Search

Globally abundant wave energy for power generation attracts ever increasing attention. Because of non-linear dynamics and potential uncertainties in ocean energy conversion systems, generation productivity needs to be increased by applying robust control algorithms. This paper focuses on control strategies for a small ocean energy conversion system based on a direct driven permanent magnet synchronous generator (PMSG). It evaluates the performance of two kinds of control strategies, i.e., traditional field-oriented control (FOC) and robust adaptive control. The proposed adaptive control successfully achieves maximum velocity and stable power production, with reduced speed tracking error and system response time. The adaptive control also guarantees global system stability and its superiority over FOC by using a non-linear back-stepping control technique offering a better optimization solution. The robustness of the ocean energy conversion system is further enhanced by investigating the Lyapunov method and the use of a DC-DC boost converter. To overcome system complexity, turbine-generator based power take-off (PTO) is considered. A Matlab/Simulink study verifies the advantages of a non-linear control strategy for an Oscillating Water Column (OWC) based power generation system.

In this paper, the impact of communication time delays (CTDs) on combined load frequency control (LFC) and automatic voltage regulation (AVR) of a multi-area system with hybrid generation units is addressed. Investigation reveals that CTDs have significant effect on system performance. A classical PID controller is employed as a secondary regulator and its parametric gains are optimized with a differential evolution - artificial electric field algorithm (DE-AEFA). The superior performance of the presented algorithm is established by comparing with various optimization algorithms reported in the literature. The investigation is further extended to integration of redox flow batteries (RFBs) and interline power flow controller (IPFC) with tie-lines. Analysis reveals that IPFC and RFBs coordinated control enhances system dynamic performance. Finally, the robustness of the proposed control methodology is validated by sensitivity analysis during wide variations of system parameters and load.

The modeling and multi-energy flow calculation of an integrated energy system (IES) are the bases of its operation and planning. This paper establishes the models of various energy sub-systems and the coupling equipment for an electricity-gas-thermal IES, and an integrated multi-energy flow calculation model of the IES is constructed. A simplified calculation method for the compressor model in a natural gas network, one which is not included in a loop and works in constant compression ratio mode, is also proposed based on the concept of model reduction. In addition, a numerical conversion method for dealing with the conflict between nominal value and per unit value in the multi-energy flow calculation of IES is described. A case study is given to verify the correctness and speed of the proposed method, and the electricity-gas-thermal coupling interaction characteristics among sub-systems are studied.

In this paper, a Sliding mode controller design method for frequency regulation in an interconnected power system is presented. A sliding surface having four parameters has been selected for the load frequency control (LFC) system model. In order to achieve an optimal result, the parameter of the controller is obtained by grey wolf optimization (GWO) and particle swarm optimization (PSO) techniques. The objective function for optimization has been considered as the integral of square of error of deviation in frequency and tie-line power exchange. The method has been validated through simulation of a single area as well as a multi-area power system. The performance of the Sliding mode controller has also been analyzed for parametric variation and random loading patterns. The performance of the proposed method is better than recently reported methods. The performance of the proposed Sliding mode controller via GWO has 88.91% improvement in peak value of frequency deviation over the method of Anwar and Pan in case study 1 and similar improvement has been observed over different case studies taken from the literature.

Wind power, solar power and water power are technologies that can be used as the main sources of renewable energy so that the target of decarbonisation in the energy sector can be achieved. However, when compared with conventional power plants, they have a significant difference. The share of renewable energy has made a difference and posed various challenges, especially in the power generation system. The reliability of the power system can achieve the decarbonization target but this objective often collides with several challenges and failures, such that they make achievement of the target very vulnerable, Even so, the challenges and technological solutions are still very rarely discussed in the literature. This study carried out specific investigations on various technological solutions and challenges, especially in the power system domain. The results of the review of the solution matrix and the interrelated technological challenges are the most important parts to be developed in the future. Developing a matrix with various renewable technology solutions can help solve RE challenges. The potential of the developed technological solutions is expected to be able to help and prioritize them especially cost-effective energy. In addition, technology solutions that are identified in groups can help reduce certain challenges. The categories developed in this study are used to assist in determining the specific needs and increasing transparency of the renewable energy integration process in the future.

This paper proposes a novel distributed secondary controller for droop-controlled microgrids to regulate the frequency and voltage, and autonomously share the power mismatch. The proposed scheme is entitled generalized proportional-intergal finite-time controller (GPI-FTC). The proposed GPI-FTC is synthesized based on the control Lyapunov function method and modifying the conventional PI controller by adding a consensus term to the integrand dynamic. The proposed distributed GPI-FTC provides plug-n-play capability, scalability, and fast finite-time convergence of the system states. Moreover, a reactive power sharing (Q-sharing) method is designed to improve the sharing pattern of reactive power under exact voltage regulation. Also, a distributed voltage observer is developed for average voltage regulation. Performance of the proposed GPI-FTC is validated through numerical simulations of the detailed model of the microgrid, including small signal analysis, load change, DG outage, Q-sharing, and performance comparison.

