PV)–diesel — battery hybrid integrated power systems (IPS) for commercial centres, with Abuja in Nigeria used for the case study. An optimal IPS was identified from 20,200 candidate solutions analysed by assessment against environmental (1st priority) and economic (2nd priority) metrics. Although environmental conditions were prioritised, the optimal system was economically viable. The environmentally optimal system emitted 33% less greenhouse gas (GHG) emissions (CO2 tonnes/yr.) than the economically optimised solution (PV–diesel) over their operational lifetimes ($/20 years), and was 4% costlier than same. The results demonstrate that carbon taxation or outright bans on independent fossil fuel systems (IFFSs) in emerging economies might not be effective policies in mitigating the impact of climate change on our environment. This study contributes to the body of knowledge on energising unserved and underserved communities in sub-Saharan Africa, considering the case study country of Nigeria. It decries the common practice of prioritising economic factors over environmental factors in optimising the operations of grid defected power system solutions as continental and regional electrification efforts are being ramped up. This is particularly of importance (an environmental responsibility), as immediate economic gains could have far-reaching environmental and social implications that elicits the limitations of economically prioritised power development projects in the offing.

This paper presents a sequential network‐flow graph‐based method for a steady‐state power flow solution in hybrid multi‐terminal power systems. The proposed method is a unique and novel one, which differs from other established methods that involve the use of modified versions of classical power flow methods. The proposed method formulates a power flow problem as a maximum network‐flow problem and solves it using a push‐relabel max‐flow algorithm. The solution procedure solves AC and DC parts sequentially, while accounting for voltage source converter losses using a generalised converter model. The proposed flow‐Augmenting method solves the power flow problem using matrix vector multiplication in its most abstract form, and it is independent of system parameters and network configuration. The proposed formulation is computationally efficient, as it is based on matrix vector multiplication, and is scalable, because the formulation works as a graph‐based method, which, inherently, allows for parallel computation for added computational speed. Further, unlike previously reported methods, the proposed method does not rely on Jacobian matrix formulation or any matrix inversion. This proves to be a strong advantage for the proposed method, as a significant reduction in computational time is observed, as a result. The proposed method is validated on 5‐bus hybrid system and CIGRE B4 DC system.

In this paper, the holomorphic embedding power flow method (HELM) is designed to solve the AC/DC hybrid power flow equations. According to the power flow model of the high voltage direct current systems (HVDC), an appropriate embedding technique with three recursive algorithms is developed for three different control modes, which is compatible with existing achievements of HELM for AC systems. In this method, the advantages of HELM, such as non-iterative, deterministic and non-ambiguous, are fully retained. In addition, a new calculation strategy based on Bauer's Eta algorithm is designed for the implementation of Pade approximations and the recursive process to avoid redundant calculations without reducing accuracy. In order to verify the reliability and effectiveness of the proposed extended HELM, several power flow cases with different scale are studied by HELM and traditional iterative method.

The hybridization of a renewable energy generator with an existing system in a specific building plays a vital role in solving many important problems of electrical energy systems such as reliability, cost-effective, and ecological option. In this perspective, a modified energy system is proposed in an existing building with integrated renewable energy using multicriteria decision analysis (MCDA). To achieve the sustainable energy solution, the hybrid power source configurations available in the locations are analyzed to ensure reliability using the HOMER software tool. Among these, the best configuration is identified by using the Best Worst Method (BWM) based MCDA approach. The study examined the technical, economic, and environmental perspectives for the achievement of the Sustainable Development Goals (SDGs) such as affordable, reliable, sustainable, and modern energy. The results of the survey in the building show that the best optimal hybrid configuration of the proposed location is the Gird-PV-Wind-based systems for the specific location based on the key techno-economic-environmental criteria of the SDGs.

The hybridization of power systems offers the low-emission and energy-efficient marine vessels. However, it increases the complexity of the power system. Design, analysis, control, and optimization of such a sophisticated system require reliable and efficient modeling tools to cover a wide range of applications. In this work, a typical DC hybrid power system model is developed using a bond graph modeling approach. Necessary component models of varying degrees of fidelity are developed and integrated to build a system model with reasonable accuracy. The developed system model, along with the rule-based energy management system, is used to simulate the entire system and to investigate the load-sharing strategies as well as the system stability in various operating scenarios. Moreover, the simulation results are validated with experimental results conducted on a full-scale laboratory setup of the DC hybrid power system and with a ship load profile. The results show that the system model is capable of capturing the fundamental dynamics of the real system. The hybrid power system model is further used to analyze the bus voltage deviation from its nominal value. The computational efficiency presented by the system is fairly good as it can simulate faster than real-time. The developed system model can be used to build up a comprehensive simulation platform for different system analysis and control designs. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

As large-scale offshore wind farms are integrated into the power grid, a hybrid multi-infeed HVDC (HMIDC) system including both LCC-HVDC and VSC-HVDC links is facing a critical steady-state voltage stability problem which mainly stems from a weak AC system under high-level DC power injections. To overcome this challenge, this paper proposes a general steady-state voltage stability analysis to accurately measure the critical voltage stability point of HMIDC systems. In this paper, a typical HMIDC system is firstly modeled as a general dual-infeed system composed of an LCC-HVDC, a VSC-HVDC, and a virtual equivalent voltage source behind a virtual equivalent impedance at the AC side. Then a hybrid power sensitive factor (HPSF) is established to indicate the critical voltage stability point with the consideration of dynamic power-voltage characteristics of HVDC links, as well as operational changes in AC system (e.g. dynamics of excitation voltage control in generator and network topology change). Finally, a general voltage stability index, called hybrid generalized short circuit ratio (HGSCR), is further derived to effectively explain the critical voltage stability point of HMIDC systems. Moreover, multiple comparative studies with existing voltage stability indices are conducted in this paper to verify the effectiveness of the proposed general steady-state voltage stability analysis by using both PSCAD/EMTDC™ power flow and time-domain simulations.

