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Inclusion of intermittent natured renewable energy resources in microgrid to reduce global warming, especially in shipboard power system and due to highly fluctuating propulsion load, frequency control strategy of isolated shipboard hybrid microgrid (ISHMG) is major point of attraction. Hence, a power system of marine vessel with dish‐stirling solar thermal system (DSTS), wind‐driven generation (WDG), solid oxide fuel cell (SOFC), super‐conducting magnetic energy storage (SMES), two different AC‐loads, and propulsion loads are considered as an ISHMG. The main objective of this paper is reducing the mismatch between generation and demand with the help of fractional‐order proportional integral‐derivative (FOPID) controller. To improve the frequency control, the tuning of the controller coefficients plays a major role as the controller's performance fully dependent on the parameters. Accordingly, the recently developed butterfly optimization algorithm (BOA) has been used to optimize the FOPID controller's parameters. Comparative analysis of several techniques like FA, PSO, GOA, SSA, and BOA used for PID, PI, FOPID controllers' optimization, and sensitivity analysis under different parametric variation has been presented to prove the stability of the ISHMG model. Analyzing all the results, it is found that BOA‐based FOPID controller is performing the frequency control far better than other techniques. [ABSTRACT FROM AUTHOR]

This study presents a novel frequency regulation solution for renewables (wind‐solar tower)‐bio (biodiesel‐biogas) cogenerated independent dual‐area interlinked microgrid power system (IµPS) with collective effect of time delay and flexible gate‐controlled series capacitor (GCSC). As a component, a non‐integer proportional fractional integral fractional derivative (PFIFD) controller is introduced whose dynamic responses is compared with integer order PID (IOPID) and fractional order PI (FOPI) controllers. The findings demonstrate that the suggested non‐integer PFIFD controller performs better than IOPID and FOPI at giving superior dynamic properties, such as different decision parameters and minimum error function (J). Subsequently, to obtain the optimally tuned controllers' parameters, a recently developed yellow saddle goatfish technique (YSGA) is leveraged. In this study, the comparative effect of time delay, interline power flow controller (IPFC) and GCSC scheme have been analyzed under real time wind data in IµPS. Further, a meticulous sensitivity assessment of YSGA tuned PFIFD controller is performed under different uncertainties. The improved results show that the recommended YSGA‐based PFIFD controller offers a wonderful improvement in system frequency stability under a variety of situations, including system uncertainties, physical constraints, and significant renewables penetration. Finally, real‐time hardware‐in‐the‐loop (HIL) simulation platform is utilized to validate the proposed control approach. [ABSTRACT FROM AUTHOR]

The ongoing pandemic due to novel coronavirus disease-2019 (COVID-19) has rapidly unsettled the health sector with a considerable fatality rate. The main factors that help minimize the spread of this deadly virus are the proper use of masks, social distancing and antibody growth rate in a person. Based on these factors, we propose a new nature-inspired meta-heuristic algorithm named COVID-19 Based Optimization Algorithm (C-19BOA). The proposed C-19BOA mimics the spread and control behavior of coronavirus disease centered on three containment factors: (1) social distancing, (2) use of masks, and (3) antibody rate. Initially, the mathematical models of containment factors are presented, and further, the proposed C-19BOA is developed. To ascertain the effectiveness of the developed C-19BOA, its performance is verified on standard IEEE mathematical benchmark functions for the minimization of these benchmark functions and convergence to the optimal values. These performances are compared with established bio-inspired optimization algorithms available in the literature. Finally, the developed C-19BOA is applied on an electrical power system load–frequency–control model to test its effectiveness in optimizing the power system parameters and to check its applicability in solving modern engineering problems. A performance comparison of the proposed C-19BOA and other optimization algorithms is validated based on optimizing the controller gains for reducing the steady-state errors by comparing the effective frequency and tie-line power regulation ability of an industrially applied Proportional–Integral–Derivative controller (PID) and Active Disturbance Rejection controller (ADRC). Moreover, the robustness of C-19BOA optimized PID and ADRC gains is tested by varying the system parameters from their nominal values. [ABSTRACT FROM AUTHOR]

Power system control is an important issue with regard to power system safety, flexibility, and reliability. Over the years, various new power system control strategies have been explored, but the main disadvantage of these control strategies is their complexity in structures with respect to industrially applied PID controller. The present paper introduces a novel control strategy based on modified disturbance rejection control, which is a modification of the PID controller that not only preserves the simplicity of control design but also offers an effective control based on state observer-based control law. The proposed control strategy addresses some basic limitations of a PID controller and implements modified control law to remove these limitations. In order to prove the effective control of the proposed control strategy, a standard IEEE-39 bus power system integrated with renewable energy generations is developed, and a comparative analysis of the proposed controller is performed with respect to its ancestor controllers. The comparison is validated based on the system dynamic responses like frequency and tie-line power deviations when the power system is subjected to different disturbances. Furthermore, the power system is integrated with electric vehices (EVs) in vehicle-to-grid (V2G) mode in order to ascertain the effect of EVs when used in V2G mode. A novel study is carried out in which the optimal location of EVs in the power system is determined based on the enhancement in stability of the power system by EVs. The analyses are carried out in MATLAB Simulink software. Simulation reports reflect the optimal control action of the proposed controller with respect to already established strategies projected in the literature. Moreover, the results illustrate that EVs when connected in Area 1 and Area 3 of the power system, the system deviations and steady-state errors are much less as compared to the other cases. [ABSTRACT FROM AUTHOR]