High voltage direct current (HVDC) transmission is an economical option for transmitting a large amount of power over long distances. Initially, HVDC was developed using thyristor-based current source converters (CSC). With the development of semiconductor devices, a voltage source converter (VSC)-based HVDC system was introduced, and has been widely applied to integrate large-scale renewables and network interconnection. However, the VSC-based HVDC system is vulnerable to DC faults and its protection becomes ever more important with the fast growth in number of installations. In this paper, detailed characteristics of DC faults in the VSC-HVDC system are presented. The DC fault current has a large peak and steady values within a few milliseconds and thus high-speed fault detection and isolation methods are required in an HVDC grid. Therefore, development of the protection scheme for a multi-terminal VSC-based HVDC system is challenging. Various methods have been developed and this paper presents a comprehensive review of the different techniques for DC fault detection, location and isolation in both CSC and VSC-based HVDC transmission systems in two-terminal and multi-terminal network configurations.

Optimal reactive power dispatch (ORPD) is a complex and non-linear problem, and is one of the sub-problems of optimal power flow (OPF) in a power system. ORPD is formulated as a single-objective problem to minimize the active power loss in a transmission system. In this work, power from distributed generation (DG) is integrated into a conventional power system and the ORPD problem is solved to minimize transmission line power loss. It proves that the application of DG not only contributes to power loss minimization and improvement of system stability but also reduces energy consumption from the conventional sources. A recently proposed meta-heuristic algorithm known as the JAYA algorithm is applied to the standard IEEE 14, 30, 57 and 118 bus systems to solve the newly developed ORPD problem with the incorporation of DG. The simulation results prove the superiority of the JAYA algorithm over others. The respective optimal values of DG power that should be injected into the four IEEE test systems to obtain the minimum transmission line power losses are also provided.

Large interconnected power systems are usually subjected to natural oscillation (NO) and forced oscillation (FO). NO occurs due to system transient response and is characterized by several oscillation modes, while FO occurs due to external perturbations driving generation sources. Compared to NO, FO is considered a more severe threat to the safe and reliable operation of power systems. Therefore, it is important to locate the source of FO so corrective actions can be taken to ensure stable power system operation. In this paper, a novel approach based on two-step signal processing is proposed to characterize FO in terms of its frequency components, duration, nature, and the location of the source. Data recorded by the Phasor Measurement Units (PMUs) in a Wide Area Monitoring System (WAMS) is utilized for analysis. As PMU data usually contains white noise and appears as multi-frequency oscillatory signal, the first step is to de-noise the raw PMU data by decomposing it into a series of intrinsic mode functions (IMF) using Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) technique. The most appropriate IMF containing the vital information is selected using the correlation technique. The second step involves various signal processing and statistical analysis tools such as segmented Power Spectrum Density (PSD), excess kurtosis, cross PSD etc. to achieve the desired objectives. The analysis performed on the simulated two-area four-machine system, reduced WECC-179 bus 29 machine system, and the real-time power system PMU data set from ISO New England, demonstrates the accuracy of the proposed method. The proposed approach is independent of complex network topologies and their characteristics, and is also robust against measurement noise usually contained in PMU data.

Large integration of doubly-fed induction generator (DFIG) based wind turbines (WTs) into power networks can have significant consequences for power system operation and the quality of the energy supplied due to their excessive sensitivity towards grid disturbances. Under voltage dips, the resulting overcurrent and overvoltage in the rotor circuit and the DC link of a DFIG, could lead to the activation of the protection system and WT disconnection. This potentially results in sudden loss of several tens/hundreds of MWs of energy, and consequently intensifying the severity of the fault. This paper aims to combine the use of a crowbar protection circuit and a robust backstepping control strategy that takes into consideration of the dynamics of the magnetic flux, to improve DFIG’s Low-Voltage Ride Through capability and fulfill the latest grid code requirements. While the power electronic interfaces are protected, the WTs also provide large reactive power during the fault to assist system voltage recovery. Simulation results using Matlab/Simulink demonstrate the effectiveness of the proposed strategy in terms of dynamic response and robustness against parametric variations.

For AC transmission lines connected to an LCC-HVDC inverter station, commutation failure can lead to the wrong operation of traditional protection. To solve the problem, this paper proposes a fast protection scheme using transient information from one end of the AC line. The boundary frequency characteristics of the AC line connected to LCC-HVDC inverter are analyzed first. This reveals the existence of significant attenuation on both high frequency signals and some specific frequency signals. Based on the boundary characteristics, a novel boundary protection principle utilizing a backward traveling wave is then proposed. A PSCAD/EMTDC simulation model of a ± 800 kV LCC-HVDC and 500 kV AC transmission system is established, and different fault cases are simulated. The simulation results prove that the novel protection principle is immune to commutation failure, fault resistance and fault type.

Combined estimation of state and feed-back gain for optimal load frequency control is proposed. Load frequency control (LFC) addresses the problem of controlling system frequency in response to disturbance, and is one of main research areas in power system operation. A well acknowledged solution to this problem is feedback stabilization, where the Linear Quadratic Regulator (LQR) based controller computes the feedback gain K from the known system parameters and implements the control, assuming the availability of all the state variables. However, this approach restricts control to cases where the state variables are readily available and the system parameters are steady. Alternatively, by estimating the states continuously from available measurements of some of the states, it can accommodate dynamic changes in the system parameters. The paper proposes the technique of augmenting the state variables with controller gains. This introduces a non-linearity to the augmented system and thereby the estimation is performed using an Extended Kalman Filter. This results in producing controller gains that are capable of controlling the system in response to changes in load demand, system parameter variation and measurement noise.