With the increasing scale of wind energy being connected to the power grid, the system flexibility shows an increasingly important role in maintaining the power balance. This trend indicates that it requires a clearer understanding of how the flexibility resource provided by hydroelectric units affects the flexibility performance. It is a challenge for the flexibility assessment as one of the major reasons for the accurate quantification involves the randomness, volatility, and intermittency of wind power injected into the grid. To address this challenge, a mathematical model of a wind-hydro hybrid power system (WHHPS) is developed and verified. The flexibility indices, namely, the probability and expectation of upward/downward flexibility not supplied, are defined. Finally, the flexibility properties of different reserve ratios and line distances are quantitatively analyzed. One of the main results shows that both the upward and downward flexibility are improved with the reserve ratio increasing regardless of changes in wind speed types. The proposed methods and results provide a visualized reference for the dispatching department to evaluate the required flexibility for improving the utilization rate of wind energy.

To confront climate change, decarbonization strategies must change the global economy. According to statements made as part of the European Green Deal, maritime transport should also become drastically less polluting. As a result, the price of transport must reflect the impact it has on the environment and on health. In such a framework, the purpose of this paper is to suggest a novel method for minimizing emissions from ships, based on so-called Pareto multi-objective optimization. For a given voyage by a ship, the problem is to minimize emissions on the one hand and minimize fuel consumption or passage time on the other. Minimizing emissions is considered as the preferred objective. Therefore, the objective of minimizing fuel consumption or passage time needs to be reformulated as a constraint. Solving such a problem consists of finding most favourable path and speed for the ship and satisfying the optimization criteria. Relatively new systems such as hybrid diesel–electric systems have the potential to offer significant emissions benefits. A hybrid power supply utilizes the maximum efficiency of the direct mechanical drive and the flexibility of a combination of combustion power from the prime mover and stored power from energy storage from an electrical supply, at part load and overload. A new report by the American Bureau of Shipping suggests that maritime transport is likely to meet the International Maritime Organization’s target by 2030, solely by using current technology and operational measures. However, this would not be enough to attain the target of reducing CO2 emissions by 2050 by at least 50% compared to 2008. New technologies and operational methods must be applied.

Due to the flexibility of seam tracking robot in special environment, independent power supply with different characteristics is adopted. Power allocation of hybrid power system composed of proton exchange membrane fuel cell and lithium battery is mainly researched. According to the requirements of economy and safety, hybrid rule fuzzy state machine control is designed to realize the optimal operation and fast response of power supply system. On the basis of energy allocation, further reduction of hydrogen consumption and power fluctuation is considered, which improves the power supply scheme. The sensitivity analysis method is used to screen the optimization variables, which reduces the complexity of the strategy; in addition, an adaptive mutation particle swarm optimization is studied to optimize the strategy, which combines the mutation idea, adaptively changes the weight and learning factor, and realizes the minimization of power fluctuation and equivalent hydrogen consumption. The results show that the stability of fuel cell and the rationality of lithium battery charging and discharging are greatly improved, and the fuel economy and service life of hybrid power system are improved.

PurposeIn the hybrid electricity market consisting of renewable and conventional energy, the generation output of renewable power is uncertain because of its intermittency, and the power market demand is also fluctuant. Meanwhile, there is fierce competition among power producers in the power supply market and retailers in the demand market after deregulation, which increases the difficulty of renewable energy power grid-connection. To promote grid-connection of renewable energy power in the hybrid electricity market, the authors construct different contract decision-making models in the “many-to-many” hybrid power supply chain to explore the pricing strategy of renewable energy power grid-connecting.Design/methodology/approachConsidering the dual-uncertainty of renewable energy power output and electricity market demand, the authors construct different decision-making models of wholesale price contract and revenue-sharing contract to compare and optimize grid-connecting pricing, respectively, to maximize the profits of different participants in the hybrid power supply chain. Besides, the authors set different parameters in the models to explore the influence of competition intensity, government subsidies, etc. on power pricing. Then, a numerical simulation is carried out, they verify the existence of the equilibrium solutions satisfying the supply chain coordination, compare the differences of pricing contracts and further analyze the variation characteristics of optimal contract parameters and their interaction relations.FindingsRevenue-sharing contract can increase the quantity of green power grid-connection and realize benefits Pareto improvement of all parties in hybrid power supply chain. The competition intensity both of power supply and demand market will have an impact on the sharing ratio, and the increase of competition intensity results in a reduction of power supply chain coordination pressure. The power contract price, spot price and selling price have all been reduced with the increase of the sharing ratio, and the price of renewable power is more sensitive to the ratio change. The sharing ratio shows a downward trend with the increase of government green power subsidies.Originality/valueOn the basis of expanding the definition of hybrid power market and the theory of newsvendor model, considering the dual-uncertainty of green power generation output and electricity market demand, this paper builds and compares different contract decision-making models to study the grid-connection pricing strategy of renewable energy power. And as an extension of supply chain structure types and management, the authors build a “many-to-many” power supply chain structure model and analyze the impact of competition intensity among power enterprises and the government subsidy on the power grid-connecting pricing.

Conventional wind-solar hybrid power systems (WS-HPSs) have certain structural drawbacks owing to their large size and the difficulty in adjusting the tilt angle of the solar panels. To address these limitations, this study proposes a compact spherical wind-solar hybrid power system (CSWS-HPS). Furthermore, to investigate the aerodynamic performance of the designed CSWS-HPS, a computational fluid dynamics model of the wind rotor was established using the Reynolds-averaged Navier–Stokes equations, renormalization group k-e turbulence model, and sliding mesh. Subsequently, the flow field distribution of velocity and pressure under different numbers of blades, blade installation angles, and tip-speed ratios (TSRs) were analyzed by performing a three-dimensional simulation of the CSWS-HPS. The monitored values of the moment coefficients were used to calculate the power coefficient value of the wind turbine to obtain the optimum structural parameters, which in turn provided the optimal values for the CSWS-HPS model. The simulation results revealed that the CSWS-HPS achieved considerable power generation efficiency in comparison with that of conventional hybrid systems. In addition, the CSWS-HPS is more compact in size and does not emit CO2.