Green energy sources are implemented for the generation of power due to their substantial advantages. Wind generation is the best among renewable options for power generation. Generally, the wind system is directly connected with the power network for supplying power. In direct connection, there is an issue of managing power quality (PQ) concerns such as voltage sag, swells, flickers, harmonics, etc. In order to enhance the PQ in a power network with a wind energy conversion system (WECS), peripheral compensation is needed. In this paper, we highlight a novel control technique to improve the PQ in WECS by adopting an Artificial Neural Network (ANN)-based Distribution Static Compensator (DSTATCOM). In our proposed approach, an online learning-based ANN Back Propagation (BP) model is used to generate the gate pulses of the DSTATCOM, which mitigate the harmonics at the grid side. It is modelled using the MATLAB platform and the total harmonic distortion (THD) of the system is compared with and without DSTATCOM. The harmonics at the source side decreased to less than 5% and are within the IEEE limits. The results obtained reveal that the proposed online learning-based ANN-BP is superior in nature. [ABSTRACT FROM AUTHOR]

Phasor measurement units (PMUs) are widely used to monitor the operating conditions of a smart grid. The PMU communication network is, generally, a public wide area network, hence it is vulnerable to cyberattacks. At present, IEEE C37.118.2 is widely used as the communication standard for PMU communication. However, the IEEE C37.118.2 standard does not specify any security mechanism to protect the PMU data from cyberattacks. Deviation in the transmitted data of PMUs may lead to devastating consequences, such as blackouts in the grid. To mitigate cyberattacks on a PMU, this article proposes a security mechanism based on key distribution scheme that ensures integrity along with confidentiality. This mechanism involves addition of new security fields to IEEE C37.118.2 message structure. The introduction of security mechanism imposes additional computational complexity on resource constraint PMU devices and addition of new security fields in PMU message structure increases overall message size which in turn increases communication delays. In order to assess the additional computational complexity and increased communication delays, an experimental set up consisting of PMU simulators and network emulator is developed in this article. The developed PMU simulator generates IEEE C37.118.2 messages with proposed security mechanisms. Results validate the applicability of the proposed security mechanism in PMU networks without any repercussions. [ABSTRACT FROM AUTHOR]

The aim of the current paper is to present a mimetic algorithm called the chaotic evolutionary programming Powell's pattern search (CEPPS) algorithm for the solution of the multi-fuel economic load dispatch problem. In the CEPPS algorithm, the exploration process is maintained by chaotic evolutionary programming, whereas exploitation is taken care off by a pattern search. The proposed CEPPS has two variants based on the Gauss map and the tent map. Seven generalized benchmark test functions and six cases of the multi-fuel economic load dispatch problem are considered for the performance analysis. It is observed from the analysis that the CEPPS solution procedure based on the tent map exhibits superiority to obtain an excellent solution and better convergence characteristics than traditional chaotic evolutionary programming. Further, the performance investigation for the considered economic load dispatch shows that the Gauss map CEPPS solution procedure performs better than the tent map based CEPPS to obtain the solution of the multi-fuel economic dispatch problem. [ABSTRACT FROM AUTHOR]

Smart grid is the nexus of advanced information and communication technologies and legacy power systems. With increasing awareness on the vulnerabilities of smart grids to cyberattacks, cybersecurity is becoming a prime concern. Earlier, it was assumed that the power system communication protocols are very specialized and different, so the “security by obscurity” approach would be sufficient. However, with the standardization of communication protocols for power utilities and the emergence of the power market, this approach is no longer valid. IEC 62351 Standard has been published to provide security recommendations for different power system communication protocols including IEC 61850. IEC 61850 is emerging as the most promising and popular power system communication standard. Therefore, in this article, a detailed analysis of security threats, possible attacks, and security requirements for IEC 61850 communication is presented. Building on this, the security considerations presented in IEC 62351 for securing different IEC 61850 messages, such as generic object-oriented substation events (GOOSE), sampled values (SV), routable-GOOSE, routable-SV, and manufacturing message specification messages have been presented in great detail. [ABSTRACT FROM AUTHOR]

The concept of energy Internet (EI) is very promising due to its ability to integrate distributed generators and storage devices. Energy routers (ERs) enable highly efficient, reliable, and flexible power system operation. To dynamically control and optimize energy flow in EI, an extensive communication is required. Considering the diversity of generators and ERs, it is crucial that such communication is achieved in a standardized and interoperable way. In this paper, an improved energy routing algorithm and its impact in EI operation are demonstrated. Furthermore, a full communication solution is developed for ERs and their interaction with grid operator. This paper proposes an International Electrotechnical Commission (IEC) 61850 communication-based power routing algorithm in microgrids. Optimal selection of source and routing path is achieved according to the proposed algorithm and communicated to the ERs via IEC 61850 based communication. The effectiveness of the proposed IEC 61850 communication-based routing algorithm is verified on network emulation platform comprising of IEC 61850 emulator tools and network simulator tool. [ABSTRACT FROM AUTHOR]