Phasor measurement units (PMUs) are preferred for installation at weak buses in a power network. Therefore, the weak buses need to be located and the strategic locations of PMUs identified to ensure network observability. Thus, the primary aim of this work is to identify the placements of the maximum number of PMUs installed at the weak buses in the electrical network. The voltage collapse proximity indicator, line stability index, fast voltage stability index, and a new voltage stability indicator utilizing load flow measurement are used to determine the weak buses. A novel deterministic methodology based on a binary-integer linear programming model is then proposed to determine the optimal locations of PMUs. The effect of a single PMU outage considering the weak buses is also demonstrated. The effectiveness of the developed approach is tested and validated on the standard IEEE 14-, 118-, 300-, and New England 39-bus systems. The obtained results are also compared to those using different weak bus methodologies.

This paper presents a fast hybrid fault location method for active distribution networks with distributed generation (DG) and microgrids. The method uses the voltage and current data from the measurement points at the main substation, and the connection points of DG and microgrids. The data is used in a single feedforward artificial neural network (ANN) to estimate the distances to fault from all the measuring points. A k-nearest neighbors (KNN) classifier then interprets the ANN outputs and estimates a single fault location. Simulation results validate the accuracy of the fault location method under different fault conditions including fault types, fault points, and fault resistances. The performance is also validated for non-synchronized measurements and measurement errors.

PV power production is highly dependent on environmental and weather conditions, such as solar irradiance and ambient temperature. Because of the single control condition and any change in the external environment, the first step response of the converter duty cycle of the traditional MPPT incremental conductance algorithm is not accurate, resulting in misjudgment. To improve the efficiency and economy of PV systems, an improved incremental conductance algorithm of MPPT control strategy is proposed. From the traditional incremental conductance algorithm, this algorithm is simple in structure and can discriminate the instantaneous increment of current, voltage and power when the external environment changes, and so can improve tracking efficiency. MATLAB simulations are carried out under rapidly changing solar radiation level, and the results of the improved and conventional incremental conductance algorithm are compared. The results show that the proposed algorithm can effectively identify the misjudgment and avoid its occurrence. It not only optimizes the system, but also improves the efficiency, response speed and tracking efficiency of the PV system, thus ensuring the stable operation of the power grid.

To improve the robustness and performance of the dynamic response of a cage asynchronous motor, a direct torque control (DTC) based on sliding mode control (SMC) is adopted to replace traditional proportional-integral (PI) and hysteresis comparators. The combination of the proposed strategy with sinusoidal pulse width modulation (SPWM) applied to a three-level neutral point clamped (NPC) inverter brings many advantages such as a reduction in harmonics, and precise and rapid tracking of the references. Simulations are performed for a three-level inverter with SM-DTC, a two-level inverter with SM-DTC and the three-level inverter with PI-DTC-SPWM. The results show that the SM-DTC method achieves better performance in terms of reference tracking, while adoption of the three-level inverter topology can effectively reduce the ripples. Applying the SM-DTC to the three-level inverter presents the best solution for achieving efficient and robust control. In addition, the use of a sliding mode speed estimator eliminates the mechanical sensor and this increases the reliability of the system.

With the development of power electronics technology, the flexible DC grid will play a significant role in promoting the transformation and reformation of the power grid. It is immune to commutation failure and has high flexibility in power control and renewable energy grid integration. However, the protection and fault handling technology for a flexible DC grid is a big challenge because of the limited overcurrent capability of the converters. This paper summarizes the development of the flexible DC grid, and analyzes the fault characteristics in detail. Next, the applicability, advantages and disadvantages of the existing protection principle, fault isolation and recovery schemes are reviewed. Finally, the key problems and development trend of the future flexible DC grid are pointed out and forecasted respectively.

Integration of Information and Communications Technology (ICT) into the distribution system makes today's power grid more remotely monitored and controlled than it has been. The fast increasing connectivity, however, also implies that the distribution grid today, or smart grid, is more vulnerable. Thus, research into intrusion/anomaly detection systems at the distribution level is in critical need. Current research on Intrusion Detection Systems for the power grid has been focused primarily on cyber security at the Supervisory Control And Data Acquisition, and single node levels with little attention on coordinated cyberattacks at multiple nodes. A holistic approach toward system-wide cyber security for distribution systems is yet to be developed. This paper presents a novel approach toward intrusion prevention, using a multi-agent system, at the distribution system level. Simulations of the method have been performed on the IEEE 13-Node Test Feeder, and the results compared to those obtained from existing methods. The results have validated the performance of the proposed method for protection against cyber intrusions at the distribution system level.

The wind turbine startup and shutdown procedures for electrical subsystems are straightforward for wind turbines featuring full-scale power electronic converters and have not required significant attentions from the research community. However, for offshore wind farms featuring series-connected dc collection systems and differential power processing capabilities, the controllable wind turbine power converters might not be rated in such a way that a full-scale output power difference can be handled within a series string. As startup and shutdown procedures can require a transition from zero to full power, a more elaborate design is required to ensure that wind turbines can still start and stop reliably under all conditions, without compromising advantages in reduced wind turbine converter ratings with differential power processing capabilities. In this paper, the startup and shutdown procedures for a series-dc wind farm featuring diode-bridge rectifiers and partial power processing converters as wind turbine converters, are investigated and constraints on converter ratings are evaluated.