This article presents a novel energy management strategy (EMS) for fuel cell hybrid electric vehicle (FCHEV) considering the exact identification of movement conditions, optimal power sharing, fuel consumption minimization, and reduction of battery power fluctuations. The vehicle's hybrid power source structure consists of a fuel cell, battery, ultracapacitor, and photovoltaic array, which is installed on the roof of FCHEV. Also, the maximum power point tracking (MPPT) is presented to fast tracking of various conditions, such as fast changes in the intensity of irradiation, temperature, and vehicle movement in various conditions. The proposed online multimode EMS is based on fuzzy logic control, equivalent consumption minimization, as well as operational mode control that can increase total energy efficiency and reduce power fluctuations of the battery. This study presents a classification of the vehicle's various movement conditions, separation of battery state of charge, and ultracapacitor voltage discharge ratio regions based on combined efficiency. Moreover, fuel cell power is classified based on efficiency to run the operational mode control strategy. Simulation results indicate a reduction in fuel consumption and fluctuations of the battery power compared to the other methods. Besides, increasing daily driving mileage and fast-tracking MPPT method results verified in the discussion of installed photovoltaic.

With the increasing development of AC/DC hybrid power systems, local synchronous generators in receiving-end grids are being replaced by high-voltage direct current (HVDC) power. The risk of short-term voltage instability exists because of the decline in dynamic reactive power resources from generators, the presence of high-proportioned induction motors and the demand for vast reactive power of HVDC under AC faults. In this situation, unit commitment (UC) should take short-term voltage stability into account. Hence, crucial generators can be retained to provide sufficient dynamic reactive power. This paper proposes a UC model incorporating short-term voltage stability constraints (SVSCUC). Furthermore, a decomposition-based solution approach is presented, which involves an alternate iterative solving of UC and differential-algebraic equations (DAEs). Time-domain simulation (TDS) is utilized to quantify the stability with an indicator. Linear stable cuts are formulated through trajectory sensitivity analysis and added into the UC. The UC is decomposed into a master problem based on mixed-integer linear programming (MILP) and subproblems. The SVSCUC is illustrated using benchmark systems and a real system in eastern China. The results show the effectiveness and efficiency of the proposed methods. Violations of short-term voltage stability for credible contingencies are eliminated under the commitment of SVSCUC.

The paper describes a manifold learning-based algorithm for big data classification and reduction, as well as parameter identification in real-time operation of a power system. Both black-box and gray-box settings for SCADA- and PMU-based measurements are examined. Data classification is based on diffusion maps, where an improved data-informed metric construction for partition trees is used. Data classification and reduction is demonstrated on the measurement tensor example of calculated transient dynamics between two SCADA refreshing scans. Interpolation/extension schemes for state extension of restriction (from data to reduced space) and lifting (from reduced to data space) operators are proposed. The method is illustrated on the single-phase Motor D example from a very detailed WECC load model, connected to the single bus of a real-world 441-bus power system.

Generated electricity from renewable sources such as solar panels and wind turbines is considered, until now, as clean and nonpolluting energy. However, these systems are responsible and directly t...

AC/DC hybrid power supply will become an important form of power distribution in the future. Its simulation is the indispensable mean for AC/DC power system research and related equipment/system development. This paper proposes a concept of AC/DC power system simulator, expounds the digital simulation platform and physical testing platform. Based on this, the paper focuses on the physical testing platform, and proposes corresponding simulation schemes including AC/DC flexible interconnection simulation, DC/DC flexible access simulation, and coordinated operation strategy. The corresponding tests reveal the effectiveness and feasibility of AC/DC power system simulator.

Coordinated operation of various energy sources has drawn the attention of many power producers worldwide. In this paper, a Concentrating Solar Power Plant (CSPP) along with a wind power station, a Compressed Air Energy Storage (CAES) unit, and a Demand Response Provider (DRP) constitute the considered Hybrid Power Producer (HPP). In this regard, this paper deals with the optimal participation of the mentioned HPP in the Day-Ahead (DA), and intraday electricity markets by benefiting from the joint configuration of all accessible resources. To attain risk-averse strategies in the suggested model, Conditional Value-at-Risk (CVaR) based on the $\epsilon$ -constraint technique is employed, while its efficiency is validated compared to the previously applied method to such problems. On the whole, the main contributions of this work lie in: 1) proposing a novel model for optimal behavior of a CSPP-based HPP in DA, and intraday markets using a three-stage decision-making architecture, and 2) developing a bi-objective optimization framework to improve the functioning of the risk-constrained algorithm. Simulation results reveal that taking advantage of the CSPP in the intraday market, and coordinated operation of all resources not only enhance the profitability of the system but also lessen the associated risk compared to the previous models.

A waste heat recovery system consisting of a hybrid power and cooling cycle is described in this paper. It couples a thermoelectric generator (TEG) and an organic Rankine cycle driving a vapor comp...

Because of the energy supply of the offshore oil platforms mainly relies on the supply of gas turbine, the development of renewable energy will become a rich energy supply for offshore oil platforms and a reliable way to improve the stability of the grid of the platforms. This paper developed the simulation model of offshore oil gas turbine platform power grid, simulated the hybrid power grid structure, the energy storage of frequency regulation, high wind power penetration rate, wind power and gas turbine power frequency stability and fault treatment. The method of increasing renewable energy penetration rate was proposed, and the hybrid energy coordinated control strategy of offshore oil platform was also carried out. Based on the weakly connected distributed offshore oil platform power grid project, this paper studied the influence of wind power and turbine power penetration rate on the power grid, in order to explore, determine and verify the limit of high wind power penetration rate under the condition of “large generation machine and small grid”. The simulation experiment of high wind power penetration rate under the condition of different load conditions and different wind speed limits were discussed, on the basis of research the influence degree of the stability of power grid frequency of low wind power swings, as well as to the wind power is given priority to with gas turbine mainly in both cases the advantages and disadvantages of the grid system, and attempt to put forward the corresponding switch control strategy.