IEC 61850 is poised to be the communication standard of the future power networks. Due to its historical evolution, it focuses on substation automation and modeling its entities. There have been recent extensions in the standard's modeling to include other grid equipment as well as distributed generators. However, the configuration of the communication network, as it is outlined in IEC 61850-6, is very substation-focused and cannot be used for microgrids. The microgrid network is a wide-area network with multiple distributed generations (DGs) cannot be configured in a manner similar to a substation communication network detailed in IEC 61850-6. This is because the enhanced system configuration description language (SCL) files cannot be exchanged with each DG while this is not an issue for substation modeling. Also, this would result in multiple copies of enhanced SCL files and is not feasible to implement. Thus, there is a need to develop a process for configuring IEC 61850 based communication networks at the microgrid level. This paper proposes a central configurator and a step-by-step configuration procedure for modeling microgrids according to IEC 61850. Such a configurator assists in connecting IEDs in different locations and updates the system with the new deployment. The process is shown with a centralized microgrid protection scheme by employing a microgrid-level system configurator. [ABSTRACT FROM AUTHOR]

Recent developments in renewable energy and information technology (IT) fields made it easier to set up power systems at a smaller scale. This proved to be a turning point for developing first-access electricity systems for the underserved locations around the world. However, there are planning and operation challenges due to lack of past data on such places. Deployment of Internet-of-Things (IoT) devices and proliferation of smart infrastructures with additional sensors will lead to tremendous opportunities for gathering very useful data. For different stakeholders to access and manage these data, trusted and standardized mechanisms need to be in place. Storing proper data in a well-structured common format allows for collaborative research across disciplines, large-scale analytics, and sharing of algorithms and methodologies, in addition to improved customer service. Data standardization plays a more vital role in the context of electricity access in the underdeveloped countries, where there is no past data on generation or consumption as in utility grids. Data collected in a standard structure, being it for a short period of time, facilitate learning from the past experiences, monitoring the current projects, and delivering better results in the future endeavors. It will result in ways to better assist consumers and help the industry operate more efficiently by sharing data with different stakeholders. It can also enhance competition, thus making electricity accessible faster and to more people. The focus of this article is data standardization for first-access electricity systems, in general, and renewable energy-based microgrids, in particular. Different data sources and ways that the corresponding data can be exploited, technological and capacity constraints for storage of data, political and governance implications, as well as data security and privacy issues, are examined. This article is relevant to different stakeholders, such as investors, public utilities, nongovernmental organizations (NGOs), and communities. Using the data standardization approach developed here, it is possible to create a much-needed first-access electricity system database. This will provide an important resource for project developers and energy companies to assess the potential of a certain unelectrified site, estimating its demand growth in time and establishing universal control systems that can seamlessly communicate with different components. [ABSTRACT FROM AUTHOR]

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Intermittency of renewable energy resources makes reactive power management a challenge in microgrids. Since standards do not recommend the use of distributed energy resources (DERs) for voltage regulation and reactive power management in microgrids, therefore, traditionally, locally controlled Distribution STATic COMpensators (DSTATCOM) are widely used. The management of reactive power requirement in microgrids can be improved through communication-based coordinated operation of DERs and DSTATCOM. To make this communication standardized and interoperable, this paper presents modeling of DSTATCOM as per IEC 61850 and an eXtensible Message Presence Protocol (XMPP) for providing scalability and information security. The mapping of IEC 61850 Abstract Communication Service Interface services over MMS ASN.1 XER (XMPP—web protocol) to transform the basic MMS type message into an XML message for their use in XMPP communication is also demonstrated. [ABSTRACT FROM AUTHOR]

IEC 62351-6 standard stipulates the use of digital signatures for ensuring integrity and authenticity in IEC 61850 Generic Object-Oriented Substation Events (GOOSE) message exchanges. Yet, it does not specify any method for ensuring confidentiality in GOOSE messages. With rapid growth of IEC 61850 from substation automation to power management domain, sensitive data that requires privacy is carried over GOOSE messages. In this letter, a novel method employing Authenticated Encryption with Associated Data (AEAD) algorithms is proposed to achieve both confidentiality and integrity of GOOSE messages. Further, lab tests are run to observe the timing performance and applicability of these algorithms to GOOSE messages with strict timing requirements. [ABSTRACT FROM AUTHOR]

Increasingly, electric vehicles (EVs) are being adopted and integrated into intelligent transport systems (ITSs) as developed countries continue to the push for sustainable transport solutions that offer higher energy efficiency and reduced carbon emissions. EVs communication with roadside units (RSUs) in ITSs and smart grid is possible using onboard units for wireless transmission. This paper presents the different information models for vehicle-to-infrastructure (V2I) and vehicle-to-grid (V2G) communication based on the IEEE 1609 WAVE and IEC 61850 standards, respectively. Utilizing EVs communication with smart grid components such as charging stations (CSs) will help utilities better manage the EV load on their distribution networks. To this effect, an EV charging management scheme based on communication between EVs and RSU is presented. The performance evaluation in terms of end-to-end delay of the proposed harmonized communication over different vehicular ad-hoc network (VANET) protocols is simulated in Riverbed Modeler. The results show that protocols with lower overhead have better performance. [ABSTRACT FROM AUTHOR]