The recent legalization of cannabis is facilitating very rapid growth in the cannabis cultivation industry, with the energy intensive indoor cultivation facilities becoming more prevalent. This presents a challenge to utilities as the high energy demand from this industry can overburden the existing utility infrastructure. Hence, from both planning and operational perspectives, it is crucial to understand the energy consumption of the rapidly growing load. This paper proposes a deterministic energy consumption model for indoor cannabis cultivation operations for the two major loads in these facilities, i.e., lighting and HVAC, over a 24-hour period based on equipment specifications and operational requirements of the facility. This model can further be used to estimate or forecast short-term and long-term energy demands and costs of indoor cannabis operation(s). The proposed model successfully simulated the environmental conditions in a real-world cannabis facility, and the model’s energy consumption output is validated using actual measurements taken from this facility as well as model output using GridLab-D.

A benchmark distribution system is developed for investigating control and energy management of distributed generation (DG) at a residential level in the form of three single-phase microgrids. The benchmark is derived from a typical distribution network architecture with common parameters found in North-America systems including wiring specifications, line impedances and connection details for rooftop PV systems. This benchmark system can accommodate microgrids operating in both grid-connected and islanded modes. Within this benchmark, multiple single-phase DG sources located in different phases can be coordinated to form a dynamically balanced three phase system under different load and generation profiles in different phases. The coordination of DG sources in a particular phase is achieved through an intra-phase power management device, while mitigating loads and generation imbalance among all phases are done by an inter-phase power management scheme. It is expected that this benchmark system will facilitate investigation of impacts posed by proliferation of single-phase distributed generation devices and local storage systems in private residences. Three case studies have been carried out to demonstrate the versatility and effectiveness of this benchmark system.

Forecasting has been an essential part of the power and energy industry. Researchers and practitioners have contributed thousands of papers on forecasting electricity demand and prices, and renewable generation (e.g., wind and solar power). This article offers a brief review of influential energy forecasting papers; summarizes research trends; discusses importance of reproducible research and points out six valuable open data sources; makes recommendations about publishing high-quality research papers; and offers an outlook into the future of energy forecasting.

This paper presents a novel methodology to control HVAC system and minimize energy cost on the premise of satisfying power system constraints. A multi-agent architecture based on game theory and reinforcement learning is developed so as to reduce the cost and computational complexity of the microgrid. The multi-agent architecture comprising agents, state variables, action variables, reward function and cost game is formulated. The paper fills the gap between multi-agent HVAC systems control and power system optimization and planning. The results and analysis indicate that the proposed algorithm is beneficial to deal with the problem of “curse of dimensionality” for multi-agent microgrid HVAC system control and speed up learning of unknown power system conditions.

This paper is related to research on parallelization methods for the simulation of electromagnetic transients (EMTs). It presents an automatic parallelization approach based on the solution of sparse matrices resulting from the formulation of network equations. Modified-augmented-nodal analysis is used to formulate network equations. The selected sparse matrix solver is parallelized and adapted to improve performance by pivot validity testing and partial refactorization. Refactorization is needed when dealing with varying topology networks and nonlinear models. The EMT solver employs a fully iterative method for nonlinear functions. Conventional computer CPU-based parallelization is achieved and does not require any user intervention for given arbitrary network topologies. The presented approach is tested on real networks with complex models, including nonlinearities and power-electronics converters for wind generator applications.

The increasing penetration of renewable energy sources (RESs) brings more power generation fluctuations into power systems, which puts forward higher requirement on the regulation capacities for maintaining the power balance between supply and demand. In addition to traditional generators for providing regulation capacities, the progressed information and communication technologies enable an alternative method by controlling flexible loads, especially thermostatically controlled loads (TCLs) for regulation services. This paper investigates the modeling and control strategies of aggregated TCLs as the virtual energy storage system (VESS) for demand response. First, TCLs are modeled as VESSs and compared with the traditional energy storage system (ESS) to analyze their characteristic differences. Then, the control strategies of VESS are investigated in microgrid and main grid aspects, respectively. It shows that VESS control strategies can play important roles in frequency regulation and voltage regulation for power systems’ stability. Finally, future research directions of VESS are prospected, including the schedulable potential evaluation, modeling of TCLs, hierarchical control strategies of VESS considering ESSs and RESs and reliability and fast response in frequency control for VESS.

In this paper, we elaborate a new strategy based on cooperative game theory models to encourage and manage the interactions in a MicroGrid network. The proposed strategy optimizes the cooperation and the energy exchange in a distributed μGrid network. The strategy consists of a two stage algorithm: Coalition formation algorithm which was specifically created to approximate the optimal set of coalitions that return considerable savings. And the Matching game to manage the energy exchange inside each coalition. The performance of our strategy was verified through simulations. These latter show that the losses can be considerably decreased by the use of the proposed strategy: the rate of the loss reduction can reach up to 20% if the two stages are applied on the network. Moreover, the strategy proved to have a fast convergence which makes it operational for real implemented networks.