This paper presents a novel direct parallel power control scheme with independent current paths for the proposed hybrid energy-harvesting system that consists of a low-power photovoltaic panel, a piezoelectric harvesting module, and an energy storage system. A battery is connected to store the generated power from the two renewable power sources to provide a continuous power supply for the users. The designed power converter controls both battery state and power supply without any power conditioning system. To achieve this, a low-power DC–DC converter with battery charging function and control algorithm is designed for the hybrid power source. Therefore, in the proposed system, no additional battery charge controller is required. To control the battery, however, an additional current sensor to detect the battery power is simply added to each DC–DC converter. In the proposed power control scheme and controller, each power input, output, and the combined power flow are connected with neither communication protocols nor additional controller. Moreover, the converters can adjust the supplied power for parallel power-sharing. For maximum output current protection in each converter and constant current control for the battery, a hybrid power connection and its related current path are also proposed in this paper. The effectiveness of the proposed hybrid power system and the direct parallel power control scheme was verified through experiments.

The dynamic performance of a hybrid power plant configuration comprising of a ground heat exchanger and an organic Rankine cycle (ORC) for power generation at the load end is studied. The ground he...

Energy recovery and hybrid power technology are new directions in construction machinery energy-saving research. Thus far, however, no uniform standard method exists to evaluate the efficiency of novel energy-saving concept systems in early stages of development. Efficiency assessment is valuable and credible only by relying on driving cycles that are consistent with actual data. As representative products of construction machinery, hydraulic excavators are multifunctional, object-uncertain, and heavily influenced by operator habits. It is therefore challenging to develop standard excavator driving cycles. Aiming at the energy efficiency evaluation of new energy-saving products characterized by energy recovery and power system optimization, taking medium-sized hydraulic excavator as an example, this paper proposes an evaluation method of energy-saving efficiency and a classification construction method of comprehensive driving cycle of hydraulic excavator based on actual operating data with load demand power and boom recoverable power as combined variables. First, based on the analysis of general driving cycle variables for excavators with different energy-saving schemes, a load demand power model and boom recoverable power model based on machine sensing data are established. Second, 10 excavators were selected at different locations in southern China, and 30 days of real-world working data were recorded. Third, according to the periodic characteristics of working data, a method for dividing microcycle operation structure is proposed. The microcycle sample space based on the data conversion of working data is constructed and classified via the clustering algorithm. Finally, a comprehensive excavator driving cycle based on the classification results is constructed through the Markov method. Results show that the energy-saving efficiency of the three classification driving cycles was 17.45%, 13.60%, and 11.88%, respectively; the comprehensive energy-saving efficiency was 15.76%. The deviations in maximum load demand power and maximum boom recoverable power between the constructed comprehensive cycle and the sample space were 7.81% and 8.61%; the average deviation of characteristic parameters was 4.26%. The comprehensive driving cycles can fairly reflect the general characteristics of real-world working conditions. The proposed construction method of comprehensive driving cycles based on sample space is therefore reliable and holds great promise for evaluating the energy-saving efficiency of new energy-saving concept systems.

This article deals with the Automatic Generation Control (AGC) mechanism for an interconnected, deregulated hybrid power system. The physical generation constraints such as boiler dynamics, governor dead band (GDB) and generation rate constraints (GRC) are included for a more realistic approach. The integration of distributed generation (DG) systems is also considered to match with present scenario. The intermittency nature of the DGs ruins the system's inertia and dynamic behaviour. A novel cascaded fractional order controller configuration 2-DOF (FOPIλDN)-PDN is proposed for the AGC mechanism and a new quasi opposition based volleyball premier league (QVPL) algorithm is employed to optimize the controller gains. On the other hand, the inertia emulation strategy (IES) based modified HVDC tie-line is used parallel to the AC tie-line to retrace the power system's inertia. The impact of the proposed controller and IES based modified HVDC tie-line has been analysed by subjecting to several case studies. The effectiveness of the QVPL based proposed controller has also been tested by comparing it with the previously published works on the same platform.

Integrating different energy resources, like solar PV, wind, and hydro is used to ensure reliable power to the rural community loads. Hybrid power system offers sufficient power supply for the rural villages by providing alternative supply for intermittent nature of renewable energy resource. Hence, intermittency of renewable energy resources is a challenge to electrify the rural community in a sustainable manner with the above sources. Thus, efficient resources management is a reasonable choice for intermittent renewable energy resources. The majority of rural villages in Ethiopia are suffering from lack of electricity. This causes deforestation, travel for long distance to fetch water, and no good social services, like clinic and schools, sufficiently. Therefore, the objective of this study was to maximize reliability of power supply by renewable energy sources. Data on wind speed and solar radiation are obtained from the NASA surface meteorological agency. While hydro data are obtained from physical measurements. Different configuration options are considered by Homer software to find the optimal configuration of hybrid system. The optimal configuration system is selected and hybrid components are sized. The optimal hybrid system consists of solar PV, wind, and hydro to supply a community load with a share of 13%, 52%, and 35% respectively. The fuzzy logic controller is designed to manage the intermittent nature of energies. Hence, the demand and energy sources are unpredictable; intelligent control system is important to manage the system accordingly. The control system is designed in MATALAB software. The result obtained from resource combination shows demand and supply are balanced. From the Twelve probabilistic combinations of demand and energy sources, one of the combinations shows that when 7.5 kW is demanded, the power generated/output from hybrid system is 10 kW which is greater than demand. To satisfy 7.5 kW demand control system takes 4.25 kW, 2.75 kW, and 1.08 kW share from wind, hydro, and solar sources respectively. The fuzzy logic control system is designed, to monitor the resource availability and load demand. This controller was managing the demand and the available resources according to the rule.