Today's power utilities, around the world, own multiple substations that are connected together to form a complex energy network. The functions within and between these substations are being automated according to globally accepted power utility automation standard IEC 61850. This automation results in efficient operation and enhanced protection of power network with the aid of the communication system. Implementing the protection schemes modeled using communication configurations of standardized information exchange will lead to digital power grid. Designing an IEC-61850-based protection scheme to take care of the faults outside the substations is a challenge, as the typical local-area-network-based generic-object-oriented substation events and sampled-value messages need to be transmitted over a wide-area network. This paper presents communication configuration for line current differential protection schemes applied between two automated substations. It presents the simulation results of communication configuration network between two substations. Its performance is evaluated using a network simulator tool. This study intends to guide the development of a robust protection scheme with IEC-61850-based communication configuration. [ABSTRACT FROM PUBLISHER]

High-speed peer-to-peer IEC 61850-8-1 GOOSE and IEC 61850-9-2 sampled values based information-exchange among IEDs in modern IEC 61850 substations have opened the opportunity for designing and developing innovative all-digital protection applications. The transmission reliability and real-time performance of these SVs and GOOSE messages, over the process-bus network, are critical to realize these all-digital IEC 61850 substation automation systems (SASs) protection applications. To address the reliability, availability, and deterministic delay performance needs of SAS, a novel IEC 61850-9-2 process-bus based substation communication network (SCN) architecture is proposed in this article. Reliability of the proposed as well as the traditional process-bus based SCN architectures is evaluated using the reliability block diagram (RBD) approach. Network components are modeled, and end-to-end (ETE) time-delay performance is also evaluated for all-digital protection applications running on the SCN architectures simulated in the OPNET modeler platform. The reliability and performance results of the proposed architecture compared to the traditional architectures confirmed its highly reliable, fast, and deterministic nature. [ABSTRACT FROM AUTHOR]

This paper presents a day-ahead demand-side management (DSM)-integrated hybrid power management algorithm (PMA) with an objective of combined economic and emission load dispatch (CEED) considering losses. The algorithm was tested on an IEEE 30-bus six-generator system consisting of solar thermal/wind/wave/battery energy storage systems (BESSs) considering real-time data of the Gujarat (19°07′ N, 72°51′ E) coastal region and diverse renewable energy (RES) and storage sources. A maiden attempt of utilizing hybrid firefly particle swarm optimization (HFPSO) to reduce thermal energy consumption and carbon emission was presented. Further, a novel attempt for a versatile renewable power management system was proposed based on a day-ahead pricing scheme to manage load demand and generation effectively. The PMA permits the users to bring down the general load demand and adjust the load curve during the peak time frame. The comparative performance of particle swarm optimization (PSO), firefly algorithm (FA), and HFPSO algorithms in solving the objective was presented. The HFPSO algorithm was found to be the best in terms of a fuel cost of 544.160 (USD/h), emission 20.301 (kg/h), and peak-load reduction of 31.292%, 24.210%, and 51.197% for residential, commercial, and industrial loads, respectively, when contrasted with the other two algorithms PSO and FA. [ABSTRACT FROM AUTHOR]

This work presents the power generation control of a two-area, hybrid, deregulated power system integrated with renewable energy sources (RES). The incorporation of appropriate system non-linearities and RES into the power system makes it complex, but more practical. The hybrid deregulated power system with RES is a complex nonlinear system that regularly exposes the major issue of system dynamic control due to insufficient damping under varying loading circumstances. The generation-demand equilibrium point of the power system varies following a contingency; hence, it becomes difficult to maintain the appropriate equilibrium point via traditional control approaches. To solve this problem, novel control approaches, along with rapid-acting energy storage devices (ESD), are immediate need for advanced power systems. As a result, various secondary controllers are inspected for improvements in system dynamics. A performance comparison infers the cascaded ID-PD controller as the optimum one. The secondary controller gains are successfully optimized by the powerful satin bowerbird optimization (SBO) technique. Additionally, the impact of a super-conducting-magnetic-energy-storage (SMES) device in system dynamics and control of developed power system is analyzed in this study. A sensitivity evaluation (SE) infers that SBO-optimized cascaded ID-PD controller gains are strong enough for alterations in load perturbations, system loading, inertial constant (H), solar irradiance and the DISCO involvement matrix (DIM). [ABSTRACT FROM AUTHOR]

Concerned with the increasing greenhouse gases in the atmosphere due to fossil fuels, the entire world is focusing on electricity generation through renewable energy resources. The most advantageous aspect of the distributed renewable sources is to provide the electricity to remote, scattered and the deprived rural areas by developing the hybrid power system at the smaller scale where power transmission through grid extension is not viable due to some economical, technical or environmental constraints for building new transmission lines. An accurate and adequate control strategy becomes inevitable to uphold the smooth operation by restraining the frequency and voltage deviation within its limit ensuring the highest degree of reliability of hybrid power system to provide an adequate power quality. In this paper, a comprehensive review of different control strategies adopted in isolated and interconnected multi-area hybrid power systems is presented. [ABSTRACT FROM AUTHOR]