Recently microgrids have drawn a potential attraction by fulfilling the environmental demands and the increasing energy demands of the end-users. It is necessary to focus on various protection and control aspects of a microgrid. During the transition between the grid-following and grid-forming modes, the voltage and the frequency instability due to the power mismatch condition becomes the major point of concern. Therefore, the paper executes a frequency-active power and voltage-reactive power drooping control strategy for the precise power-sharing among the distributed power generators. Furthermore, to handle the power deficit scenarios and to maintain the system stability, a system independent and priority-based adaptive three-stage load shedding strategy is proposed. The sensitivity of the strategy depends on the system inertia and is computed according to the varying absolute rate-of-change-of-frequency. The strategy incorporates the operation of battery storage system and distributed static compensator (D-STATCOM) in the microgrid, to provide a reliable power supply to the customers for a considerable time instead of a sudden load shedding. The effectiveness of the proposed strategies is investigated on a scaled-down modified IEEE 13-bus microgrid system on the podium of MATLAB 2015b through the time-domain simulation.

In recent years, due to the economic and environmental issues, modern power systems often operate proximately to the technical restraints enlarging the probable level of instability risks. Hence, efficient methods for voltage instability prevention are of great importance to power system companies to avoid the risk of large blackouts. In this paper, an event-driven emergency demand response (EEDR) strategy based on whale optimization algorithm (WOA) is proposed to effectively improve system voltage stability. The main objective of the proposed EEDR approach is to maintain voltage stability margin (VSM) in an acceptable range during emergency situations by driving the operating condition of the power system away from the insecure points. The optimal locations and amounts of load reductions have been determined using WOA algorithm. To test the feasibility and the efficiency of the proposed method, simulation studies are carried out on the IEEE 14-bus and real Algerian 114-bus power systems.

This article presents the direct torque control (DTC) strategy for the doubly fed induction motor (DFIM) connected to two three-level voltage source inverters (3LVSIs) with neutral point clamped (NPC) structure. This control method allows to reduce the torque and flux ripples as well as to optimize the total harmonic distortion (THD) of motor currents. The use of 3LVSI increases the number of generated voltage, which allows improving the quality of its waveform and thus improves the DTC strategy. The system modeling and control are implemented in Matlab/Simulink environment. The analysis of simulation results shows the better performances of this control, especially in terms of torque and flux behavior, compared to conventional DTC.

This paper presents an annual performance evaluation of three maximum power point tracking (MPPT) methods. The used MPPT techniques (Perturb and Observe, Incremental Inductance and Sliding mode) are evaluated under an annual data of atmospheric conditions of the target site. The main contribution of this work is to consider real fluctuation conditions of solar irradiations, ambient temperatures and wind velocities. It was found that the Sliding mode provides higher energy yields independently of the period. Compared to the basic P&O and the IC techniques, sliding mode has the potential of generating up to 8.18% more electrical energy than other techniques.

Heavy fault currents flow in the event of fault at the loads connected in distribution system. To protect these loads, circuit breakers and relays are required at appropriate places with proper coordination between them. This research paper focuses on finding optimum relay setting required for minimum time to interrupt power supply to avoid miscoordination in operation of relays and also investigates effect on time multiplier settings (TMS) of directional overcurrent relays in a system with combined overhead lines-underground cables. Linear programming problem (LPP) approach is used for optimization. It is interesting to know the quantitative variations in TMS as the underground cables have different characteristics than overhead lines.

This work considers the problem of decentralized control of inverter-based ac micro-grid in different operation modes. The main objectives are to (i) design decentralized frequency and voltage controllers, to gather with power sharing, without information exchange between microsources (ii) design passive dynamic controllers which ensure stability of the entire microgrid system (iii) capture nonlinear, interconnected and large-scale dynamic of the micro-grid system with meshed topology as a port-Hamiltonian formulation (iv) expand the property of shifted-energy function in the context of decentralized control of ac micro-grid (v) analysis of system stability in large signal point of view. More precisely, to deal with nonlinear, interconnected and large-scale structure of micro-grid systems, the port-Hamiltonian formulation is used to capture the dynamic of micro-grid components including microsource, distribution line and load dynamics as well as interconnection controllers. Furthermore, to deal with large signal stability problem of the microgrid system in the grid-connected and islanded conditions, the shifted-Hamiltonian energy function is served as a storage function to ensure incremental passivity and stability of the microgrid system. Moreover, it is shown that the aggregating of the microgrid dynamic and the decentralized controller dynamics satisfies the incremental passivity. Finally, the effectiveness of the proposed controllers is evaluated through simulation studies. The different scenarios including grid-connected and islanded modes as well as transition between both modes are simulated. The simulation conforms that the decentralized control dynamics are suited to achieve the desired objective of frequency synchronization, voltage control and power sharing in the grid-connected and islanded modes. The simulation results demonstrate the effectiveness of the proposed control strategy.

The role of Power System Stabilizer (PSS) in the power system is to provide necessary damping torque to the system in order to suppress the oscillations caused by a variety of disturbances that occur frequently and maintain the stability of the system. In this paper, a PSS design technique is proposed using Whale Optimization Algorithm (WOA) by considering eigenvalue objective function. Two bench mark multi machine test systems: three- generator nine- bus system, two- area four- generator inter connected system working on various operating conditions are considered as case studies and tested with the proposed technique. Extensive simulation results are obtained and effectiveness of proposed WOA-PSS are compared with well - known PSO and DE based stabilizers under several disturbances.