Energy efficiency is one of the main requirements for modern traction rolling stock of mainline and industrial railway transport, as well as urban transport. A qualitative improvement in the energy efficiency indicators of traction rolling stock can be provided by building onboard power complexes using high-capacity electric energy storage units, which make it possible to organize efficient energy exchange between the main source (contact network, diesel-generator set), storage devices and energy consumers in various operating modes. Rolling stock with an energy system of this type has been designated as “hybrid traction rolling stock.” This article proposes a classification of hybrid traction rolling stock that which categorizes the specifics of the architecture of its power plants. To assess the properties of hybrid traction rolling stock, a system of quantitative indicators has been proposed, which make it possible to form a comprehensive comparative assessment of the technical level, energy efficiency, and competitiveness of various types of hybrid rolling stock. The most promising topology of a power hybrid power plant of traction rolling stock, which provides the possibility of independent control of energy flows and optimization of the operating modes of on-board energy storage systems, is shown.

Aiming at the adverse effect of the peak power of the electric motor of the battery-powered rail vehicles on the battery life and the driving range when starting or accelerating, a new type of electro-hydrostatic hydraulic hybrid powertrain is designed. This article proposes a novel power form that assists the vehicle to start or accelerate through two power coupling methods: torque coupling circuit and flow rate coupling circuit which have good power performance and energy-saving performance. A mathematical model for power coupling of hybrid power system is constructed, and the effects of key parameters of the system and different power coupling ratios on electric power consumption and power coupling characteristics are studied. Based on the simulation and test platform, the power coupling characteristics of the electro-hydrostatic hydraulic hybrid powertrain are simulated and experimentally researched. The results show that compared with the traditional electro-hydrostatic series system, the novel electro-hydrostatic hydraulic hybrid powertrain can effectively avoid the impact of electric motor power and reduce the power consumption. Based on the characteristics of power coupling, the acceleration strategy of minimum peak power is studied to control the key components of the power coupling process. Simulation and experimental results show that under the control of the new acceleration strategy, the electro-hydrostatic hydraulic hybrid powertrain has good electro-hydraulic power coupling characteristics. The electric power of the power system is greatly reduced during acceleration, which has better energy-saving characteristics and value for engineering applications.

Rural healthcare centers offer essential preventive and curative care to rural communities. The most of these centers are located in landlocked and difficult to access areas all year long or at least during bad weather conditions periods (snowfall for example). Some of these centers include sensitive services that operate 24 h a day such as maternity facilities, which take care of women and their newborns and which require a healthcare supervised environment before and after childbirth. This paper highlights the importance of using hybrid power sources based on renewable energy for reliable, secure and economically profitable technologies. Solar photovoltaic (PV) sources become more technologically mature and more cost competitive; therefore the cost of deploying and operating solar PV farms is declining, reducing the cost of energy produced and finally the applied electricity tariffs for kWh. The combination of PV technology with other technology e.g. diesel generator could be an interesting alternative to ensure a permanently power supply 24 h a day and whatever the weather conditions can be. In this paper, the technical applicability of this concept and its potential advantages with comparison to other technologies according to efficiency, cost and environmental impact are investigated.

A considerable no. of intermittent renewable sources such as PV generation and wind energy when integrated to the conventional grid technology causes serious issues in the power systems like frequency instability. So a more balancing controller is desired for a stable and reliable operation of the power system. Bidirectional power control of the EV aggregator is making itself a wise choice for distributed energy storage to scale down the frequency and power fluctuation. In this work, an intelligent load frequency controller using a fractional-order adaptive fuzzy PID controller with filter (FOAFPIDF) for hybrid power system with electric vehicle (EV) based on modified salp swarm algorithm (MSSA) technique is proposed. The effectiveness of MSSA technique is compared with original salp swarm algorithm as well as moth flame optimization , grey wolf optimization , particle swarm optimization and sine cosine algorithm techniques for benchmark test functions using statistical analysis. The effectiveness of the suggested load frequency control strategy by the use of electric vehicle as well as with other energy storing elements such as the superconducting magnetic energy storage component, flywheel energy storage system and ultra-capacitor along with their inherent rate constraint nonlinearity is validated by numerical simulations conducted on the studied test system. It is demonstrated that the proposed controller provides a better control action to suppress the frequency fluctuations as compared to PID controller. The robustness of the controller is also investigated against variation of system parameters and random load changes.

This dissertation introduces an intelligent hybrid technique for the design of modelling and controller of the three-phase hybrid network connection system based on CMI. The hybrid technique is the Recurrent Neural Network (RNN) assisted by Wolf Pack Search (WPS) and therefore it is known as WPSNN technique. Here, the three stage CMI control scheme is considered as two stages and these are analyzed with the help of the proposed intelligent controller. In first stage, the WPS is developed to demonstrating the PV total and wind voltages and the WPS algorithm of the second stage assisted to RNN is used to extracting the reference currents of network. In first stage, input of WPS algorithm is PV and wind reference voltages and the gain parameters is generated as the output for optimal tuning of PI controller. In the second phase, the RNN is trained with on line process; the output of RNN is given to the WPS algorithm. It provides the corresponding tuning parameters to achieve the network current. To regulate the dc link voltage and the extraction of network current is developed with established technique. CMI based on the established technique is synchronizes the firing work relationship and reduces the modulation load. By then, the established technique is evaluated in MATLAB/Simulink working stage and the execution is assessed to existing techniques.

