This paper proposes a new model to mimics accurately the real dynamic and steady-state power generation profiles of a photovoltaic (PV) power plant connected to the power system. The model is targeted at load frequency control (LFC) studies, which takes into account the effect of the dynamic behavior of the system frequency on the PV output power. The artificial neural network using the radial bias function (ANN-RBF) is adopted to model the nonlinear behavior of the PV power plant only considering the frequency deviation as one of the inputs at different operating conditions. Also, the ANN prevents going into complex mathematical analysis to get the dynamic behavior of the output power from the PV plant. The input layer of the ANN-RBF receives the temperature, humidity, irradiation level, and frequency deviation, while the output layer represents the output power from the PV power plant. The main idea to include the frequency deviation in the PV modeling is to represent the dynamic behavior of the PV power that is injected by the PV inverter that is synchronized with the power system using the utility grid angle, i.e. system frequency. The ANN-RBF has been trained using actual data collected from a PV power plant in Aswan, Egypt. The ANN dataset contains significant variations of operating parameters to generalize the output modeling of the PV array. Moreover, the shortages in the previous models for the PV system used in the LFC studies, which are the first-order model, second-order model, and noise-based model, are discussed in detail. The simulation results show that the proposed model of the PV system based on the ANN-RBF is more suitable for the LFC studies than the well-known models based on the first-order representation as it takes into account the dynamic behavior of the system frequency during the load disturbance.

Like other multi-input multi-output (MIMO) systems, adverse effects of interactions among control loops on the system performance is one of the most challenging issues in the control of microgrids (MGs). In this paper, a robust MIMO controller is proposed for the MGs to solve the problem of power sharing among its distributed generators systematically. To this end, the relative gain array (RGA) matrix is used to address the problem of input-output pairing, and adverse effects of interactions among the control loops are decreased by designing proper pre-compensators. The sequential loop closing technique is employed, and the quantitative feedback theory (QFT) is used to achieve robust stability, the robust tracking performance, and the desired level of disturbance attenuation for all the control loops. The simulation and experimental results reveal the desirable and acceptable performance of the proposed control strategy.

Increasing the penetration level of distributed generation units as well as power electronic devices adds more complexity and variability to the dynamic behaviour of the microgrids. For such systems, studying the transient modelling and stability is essential. One of the major disadvantages of most studies on microgrid modelling is their excessive attention to the steady state period and the lack of attention to microgrid performance during the transient period. In most of the research works, the behaviour of different microgrid loads has not been studied. One of the mechanisms of power systems stability studies is the application of state space modelling. This paper presents a mathematical model for connected inverters in microgrid systems with many variations of operating conditions. Nonlineal tools, phase-plane trajectory analysis, and Lyapunov method were employed to evaluate the limits of small signal models. Based on the results of the present study, applying the model allows for the analysis of the system when subjected to a severe transient disturbance such as loss of large load or generation. Studying the transient stability of microgrid systems in the standalone utility grid is useful and necessary for improving the design of the microgrid’s architecture.

Active power control of the photovoltaic (PV) power generation system is a promising solution to regulate frequency fluctuation in a power system with high penetration of renewable energy. This paper proposes an autonomous active power control of a small-scale PV system for supporting the inertial response of synchronous generators and load-frequency control. In the proposed control approach, an effective grid frequency regulation scheme is realized using slow and fast frequency response characteristics. A low pass filter-based frequency measurement is used for slow frequency response characteristic, while direct frequency measurement is used for fast frequency response characteristic. The designed dual droop characteristics-based control is shaped to achieve a smooth transition between slow and fast response modes. The performance of the proposed control strategy is demonstrated for serious disturbance scenarios, i.e., considerable power-load imbalance and generation trip. In the load-power imbalance test scenario, the proposed control works properly within the normal frequency deviation region and even when the frequency deviation exceeds that region occasionally. In the generation trip test, the frequency deviation is mitigated quickly, and the employed droop control is smoothly transferred from the slow response mode to the fast response mode.