In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. The entire set of such techniques is classified as algorithms based on a population where the initial population is randomly created. Input parameters are initialized within the specified range, and they can provide optimal solutions. This paper emphasizes enhancing the neural network via optimization algorithms by manipulating its tuned parameters or training parameters to obtain the best structure network pattern to dissolve the problems in the best way. This paper includes some results for improving the ANN performance by PSO, GA, ABC, and BSA optimization techniques, respectively, to search for optimal parameters, e.g., the number of neurons in the hidden layers and learning rate. The obtained neural net is used for solving energy management problems in the virtual power plant system. [ABSTRACT FROM AUTHOR]

This study uses an artificial neural network (ANN) as an intelligent controller for the management and scheduling of a number of microgrids (MGs) in virtual power plants (VPP). Two ANN-based scheduling control approaches are presented: the ANN-based backtracking search algorithm (ANN-BBSA) and ANN-based binary practical swarm optimization (ANN-BPSO) algorithm. Both algorithms provide the optimal schedule for every distribution generation (DG) to limit fuel consumption, reduce CO2 emission, and increase the system efficiency towards smart and economic VPP operation as well as grid decarbonization. Different test scenarios are executed to evaluate the controllers' robustness and performance under changing system conditions. The test cases are different load curves to evaluate the ANN's performance on untrained data. The untrained and trained load models used are real-load parameter data recorders in northern parts of Malaysia. The test results are analyzed to investigate the performance of these controllers under varying power system conditions. Additionally, a comparative study is performed to compare their performances with other solutions available in the literature based on several parameters. Results show the superiority of the ANN-based controllers in terms of cost reduction and efficiency. [ABSTRACT FROM AUTHOR]

In the current scenario, sustainable power generation received greater attention due to the concerns of global warming and climate change. In the present paper, a Solar Photovoltaic/Diesel Generator/ Battery-based hybrid system has been considered to meet the electrical energy demand of a remote location of India. The cost of the energy of hybrid system is minimized using a Biogeography-based Optimization (BBO) algorithm under the constraints of power reliability, carbon emission and renewable energy fraction. Load following and cycle charging strategies have been considered in order to investigate the performance analysis of the proposed hybrid system. Further, different component combinations of specifications available on the market are presented for detail analysis. The minimum cost of energy of the proposed hybrid system is obtained as 0.225 $/kWh. [ABSTRACT FROM AUTHOR]

This work is the earliest attempt to propose an integrated resource planning for distributed hybrid microgrids considering virtual-inertia support (VIS) and demand-response support (DRS) systems. Initially, three-distributed sustainable energy-based unequal hybrid microgrids are envisioned with the availability of solar/wind/bioenergy resources. In order to overcome the effects of intermittency in renewable resources and low inertia, each microgrid is incorporated with DRS and VIS units for demand- and supply-side management, respectively. The proposed system is simulated in MATLAB considering real-time recorded solar/wind data with realistic loading for 12 months. A novel quasi-oppositional chaotic selfish-herd optimization (QCSHO) algorithm is proposed by hybridizing quasi-opposition-based learning and chaotic linear search techniques into the selfish-herd optimization, for optimal regulation of voltage and frequency in microgrids. Then, the system responses are compared with 7 algorithms and 5 error functions to tune PID controllers' gains, which confirmed the superiority of QCSHO over others. Then, the study proceeds to investigate the voltage, frequency, and tie-line power coordination in 5 extreme scenarios of source and load variations in the proposed system without retuning the controllers. Finally, the system responses are analyzed for 10 different possible allocation of VIS and DRS units in different microgrids to find the most suitable combinations, and the results are recorded. [ABSTRACT FROM AUTHOR]

Increased connectivity is required to implement novel coordination and control schemes. IEC 61850-based communication solutions have become popular due to many reasons—object-oriented modeling capability, interoperable connectivity and strong communication protocols, to name a few. However, communication infrastructure is not well-equipped with cybersecurity mechanisms for secure operation. Unlike online banking systems that have been running such security systems for decades, smart grid cybersecurity is an emerging field. To achieve security at all levels, operational technology-based security is also needed. To address this need, this paper develops an intrusion detection system for smart grids utilizing IEC 61850's Generic Object-Oriented Substation Event (GOOSE) messages. The system is developed with machine learning and is able to monitor the communication traffic of a given power system and distinguish normal events from abnormal ones, i.e., attacks. The designed system is implemented and tested with a realistic IEC 61850 GOOSE message dataset under symmetric and asymmetric fault conditions in the power system. The results show that the proposed system can successfully distinguish normal power system events from cyberattacks with high accuracy. This ensures that smart grids have intrusion detection in addition to cybersecurity features attached to exchanged messages. [ABSTRACT FROM AUTHOR]

As the number of EVs increases, their impact on electrical systems will be substantial. Novel management schemes are needed to manage the electrical load they require when charging. Literature is rich with different techniques to manage and control this effect on the grid by controlling and optimizing power flow. Although these solutions heavily rely on communication lines, they mostly treat communication as a black box. It is important to develop communication solutions that can integrate EVs, charging stations (CSs), and the rest of the grid in an interoperable way. A standard approach would be indispensable as there are different EV models manufactured by different companies. The IEC 61850 standard is a strong tool used for developing communication models for different smart grid components. However, it does not have the necessary models for implementing smart EV management schemes that coordinate between EVs and CSs. In this paper, these missing links are addressed through the development of corresponding models and message mapping. A hardware-in-the-loop test is performed to validate the communication models and cross-platform operation. Then, a co-simulation environment is used to perform a combined study of communication and the power system components. The developed communication model helps integrate the EVs to a centralized, coordinated voltage control scheme. These models can be used to run extensive impact studies where different domains of smart grids need to be considered simultaneously. The main contribution of this paper is the development of smartgrid communication solutions for enabling successful information exchanges. [ABSTRACT FROM AUTHOR]