Due to the high penetration of renewable energy resources in microgrids (MGs), the grid inertia becomes low which leads to the grid to be vulnerable to large disturbances. The energy storage devices can play an important role to enhance the inertia of MGs. However, due to the high investment cost of storages or their dp/dt limitation, the installed energy storages cannot cover the challenge of high df/dt. A prominent solution to solve the problem is to use the inertia response of the wind generators. However, relatively high second frequency nadir is the main drawback of using the inertia response of the wind generators which may impose an extensive disturbance to MGs. Accordingly, a coordinated operation strategy for MGs between wind generator and hybrid energy storage (HES) system is proposed in this paper. In addition, to improve the inertia response of the MG; providing high-quality communication infrastructures with low delay and increasing the Ultracapacitor capacity have been paid attention. In this paper, the costs of the installed Ultracapacitor and quality of communication services are defined as the operation cost. Guaranteeing enough frequency damping for the MG with low operation cost are two conflict objectives. Therefore, a multi-objective optimization method is used to set the controllers’ values and reduce the operation cost. The results confirmed that the effectiveness of the proposed strategy to control hybrid power storage in coordination with the wind generator and the frequency recovery process is improved. Also, employing the optimum values guaranteed the frequency damping effectively with low operation cost. The Integral Absolute Error (IAE) value and operation cost are reduced by 13.6% and 32%, respectively. Also, the simulation results show that the maximum MG frequency deviation and maximum df/dt is well compatible with different standards in the presence of load perturbations and different wind speeds.

Emergency rescue vehicles are special equipment for fire, flood, earthquake and other disasters. They need to have high efficiency and high mobility under various terrain and road conditions. The fuel economy of emergency rescue vehicles is very poor in climbing and complex terrain due to the heavy weight of vehicle chassis and upper loading. The dual-motor torque increasing hybrid power system designed in this paper greatly improves the dynamic performance and mobility of emergency rescue vehicles, and the use of dual-motor drive in steep slopes and complex terrain can avoid the engine working in low efficiency area. In order to further improve the fuel economy of vehicles under various working conditions, a fuzzy logic control strategy based on improved particle swarm optimization (PSO) is proposed in this paper. The torques of engine and dual-motor are reasonably distributed under different working conditions. A novel fuzzy parameter optimization mode is designed, which reduces the workload of optimization calculation and ensures the optimization accuracy. The off-line simulation and hardware-in-the-loop experiments are carried out for the dual-motor torque increasing hybrid power system model and the proposed improved energy control strategy. The results show that the fuzzy logic control strategy optimized by simulated annealing particle swarm optimization algorithm (SimuAPSO-FLC) has the best effect and meets the requirements of high efficiency, high mobility and stability of the emergency rescue vehicle.

In this article, an Improved Frequency Regulation (IFR) for an interconnected hybrid power system under a deregulated scenario is proposed. The analyzed test system comprises of a thermal power system, biogas plant, and Distributed Generation (DG). The impact of the integration of Renewable Energy Sources (RES) has been examined by considering DG system with solar and wind power generation. In order to make the system more realistic, appropriate non-linearities are incorporated into the thermal and biogas system. Electric Vehicle (EV) is also employed to take care of some portion of uncontracted demand. A maiden hybridized fuzzy-Proportional Integral (FPI)-Linear Active Disturbance Rejection Control (LADRC) is proposed and successfully implemented for IFR. Also, a new Quasi-Opposition-based Artificial Electric Field Algorithm (QO-AEFA) is proposed to acquire the optimal controller gain parameters of the tested system. A pertinent performance analysis is also examined for other employed algorithm in this study, to figure out the eminence of the proposed control algorithm. A comprehensive examination and comparison of the proposed controller with other controllers shows its effectiveness for the proposed test system. In order to ensure the reliability of the proposed controller, sensitivity analysis is also carried out for system parameters that reveal its robust nature. Further, case studies for random load variations and comparison with the works in previous literature also manifest the puissance of the current research work. Moreover, the improved results under random weather conditions illustrate the effectiveness of the proposed IFR under deregulation.

This work is a maiden attempt towards the voltage stability enhancement of a hybrid power system (HPS) comprising of Parabolic Trough solar power (PSP), Dish-Stirling Solar Power (DSP) and diesel generator (DG). DSP coupled with induction generator requires reactive power for its field winding to be magnetized whereas PSP employing permanent magnet synchronous generator (PMSG) doesn’t require reactive power for excitation. So, it’s worthwhile to infer that PSP reduces the reactive power requirement for its own functionality and may meet the same load demand at low voltage compensation. Lower voltage compensation requirement results in higher voltage stability. Besides, dynamic responses of the system are also improved as the HPS has been incorporated with Voltage Compensating Devices (VCDs) like Static Var Compensator (SVC), Static Synchronous Compensator (STATCOM) and Dynamic Voltage Restorer (DVR). Inclusion of FACTS devices reduces the probability of the transient voltage instability. HPS with FACTS devices under PSP has been subjected to the critical change in load with positive and negative infinite slope at regular interval of time to see the system practicality and its feasibility. The graphical and numerical analysis of the proposed system explicitly shows that the proposed HPS with PSP retains the system voltage stability with great margin under DVR. The efficient hybrid power system as a whole has been achieved to maintain the system reliability in terms of voltage because of the presence of PSP and DVR.

Taking the Steady-state Security Region (SSR) of AC/DC hybrid power system as a link, the mathematical model of coordinated control optimization problem is established by using the complementarity between preventive control and corrective control. Firstly, taking into account the probability and severity of anticipated accidents, a two-layer optimization model of coordinated control with dynamic constraints is established with the lowest total cost of coordinated control as the objective function. Secondly, invalid anticipated accidents are eliminated based on the theory of dominant event, which reduces the scale of the model and the complexity of optimization space. Finally, based on the constraint relaxation outer-layer optimization method, the anticipated accident with the minimum Steady-state Security Distance(SSD) is eliminated from the preventive control subset and incorporated into the corrective control subset, providing fixed anticipated accident subsets for the inner-layer optimization. In the inner-layer optimization, the SSDs are used to replace the power flow equations as the constraint condition, then the nonlinear constraints are transformed into linear constraints, which can reduce the difficulty of solving the mathematical model. The transformed IEEE 39 node AC/DC hybrid system is analyzed and calculated, and the calculation results verify that the proposed method can effectively improve the efficiency of solving optimal control scheme, and provide the possibility for online application.