In this paper, a particular standard MicroGrid (MG) is accurately simulated in the presence of the Electric Vehicles (EVs) participating in decentralized primary frequency control service. It examines effect of number of the participating EVs on the short-term dynamic behaviour. The simulation results confirm that frequency deviation will not definitely become zero even though an unlimited number of the EVs participate. The output power of each EV is determined according to the frequency deviation. On the other hand, the output power of each EV affects the value of the frequency deviation, especially in small-scale MGs and MGs with predominant inductance behaviour. Eventually, an equilibrium point is reached after a new EV is added that depends on the characteristics of the MG and the functions executed in the MG central controller during such a service. Additionally, effect of Reflex method, an advanced charging technique for EVs, on the frequency deviation is examined.

Multi-Area Multi-Fuel Economic Dispatch (MAMFED) aims to allocate the best generation schedule in each area and to offer the best power transfers between different areas by minimizing the objective functions among the available fuel alternatives for each unit while satisfying various constraints in power systems. In this paper, a Fuzzified Squirrel Search Algorithm (FSSA) algorithm is proposed to solve the single-area multi-fuel economic dispatch (SAMFED) and MAMFED problems. Squirrel Search Algorithm (SSA) mimics the foraging behavior of squirrels based on the dynamic jumping and gliding strategies. In the SSA approach, predator presence behavior and a seasonal monitoring condition are employed to increase the search ability of the algorithm, and to balance the exploitation and exploration. The suggested approach considers the line losses, valve point loading impacts, multi-fuel alternatives, and tie-line limits of the power system. Because of the contradicting nature of fuel cost and pollutant emission objectives, weighted sum approach and price penalty factor are used to transfer the bi-objective function into a single objective function. Furthermore, a fuzzy decision strategy is introduced to find one of the Pareto optimal fronts as the best compromised solution. The feasibility of the FSSA is tested on a three-area test system for both the SAMFED and MAMFED problems. The results of FSSA approach are compared with other heuristic approaches in the literature. Multi-objective performance indicators such as generational distance, spacing metric and ratio of non-dominated individuals are evaluated to validate the effectiveness of FSSA. The results divulge that the FSSA is a promising approach to solve the SAMFED and MAMFED problems while providing a better compromise solution in comparison with other heuristic approaches.

Real time monitoring and control of a modern power system has achieved significant development since the incorporation of the phasor measurement unit (PMU). Due to the time-synchronized capabilities, PMU has increased the situational awareness (SA) in a wide area measurement system (WAMS). Operator SA depends on the data pertaining to the real-time health of the grid. This is measured by PMUs and is accessible for data analytics at the data monitoring station referred to as the phasor data concentrator (PDC). Availability of the communication system and communication delay are two of the decisive factors governing the operator SA. This paper presents a pragmatic metric to assess the operator SA and ensure optimal locations for the placement of PMUs, PDC, and the underlying communication infrastructure to increase the efficacy of operator SA. The uses of digital elevation model (DEM) data of the surface topography to determine the optimal locations for the placement of the PMU, and the microwave technology for communicating synchrophasor data is another important contribution carried out in this paper. The practical power grid system of Bihar in India is considered as a case study, and extensive simulation results and analysis are presented for validating the proposed methodology.

As a key component of an integrated energy system (IES), energy storage can effectively alleviate the problem of the times between energy production and consumption. Exploiting the benefits of energy storage can improve the competitiveness of multi-energy systems. This paper proposes a method for day-ahead operation optimization of a building-level integrated energy system (BIES) considering additional potential benefits of energy storage. Based on the characteristics of peak-shaving and valley-filling of energy storage, and further consideration of the changes in the system’s load and real-time electricity price, a model of additional potential benefits of energy storage is developed. Aiming at the lowest total operating cost, a bi-level optimal operational model for day-ahead operation of BIES is developed. A case analysis of different dispatch strategies verifies that the addition of the proposed battery scheduling strategy improves economic operation. The results demonstrate that the model can exploit energy storage’s potential, further optimize the power output of BIES and reduce the economic cost.

A Simplified Grey Wolf Optimizer (SGWO) is suggested for resolving optimization tasks. The simplification in the original Grey Wolf Optimizer (GWO) method is introduced by ignoring the worst category wolves while giving priority to the better wolves during the search process. The advantage of the presented SGWO over GWO is a better solution taking less execution time and is demonstrated by taking unimodal, multimodal, and fixed dimension test functions. The results are also contrasted to the Gravitational Search Algorithm, the Particle Swarm Optimization, and the Sine Cosine Algorithm and this shows the superiority of the proposed SGWO technique. Practical application in a Distributed Power Generation System (DPGS) with energy storage is then considered by designing an Adaptive Fuzzy PID (AFPID) controller using the suggested SGWO method for frequency control. The DPGS contains renewable generation such as photovoltaic, wind, and storage elements such as battery and flywheel, in addition to plug-in electric vehicles. It is demonstrated that the SGWO method is superior to the GWO method in the optimal controller design task. It is also seen that SGWO based AFPID controller is highly efficacious in regulating the frequency compared to the standard PID controller. A sensitivity study is also performed to examine the impact of the unpredictability in the parameters of the investigated system on system performance. Finally, the novelty of the paper is demonstrated by comparing with the existing publications in an extensively used two-area test system.