It is known that keeping the power balance between generation and demand is crucial in containing the system frequency within acceptable limits. This is especially important for renewable based distributed hybrid microgrid (DHμG) systems where deviations are more likely to occur. In order to address these issues, this article develops a prominent dual-level "proportional-integral-one plus double derivative {PI−(1 + DD)} controller" as a new controller for frequency control (FC) of DHμG system. The proposed control approach has been tested in DHμG system that consists of wind, tide and biodiesel generators as well as hybrid plug-in electric vehicle and an electric heater. The performance of the modified controller is tested by comparing it with standard proportional-integral (PI) and classical PID (CPID) controllers considering two test scenarios. Further, a recently developed mine blast technique (MBA) is utilized to optimize the parameters of the newly designed {PI − (1 + DD)} controller. The controller's performance results are compared with cases where particle swarm optimization (PSO) and firefly (FF) techniques are used as benchmarks. The superiority of the MBA-{PI − (1 + DD)} controller in comparison to other two strategies is illustrated by comparing performance parameters such as maximum frequency overshoot, maximum frequency undershoot and stabilization time. The displayed comparative objective function (J) and JFOD index also shows the supremacy of the proposed controller. With this MBA optimized {PI − (1 + DD)} controller, frequency deviations can be kept within acceptable limits even with high renewable energy penetration. [ABSTRACT FROM AUTHOR]

Integration of information technologies with power systems has unlocked unprecedented opportunities in optimization and control fields. Increased data collection and monitoring enable control systems to have a better understanding of the pseudo-real-time condition of power systems. In this fashion, more accurate and effective decisions can be made. This is the key towards mitigating negative impacts of novel technologies such as renewables and electric vehicles and increasing their share in the overall generation portfolio. However, such extensive information exchange has created cybersecurity vulnerabilities in power systems that were not encountered before. It is imperative that these vulnerabilities are understood well, and proper mitigation techniques are implemented. This paper presents an extensive study of cybersecurity concerns in Smart grids in line with latest developments. Relevant standardization and mitigation efforts are discussed in detail and then the classification of different cyber-attacks in smart grid domain with special focus on false data injection (FDI) attack, due to its high impact on different operations. Different uses of this attack as well as developed detection models and methods are analysed. Finally, impacts on smart grid operation and current challenges are presented for future research directions. [ABSTRACT FROM AUTHOR]

Sustainable energy based hybrid microgrids are advantageous in meeting constantly increasing energy demands. Conversely, the intermittent nature of renewable sources represents the main challenge to achieving a reliable supply. Hence, load frequency regulation by adjusting the amount of power shared between subsystems is considered as a promising research field. Therefore, this paper presents a new stratagem for frequency regulation by developing a novel two stage integral-proportional-derivative with one plus integral (IPD-(1+I)) controller for multi sources islanded microgrid system (MS-IμGS). The proposed stratagem has been tested in an MS-IμGS comprising of a wind turbine, parabolic trough, biodiesel generators, solid-oxide fuel cell, and electric water heater. The proposed model under different scenarios is simulated in MATLAB environment considering the real-time recorded wind data. A recently developed sine-cosine algorithmic technique (SCA) has been leveraged for optimal regulation of frequency in the considered microgrid. To identify the supremacy of the proposed technique, comparative studies with other classical controllers with different optimization techniques have been performed. From the comparison, it is clearly evident that, SCA-(IPD-(1+I)) controller gives better performance over other considered stratagems in terms of various time domain specific parameters, such as peak deviations (overshoot, undershoot) and settling time. Finally, the robustness of the proposed stratagem is evaluated by conducting sensitivity analysis under ±30% parametric variations and +30% load demand. The lab tests results validate the operation of the proposed system and show that it can be used to regulate the frequency in stand-alone microgrids with a high penetration of renewable energy. [ABSTRACT FROM AUTHOR]

In the present era, electrical power system is evolving to an inverter-dominated system from a synchronous machine-based system, with the hybrid power systems (HPS) and renewable energy generators (REGs) increasing penetration. These inverters dominated HPS have no revolving body, therefore, diminishing the overall grid inertia. Such a low system inertia could create issues for HPS with REG (HPSREG) such as system instability and lack of resilience under disturbances. A control strategy, therefore, is required in order to manage this task besides benefitting from the full potential of the REGs. A virtual inertia control for an HPSREG system built with the principle of fractional order (FO) by incorporation of proportional-integral-derivative (PID) controller and fuzzy logic controller (FLC) has been projected. It is utilized by adding virtual inertia into HPSREG system control loop and referred to as FO based fuzzy PID controller for this study. Simulation outcomes states that the advocated FO based fuzzy PID controller has superior control in frequency of the system under frequent load variations. It has been noted that the proposed control scheme exhibits improved efficiency in maintaining specific reference frequency and power tracking as well as disturbance diminution than optimal classic and FO-based controller. It has been validated that, the developed controller effectively delivers preferred frequency and power provision to a low-inertia HPSREG system against high load demand perturbation. In the presented paper, analysis based on sensitivity has also been performed and it has been found that the HPSREG system's is not effected by system parameter and load variations. [ABSTRACT FROM AUTHOR]