As the world is moving towards green energy generation to reduce the pollution by renewable sources such as wind, solar, geothermal and more. These sources are intermittent in nature, to coordinate and control with traditional power generating units a control technique is necessary. This paper mainly focuses on the design of fuzzy based classical controller using a PSO algorithm for optimal controller gains to control the frequency variations in island hybrid power system. The considered mathematical model comprises of a diesel generating model, wind turbine generator and a battery storage system. Fuzzy is an intelligent controller which is designed with trial and error rules or on the basis of past experience provided by experts or by optimization methods for optimized gains using computational algorithms. To give best solution for these kinds of problems with FLCs traditional controllers are integrated with fuzzy logic. The PSO algorithm is applied to tune the classical controller gains to decrease the frequency deviation of the island power system, during the different load and wind disturbances. The Fuzzy PID classical controller shows the best performance compared with the only fuzzy and Fuzzy-PI controller configurations by illustrating the under shoot, overshoot and settling time and the proposed method is robust for various loading conditions and different wind changes.

In order to simplify the stability analysis of an AC/MTDC (multi-terminal direct current) power system, this paper presents a Multi-Layer Component Connection Method (MLCCM)-based small signal model for AC/MTDC hybrid power systems. Based on ML-CCM, the system is partitioned as small individual system or components, including generator units, voltage source converter (VSC) units, time delay units, AC network and DC network. The modelling procedure can be 3 steps. First, the individual components are independently modelled. Second, several small individual components are assembled together to build the AC system model based on component interconnection relationship. Third, all AC power systems and DC network model are assembled together to build the whole hybrid power based on the interconnection relationship. There are three features for the MLCCM: (1) these component models can be built individually; (2) their interconnection relationship is a linear algebra matrix; (3) subsystem model can be verified or debugged individually. Due to the three features, the whole hybrid power can be built easily and it is convenient for finding modelling fault and debugging. An AC/DC hybrid system model in MATLAB/Simulink is also built to validate the effectiveness of the MLCCM-based small signal model.

Large power impact in a short time will cause power oscillation or even cascading failures after the blocking of HVDC. EDCPS can greatly improve the post-disturbance transient stability of power system. Firstly, the relationship between the voltage level of the AC buses at both ends of the HVDC system and the operation modes of the HVDC system is studied, giving the explanation of limited EDCPS. Next, a methodology for calculating the HVDC line power boost ability is proposed with the consideration of the short-time overload capacity of converters, voltage stabilization level of the commutation bus, and voltage support capability of the AC grid. Finally, the power modulation strategy that coordinates multiple HVDC support capabilities is developed considering HVDC real-time boosting capability and steady limitation of power transfer interfaces. The proposed methodology has been tested in the real system. The simulation results indicate that the proposed methodology is able to quickly absorb the unbalanced energy accumulated during the fault process and improve the operational stability of AC/DC hybrid power grid.

In railway traction power supply, co-phase system with hybrid power quality conditioner (HPQC) is capable of tackling the power quality issues caused by single-phase traction loads. To further reduce the overall carbon emissions in railway systems, this paper considers to integrate the renewable energy with railway power supply, which however leads to a more complicated system to model, design and control. This paper first investigates its modelling aspect. To reduce the operating capacity of HPQC while addressing the power unbalance, optimal design of the compensation scheme for co-phase system is formulated as a multi-objective optimization problem which is then solved by the nondominated sorting genetic algorithm-II (NSGA-II). To eliminate the impact of errors arising from imperfect predictions of the loads and renewable power, a hybrid optimal compensation control is proposed, yielding full and optimal compensations. Comprehensive simulation studies, considering three operation modes covering variable traction loads, renewable and regenerative braking power, are conducted. The simulation results confirm the validity of the proposed optimal compensation scheme, achieving an average of more than 20% reduction in HPQC capacity compared to the full compensation scheme. Meanwhile, the power quality requirement is satisfied, even in the presence of real-time prediction errors.

Wind and solar energy are currently the most prominent and reliable sources of renewable energy. Wind and solar power deployment largely depend on government policies and have a specific policy and regulatory provisions. The declaration of hybrid wind–solar policy has changed the dynamics of individual wind and solar power projects by introducing the scope for developing hybrid power projects to harness wind and solar energy simultaneously. The techno-economic structure and the existing scenarios of the fractional contribution of wind and solar sectors are going to play an important role in the development of hybrid power projects. This paper aims to present a comprehensive review of the impact of the existing individual wind and solar energy policies along with the recently declared hybrid policy in India and how this hybrid policy will affect the techno-economic structure of the existing and new power projects. Further, various kind of barriers faced by project developers while establishing renewable energy-based power projects and recommendations which can be practically implemented have been elaborated to facilitate and achieve the faster deployment of wind and solar power generation.

Frequency control over networks is done using the frequency droop control technique which has the simplicity advantage although it allows that, in certain situations, frequency control is not very efficient. Artificial intelligence techniques have been increasingly used, so it is justified to explore their viability in electrical networks. The present work analyzes the use of Artificial Intelligence in networks to improve the frequency droop control. In order to realize this, a deep reinforcement learning (DRL)-based agent is proposed to tune the controller parameters for voltage source converter (VSC) in this paper. The DRL-based agent is trained by numerous hybrid grid operation conditions to lean the optimal control policy, which make it achieve a good adaptability to variety of operation conditions. For the purpose of demonstrating this method, a time-domain simulation model of hybrid power system is built with MATLAB/Simulink to act as test system. The simulation results verify the effectiveness of the proposed method.