Non-renewable fuel sources have been the predominant energy sources and a significant source of foreign exchange income for Nigeria, while at the same time there is a severe problem of electricity inconsistency and persistent power blackouts in Nigeria. The research aims to end the concern for deficient energy use, and to encourage energy efficiency and sustainability. Nigeria has not maximized the advantages of renewable energy after the denationalisation of its electricity industry despite the current transformation in the power industry and the rising demand for renewable energy supply. The research adopts a doctrinal legal approach with a library-based legal research technique with a comparative legal method. It reveals that the absence of a comprehensible legal regime with encouragement for the use of renewable energy is the fundamental element causing the slow utilization of renewable energy as a substitute source of energy in Nigeria. It is suggested that, among other reforms, there is a need for a comprehensible legal regime on renewable energy and the encouragement of strict implementation of energy regulatory strategies and policies with incentives for the application of renewable energy sources in Nigeria.

This paper presents a novel composite wide area control of a DFIG wind energy system which combines the Robust Exact Differentiator (RED) and Discontinuous Integral (DI) control to damp out inter-area oscillations. RED generates the real-time differentiation of a relative speed signal in a noisy environment while DI control, an extension to a twisting algorithm and PID control, develops a continuous control signal and hence reduces chattering. The proposed control is robust to disturbances and can enhance the overall stability of the system. The proposed composite sliding mode control is evaluated using a modified benchmark two-area power system model with wind energy integration. Simulation results under various operating scenarios show the efficacy of the proposed approach.

With respect to sensitivity, selectivity and speed of operation, the current differential scheme is a better way to protect transmission lines than overcurrent and distance-based schemes. However, the protection scheme can be severely influenced by the Line Charging Capacitive Current (LCCC) with increased voltage level and Current Transformer (CT) saturation under external close-in faults. This paper presents a new UHV/EHV current-based protection scheme using the ratio of phasor summation of the two-end currents to the local end current, instead of summation of the two-end currents, to discriminate the internal faults. The accuracy and effectiveness of the proposed protection technique are tested on the 110 kV Western System Coordinating Council (WSCC) 9-bus system using PSCAD/MATLAB. The simulation results confirm the reliable operation of the proposed scheme during internal/external faults and its independence from fault location, fault resistance, type of fault, and variations in source impedance. Finally, the effectiveness of the proposed scheme is also verified with faults during power swing and in series compensated lines.

In a deregulated power system uncertainty exists and lack of sufficient damping can lead to Low Frequency Oscillations (LFO). The problem can be addressed using robust Power System Stabilizers (PSS). In this paper, an optimal procedure to design a robust PID-PSS using interval arithmetic for the Single Machine Infinite Bus (SMIB) power system is proposed. The interval modelling captures the wide variations of operating conditions in bounds of system coefficients. In the proposed design procedure, simple and new closed loop stability conditions for an SMIB interval system are developed and are used to design an optimum PID-PSS for improving the performance of an SMIB system. The optimum PID-PSS is attained by tuning the parameters using the FMINCON tool provided in MATLAB. The robustness of the proposed PID-PSS design is validated and compared to other notable methods in the literature when the system is subjected to different uncertainties. The simulation results and performance error values show the effectiveness of the proposed robust PID-PSS controller.

With the rapid development of the smart grid and increasingly integrated communication networks, power grids are facing serious cyber-security problems. This paper reviews existing studies on the impact of false data injection attacks on power systems from three aspects. First, false data injection can adversely affect economic dispatch by increasing the operational cost of the power system or causing sequential overloads and even outages. Second, attackers can inject false data to the power system state estimator, and this will prevent the operators from obtaining the true operating conditions of the system. Third, false data injection attacks can degrade the distributed control of distributed generators or microgrids inducing a power imbalance between supply and demand. This paper fully covers the potential vulnerabilities of power systems to cyber-attacks to help system operators understand the system vulnerability and take effective countermeasures.

Considering power quality problems such as overvoltage and three-phase unbalance caused by high permeability distributed photovoltaic access in low-voltage distribution networks, this paper proposes a comprehensive control scheme using a static var. generator (SVG), electric energy storage (EES), a phase switching device (PSD) and an intelligent terminal controller. The control strategies of transformer overload, bus over/under voltage, anti-countercurrent, storage battery state of charge (SOC) maintenance, and three-phase unbalance are studied. The engineering application in the Greenvale low-voltage distribution networks in Australia with high permeability distributed photovoltaics is discussed. The results show that the intelligent terminal controller is able to improve the power quality of low-voltage distribution networks through coordination with EES, SVG and PSD.

Conventional proportional integral derivative (PID) controllers are being used in the industries for control purposes. It is very simple in design and low in cost but it has less capability to minimize the low frequency noises of the systems. Therefore, in this study, a low pass filter has been introduced with the derivative input of the PID controller to minimize the noises and to improve the transient stability of the system. This paper focuses upon the stability improvement of a wind-diesel hybrid power system model (HPSM) using a static synchronous compensator (STATCOM) along with a secondary PID controller with derivative filter (PIDF). Under any load disturbances, the reactive power mismatch occurs in the HPSM that affects the system transient stability. STATCOM with PIDF controller is used to provide reactive power support and to improve stability of the HPSM. The controller parameters are also optimized by using soft computing technique for performance improvement. This paper proposes the effectiveness of symbiosis organisms search algorithm for optimization purpose. Binary coded genetic algorithm and gravitational search algorithm are used for the sake of comparison.