Smart grid technology enables active participation of the consumers to reschedule their energy consumption through demand response (DR). The price-based program in demand response indirectly induces consumers to dynamically vary their energy use patterns following different electricity prices. In this paper, a real-time price (RTP)-based demand response scheme is proposed for thermostatically controllable loads (TCLs) that contribute to a large portion of residential loads, such as air conditioners, refrigerators and heaters. Wind turbine generator (WTG) systems, solar thermal power systems (STPSs), diesel engine generators (DEGs), fuel cells (FCs) and aqua electrolyzers (AEs) are employed in a hybrid microgrid system to investigate the contribution of price-based demand response (PBDR) in frequency control. Simulation results show that the load frequency control scheme with dynamic PBDR improves the system's stability and encourages economic operation of the system at both the consumer and generation level. Performance comparison of the genetic algorithm (GA) and salp swarm algorithm (SSA)-based controllers (proportional-integral (PI) or proportional integral derivative (PID)) is performed, and the hybrid energy system model with demand response shows the supremacy of SSA in terms of minimization of peak load and enhanced frequency stabilization of the system. [ABSTRACT FROM AUTHOR]

Reactive power management in microgrids with high penetration of distributed renewable energy sources (DRESs) is challenging. The intermittent generation of DRES makes the power management cumbersome. Generally, Flexible AC Transmission System (FACTS) devices such as Distribution Static Compensator (DSTATCOM) are employed for reactive power compensation in microgrids. However, for effective results in microgrids, coordinated operation between DSTATCOM and Distributed Energy Resources (DERs) is required. In this paper, IEC 61850 communication is proposed for realizing coordinated operation between microgrid controller (MGCC), DSTATCOM and DERs. In microgrids, there may be large number of DERs dispersed over a large area. Hence, the underlying communication network technology for IEC 61850 communication must be highly scalable with wide range. Recently developed communication technology Long Term Evolution (LTE) is a promising solution since it offers high data rates, reliability, scalability and longer range. In this paper, the developed IEC 61850 based reactive power management system is tested with the LTE technology and the performance evaluation tests have been performed. Firstly, IEC 61850 messages have been mapped on LTE stack to enable their transmission. Then, simulations over a network emulator have been performed to evaluate the performance of IEC 61850 communication message exchanges over LTE network in terms of End to End (ETE) delays. [ABSTRACT FROM AUTHOR]

During the past few decades, there has been significant growth in the renewable energy market because of increased concern over global warming and the continuous depletion of fossil fuel resources. There is a promising solar thermal technology that utilizes low-temperature heat to generate electricity. The conversion process of thermal energy to electricity is based on the principle of an organic Rankine cycle (ORC). This study investigated a novel islanded hybrid power system consisting of an ORC low temperature solar thermal system, wind (WTG), diesel generation (DEG) set, and combined application of an energy storage system (ESS), such as a battery (BESS), super magnetic energy storage (SMES), and an ultracapacitor (UC) unit. Furthermore, the hybrid system was employed with a single controller (one of proportional-integral (PI), PI with derivative (PID), two-degree-of-freedom (2DOF) PI, and 2DOF PID controllers) with proportionate gains to the DEG, and the ESS, which is another unique aspect of this work. Moreover, a comparative performance assessment of the flower pollination algorithm (FPA) to tune the PI, PID, 2DOF PI, and 2DOF PID controllers was carried out. Finally, the performance of the above hybrid system was compared with different ESS combinations, namely, (i) only BESS, (ii) BESS + UC, and (iii) BESS + SMES. The simulation results indicated that a renewable integrated isolated power system with BESS + SMES provided a better response than the other ESS combinations. In fact, the presence of comparative dynamic responses verified the superiority of an FPA-tuned 2DOF PID compared with other FPA-tuned controllers. [ABSTRACT FROM AUTHOR]

Striving for the suppression of greenhouse emissions, the modern power network is facing fundamental changes with the utilization of renewable energies (REs) for the future carbon-free society. The utilization of intermittent renewable-green power needs a better power management system and virtual power plant (VPP) can be a vital candidate that meets this demand. This study investigates a coordinated control grid integrated virtual power plant (VPP) in the presence of Central Receiver Solar Thermal System (CRSTS), Wind Turbine Generator (WTG), and Electric Vehicle (EV). To this end, CRSTS employed with thermal storage acts as a dispatchable renewable generating unit and coordinated control of the system units are achieved using the available control strategy on interconnected microgrids in the modified form, employing communication time delay. The proposed control strategy employs the proportional-integral (PI) and PI-derivative (PID) controller. Coordinated power control with real-time communication delay in grid integrated VPP in presence of CRSTS, WTG, and EV is a novel approach. Genetic algorithm (GA), Particle Swarm Optimization (PSO), Slap Swarm Algorithm (SSA), and recent Butterfly Optimization Algorithm (BOA) are used for tuning the necessary control parameters. The results establish the superiority of the BOA over SSA and PSO in suppressing system frequency deviations and tie line power deviation. The analysis of the dynamic response reveals that the consideration of the communication delay in the system expressively impedes the stable operation of the power system. [ABSTRACT FROM AUTHOR]