This paper develops a recent population-based of Equilibrium Optimizer Algorithm (EOA) for solving the optimal power flow (OPF) problem in hybrid AC/DC power grids. The proposed OPF problem handles several objective functions that reflect multi dimensions economic-technical and environmental operation requirements of modern power systems. The considered objectives incorporate minimizing the total generation costs, generation environmental emissions, total power losses, and the deviations of the bus voltages. These objectives are handled separately and simultaneously to provide the preference capability to the operator objectives. EOA has adaptive dynamic control parameters. It mimics the dynamic and equilibrium states related to the mass balance models where, each concentration of search agent is randomly updated in the sake of reaching the final optimal fitness. Finally, 12 case studies are carried out via the developed EOA, particle swarm optimizer and differential evolution for the modified IEEE 14-, 30-bus test systems and West Delta power system (WDPS) in Egypt. The second-order cone OPF model is considered. Also, adding wind units and their impacts on the OPF solution is assessed for the hybrid AC/DC grid. The simulation results demonstrate the great effectiveness of the developed EOA in solving the OPF in hybrid power systems.

This paper examines the use of various types of cooling liquids in a two-cylinder single-stage piston hybrid power machine with fluid flow due to vacuum at suction. Liquids with various basic thermal properties were used as working fluids: distilled water, antifreeze, and transmission oil. Specific heat capacities and dynamic viscosities of these liquids differed from 2 to 10 times. The experimental studies showed that the greatest cooling effect on the cylinder-piston group was observed when using distilled water, and the least — when using transmission oil. The average surface temperature of the working chamber when cooled with water was minimal in the range of 330–340 K. The average surface temperature of the working chamber when cooled with transmission oil was maximum and ranged from 345 to 355 K, i. e. it was about 15 K higher than when cooled with water. The average surface temperature of the working chamber when cooled with antifreeze occupied an intermediate position between the average temperatures of the working chamber when cooled with water and that with transmission oil and was in the range of 335–345 K, i. e. about 5 K higher than when cooled with water.

Regulating the frequency fluctuations (known as load frequency control) in the power system is an important aspect that directly signifies the balance between the generation and demand. The present...

In present time the power demand increases more rapidly in the power generation and transmission and distribution system sectors. For maintaining the power system stability and steady state operation of power systems causes from disturbance, faults and suddenly changing of the load, voltage instability, voltage swell, voltage sag, harmonics, and change in frequency, stability is the most important factor for the power systems. Due to instability, different problems occur in power systems such as fluctuation in voltage and frequency, which may cause damage or failure of power systems. This article presents taxonomical survey on optimization techniques for enhancement system performance by FACTS controllers such as Thyristor Controlled Series Capacitor (TCSC), Thyristor Controlled Phase Angle Regulator (TC-PAR), Static VAR Compensator (SVC), Dynamic Voltage Restorer (DVR), Sub-Synchronous Series Compensator (SSSC), Static Synchronous Compensator (STATCOM), distributed-STATCOM, Unified Power Flow Controller (UPFC), Generalized Unified Power Flow Controller (GUPFC), Unified Power Quality Conditioners (UPQC), Unified Dynamic Quality Conditioners (UDQC), Interlink Power Flow Controller (IPFC), GeneralizedInterlink Power Flow Controller (GIPFC) and Hybrid Power Flow Controller (HPFC) etc. in power systems with static and realistic load models. The system performances such as real and reactive power losses, power quality, voltage profile, power system oscillations, loadability of system, reliability and security of system, power system stability, bandwidth of operations, flexible operations, available power transfer capacity, system power factor, environmental etc. are enhanced by optimally placed different types of FACTS controllers in power systems with static and realistic load models. In this survey article will be very much helpful to the researchers and practitioners for finding out the relevant references in the field of enhancement system performances by different types of FACTS controllers in power systems with static and realistic load models.

A hybrid renewable power system is studied in this paper. This system is composed of PV panels, wind turbines, inverter, rectifier, electrolyzer, and fuel cell such that it prioritizes storing excess energy by converting it to hydrogen and using it later in the fuel cell. Additional extra generation power is sold to the main electricity network. The system generates power from clean sources and has zero emission. To achieve minimum power generation cost, the optimal size of each component is obtained using the proposed modified seagull optimization technique. The cooperative generation of wind and PV and energy storage mitigate the uncertain behavior of renewable energy sources. The proposed hybrid power system and optimization are implemented in a real-world case study in Qingdao, China. The consumption and meteorological data of the year 2018 are used as input to the system. To prove the superiority of the proposed optimization method in terms of accuracy and computation time, it is compared to two other optimization methods, namely original seagull optimization algorithm (SOA) and modified farmland fertility algorithm (MFFA), which are used in similar applications. The proposed method has achieved 2.02% and 2.78% better results and converged 69.36% and 47.07% faster compared to conventional SOA and MFFA methods, respectively. In addition, the hybrid system is able to operate with high reliability and loss of power supply probability well below the threshold of 8 . 96 e 20 .

This article presents a method for calculating the dynamics of fluid motion in a two-stage hybrid energy machine with a gas cap. The developed method is based on the Bernoulli energy conservation equation, taking the linear hydraulic resistances, local hydraulic resistances, and inertial forces into account. The expressions for the current coordinate values of the liquid levels and pressures in the gas cap apply to the second stage compressor section and the first stage pump section. The developed method of calculation can be used for the analysis of working processes in compressor machines based on the principle of the liquid piston.

In this study, a sine adapted improved whale optimisation algorithm (SiWOA) is proposed where sine function is incorporated in the Whale Optimization Algorithm (WOA) for the choice of algorithm par...