Demand Response (DR) provides both operational and financial benefits to a variety of stakeholders in the power system. For example, in the deregulated market operated by the Electric Reliability Council of Texas (ERCOT), load serving entities (LSEs) usually purchase electricity from the wholesale market (either in day-ahead or real-time market) and sign fixed retail price contracts with their end-consumers. Therefore, incentivizing end-consumers’ load shift from peak to off-peak hours could benefit the LSE in terms of reducing its purchase of electricity under high prices from the real-time market. As the first-of-its-kind implementation of Coupon Incentive-based Demand Response (CIDR), the EnergyCoupon project provides end-consumers with dynamic time-of-use DR event announcements, individualized load reduction targets with EnergyCoupons as the incentive for meeting these targets, as well as periodic lotteries using these coupons as lottery tickets for winning dollar-value gifts. A number of methodologies are developed for this special type of DR program including price/baseline prediction, individualized target setting and a lottery mechanism. This paper summarizes the methodologies, design, critical findings, as well as the potential generalization of such an experiment. Comparison of the EnergyCoupon with a conventional Time-of-Use (TOU) price-based DR program is also conducted. Experimental results in the year 2017 show that by combining dynamic coupon offers with periodic lotteries, the effective cost for demand response providers in EnergyCoupon can be substantially reduced, while achieving a similar level of demand reduction as conventional DR programs.

Introduction Aspects of power system protection which contributes to mal-operations and blackouts can be improved by supervision of system behavior and response based analysis rather than condition-based or event-based analysis using wide area measurements based on synchrophasor technology. The paper explores the application of micro-Phasor Measurement Unit for time synchronized real-time distribution network monitoring and agile decision support schemes for system prognosis and control. Case description The scheme is proposed as part of a project on “Power System Voltage Stability Analysis using synchrophasors in Distribution System of Kerala Grid” at Kerala State Electricity Board Ltd. An actual grid occurrence during the severe tropical cyclone Ockhi, is considered as the base case which motivated the work. Discussion and evaluation A voltage stability index (VSI) based special protection scheme (SPS) for radial distribution network at a proposed smart city is presented in the present study. The proposed special protection scheme on actual implementation can use data from proposed local micro-Phasor Measurement Unit. The PMU is proposed to be placed at one of the key nodes of the distribution system network in the city. Conclusion The VSI is derived using local phasor values and is used to initiate a Special Protection Scheme for N-1 contingency at the key node, so as to ensure availability of the most essential feeder which provides supply to a hospital campus housing several health institutes of prime importance. The voltage stability index derived is tested and SPS is validated using real-time grid data.

Considering the advantages and limitations of traditional identification method, combined with the strategy of active detection, the principle of DC grid pilot protection based on active detection is proposed to improve the sensitivity and reliability of hybrid MMC DC grid protection, and to ensure the accurate identification of fault areas in DC grid. By using the DC fault ride-through control strategy of the hybrid sub-module MMC, the fault current at the converter station DC terminal is limited. Based on the high controllability of hybrid MMC, sinusoidal fault detection signals with the same frequency are injected into the line at each converter station. Based on model recognition, the capacitance model condition is satisfied by the detected signals at both ends during external faults whereas not satisfied during internal faults. The Spearman correlation coefficients is then introduced, and the correlation discriminant of capacitance model is constructed to realize fault area discrimination of DC grid. The simulation results show that the active detection protection scheme proposed in this paper can accurately identify the fault area of DC grid, and is not affected by fault impedance and has low sampling rate requirement.

Based on the large-scale penetration of electric vehicles (EV) into the building cluster, a multi-objective optimal strategy considering the coordinated dispatch of EV is proposed, for improving the safe and economical operation problems of distribution network. The system power loss and node voltage excursion can be effectively reduced, by taking measures of time-of-use (TOU) price mechanism bonded with the reactive compensation of energy storage devices. Firstly, the coordinate charging/discharging load model for EV has been established, to obtain a narrowed gap between load peak and valley. Next, a multi-objective optimization model of the distribution grid is also defined, and the active power loss and node voltage fluctuation are chosen to be the objective function. For improving the efficiency of optimization process, an advanced genetic algorithm associated with elite preservation policy is used. Finally, reactive compensation capacity supplied by capacitor banks is dynamically determined according to the varying building loads. The proposed strategy is demonstrated on the IEEE 33-node test case, and the simulation results show that the power supply pressure can be obviously relieved by introducing the coordinated charging/discharging behavior of EV; in the meantime, via reasonable planning of the compensation capacitor, the remarkably lower active power loss and voltage excursion can be realized, ensuring the safe and economical operation of the distribution system.

The Wind Energy Conversion System (WECS) based Doubly Fed Induction Generator (DFIG) has experienced a rapid development in the world, which leads to an increasing insertion of this source of energy in the electrical grids. The sudden and temporary drop of voltage at the network can affect the operation of the DFIG; the voltage dips produce high peak currents on the stator and rotor circuits, without protection, the rotor side converter (RSC) will suffer also from over-current limit, consequently, the RSC may even be destroyed and the generator be damaged. In this paper a new Direct Power Control (DPC) method was developed, in order to control the stator powers and help the operation of the aero-generator during the faults grid; by injecting the reactive power into the network to contribute to the return of voltage, and set the active power to the optimum value to suppress the high peak currents. The DPC method was designed using the nonlinear Backstepping (BS) controller associated with the Lyapunov function to ensure the stability and robustness of the system. A comparison study was undertaken to verify the robustness and effectiveness of the DPC-BS to that of the classical vector control (VC) using Proportional-Integral (PI) correctors. All were simulated under the Simulink® software.