A renewable and distributed generation (DG)-enabled modern electrified power network with/without energy storage (ES) helps the progress of microgrid development. Frequency regulation is a significant scheme to improve the dynamic response quality of the microgrid under unknown disturbances. This paper established a maiden load frequency regulation of a wind-driven generator (WG), solar tower (ST), bio-diesel power generator (BDPG) and thermostatically controllable load (heat pump and refrigerator)-based, isolated, single-area microgrid system. Hence, intelligent control strategies are important for this issue. A newly developed butterfly algorithmic technique (BOA) is leveraged to tune the controllers' parameters. However, to attain a proper balance between net power generation and load power, a dual stage proportional-integral- one plus integral-derivative PI − (1 + ID) controller is developed. Comparative system responses (in MATLAB/SIMULINK software) for different scenarios under several controllers, such as a proportional-integral (PI), proportional-integral-derivative (PID) and PI − (1 + ID) controller tuned by particle swarm optimization (PSO), grasshopper algorithmic technique (GOA) and BOA, show the superiority of BOA in terms of minimizing the peak deviations and better frequency regulation of the system. Real recorded wind data are considered to authenticate the control approach. [ABSTRACT FROM AUTHOR]

Renewable energy has become very popular in recent years. The amount of renewable generation has increased in both grid-connected and stand-alone systems. This is because it can provide clean energy in a cost-effective and environmentally friendly fashion. Among all varieties, photovoltaic (PV) is the ultimate rising star. Integration of other technologies with solar is enhancing the efficiency and reliability of the system. In this paper a fuel cell–solar photovoltaic (FC-PV)-based hybrid energy system has been proposed to meet the electrical load demand of a small community center in India. The system is developed with PV panels, fuel cell, an electrolyzer and hydrogen storage tank. Detailed mathematical modeling of this system as well as its operation algorithm have been presented. Furthermore, cost optimization has been performed to determine ratings of PV and Hydrogen system components. The objective is to minimize the levelized cost of electricity (LCOE) of this standalone system. This optimization is performed in HOMER software as well as another tool using an artificial bee colony (ABC). The results obtained by both methods have been compared in terms of cost effectiveness. It is evident from the results that for a 68 MWh/yr of electricity demand is met by the 129 kW Solar PV, 15 kW Fuel cell along with a 34 kW electrolyzer and a 20 kg hydrogen tank with a LPSP of 0.053%. The LCOE is found to be in 0.228 $/kWh. Results also show that use of more sophisticated algorithms such as ABC yields more optimized solutions than package programs, such as HOMER. Finally, operational details for FC-PV hybrid system using IEC 61850 inter-operable communication is presented. IEC 61850 information models for FC, electrolyzer, hydrogen tank were developed and relevent IEC 61850 message exchanges for energy management in FC-PV hybrid system are demonstrated. [ABSTRACT FROM AUTHOR]

Due to environmental concerns, power system generation is shifting from traditional fossil-fuel resources to renewable energy such as wind, solar and geothermal. Some of these technologies are very location specific while others require high upfront costs. Photovoltaic (PV) generation has become the rising star of this pack, thanks to its versatility. It can be implemented with very little upfront costs, e.g., small solar home systems, or large solar power plants can be developed to generate MWs of power. In contrast with wind or tidal generation, PV can be deployed all around the globe, albeit with varying potentials. These merits have made PV the renewable energy technology with highest installed capacity around the globe. However, PV penetration into the grid comes with its drawbacks. The inverter-interfaced nature of the PV systems significantly impacts the power system operation from protection, power flow and stability perspectives. There must be strategies to mitigate these negative impacts so that PV penetration into the grid can continue. This paper gives a thorough overview of such strategies from different research fields: such as communication, artificial intelligence, power electronics and electric vehicle charging coordination. In addition, possible research directions are given for future work. [ABSTRACT FROM AUTHOR]

As the number of active components increase, distribution networks become harder to control. Microgrids are proposed to divide large networks into smaller, more manageable portions. The benefits of using microgrids are multiple; the cost of installation is significantly smaller and renewable energy-based generators can be utilized at a small scale. Due to the intermittent and time dependent nature of renewables, to ensure reliable and continuous supply of energy, it is imperative to create a system that has several generators and storage systems. The way to achieve this is through an energy management system (EMS) that can coordinate all these generators with a storage system. Prior to on-site installation, validation studies should be performed on such controllers. This work presents a standardized communication modeling based on IEC 61850 that is developed for a commercial microgrid controller. Using commercial software, different terminals are set up as intelligent electronic devices (IEDs) and the operation of the EMS is emulated with proper message exchanges. Considering that these messages transmit sensitive information, such as financial transactions or dispatch instructions, securing them against cyber-attacks is very important. Therefore; message integrity, node authentication, and confidentiality features are also implemented according to IEC 62351 guidelines. Real-message exchanges are captured with and without these security features to validate secure operation of standard communication solution. [ABSTRACT FROM AUTHOR]