Increasing the penetration level of distributed generation units as well as power electronic devices adds more complexity and variability to the dynamic behavior of the microgrids. For such systems, studying the transient modelling and stability is essential. One of the major disadvantages of most studies on microgrid modelling is their excessive attention to the steady state period and the lack of attention to microgrid performance during the transient period. In most of the research works, the behavior of different microgrid loads has not been studied. One of the mechanisms of power systems stability studies is the application of state space modelling. These studies include the development of state space models of various components of the power system and then linearizing them around an equilibrium point. In this paper, a comprehensive method for modelling of islanded microgrid with dynamic and static loads is presented. The basic step of the proposed method is transformation to a dq0-based model. In order to find a complete and accurate model of islanded inverter-based microgrid, the sub-modules of generation, network and load must be modelled in local dq reference and then transferred to a common reference. The simulation results show the effectiveness of the proposed modelling approach for transient stability studies.

Increasing penetration of renewable energy sources based on power electronic interfaces in traditional power systems reduces the inertia constant and damping coefficient. It also increases uncertainty and the sensitivity of the system to disturbances. The concept of the virtual synchronous generator (VSG) is used to emulate the inertia constant and damping property like a synchronous generator. It can be shown that all given VSG structures have the same dynamics as the proportional-integral-derivative (PID) controller. In this paper, the quantitative feedback theory (QFT) is used to tune the VSG parameters such that robust system stability and performance are guaranteed. Moreover, the desired disturbance attenuation is also taken into account. Through frequency response analysis and time-domain simulations, it is shown that the proposed strategy can be successfully used to solve the load-frequency control problem in islanded microgrids (MGs). In addition, the proposed QFT-based VSG is compared with another robust VSG designed by the well-known H∞ technique to illustrate its better performance against disturbances.

To analyze the grid integration effect of a virtual synchronous generator (VSG), this paper proposes a simple power system modeling method. It is shown that for a specific disturbance, by simplifying the original network to a radical n generators single-load model, its state-space small-signal model can be obtained using a unified formula, as long as the single generator infinite bus model of each generator is given. Case studies based on the IEEE 9-bus test system as well as the New York New England test system show high efficiency of the proposed modeling to represent slow power and frequency deviations. Modal analyses give insight into how system poles are synthesized by individual generator poles, and how different designs of VSGs affect the system oscillation modes. Potential errors due to the topology simplification and the measures to avoid them are discussed. The time-domain results and modal analyses highlight some important features of VSG, which are overlooked in previous studies.

Using multiload wireless power transfer (WPT) systems to supply power to multiple receivers with a single transmitter is an interesting topic. However, previous studies are all based on a dc-dc WPT system. If the loads demand ac power, additional dc-ac inverters need to be implemented, which increases the system complexity and cost. This article addresses two direct ac WPT systems that can regulate the ac power of multiple phases or loads independently, using frequency modulation and amplitude modulation (AM), respectively. The proposed WPT systems can directly control the ac power of multiple loads through the transmitter side, without any power converter at the receiver side. A typical application of the proposed system is for powering a three-phase load in a rotational object, e.g., three-phase motors in articulated robots or in-wheel motors. To demonstrate the feasibility of the proposed WPT systems, simulation and experiment studies of a wireless three-phase power transfer are presented. The results suggest that AM is a more advantageous solution to a direct ac WPT system. A power-loss breakdown analysis is presented to suggest future steps of efficiency improvement.

Renewable energy sources, which are controllable under the management of the microgrids with the contribution of energy storage systems and smart inverters, can support power system frequency regulation along with traditionally frequency control providers. This issue will not be viable without a robust communication architecture that meets all communication specification requirements of frequency regulation, including latency, reliability, and security. Therefore, this paper focuses on providing a communication framework of interacting between the power grid management system and microgrid central controller. In this scenario, the microgrid control center is integrated into the utility grid as a frequency regulation supporter for the main grid. This communication structure emulates the information model of the IEC 61850 protocol to meet interoperability. By employing IoT’s transmission protocol data distribution services, the structure satisfies the communication requirements for interacting in the wide-area network. This paper represents an interoperable information model for the microgrid central controller and power system management sectors’ interactions based on the IEC 61850–8–2 standard. Furthermore, we evaluate our scenario by measuring the latency, reliability, and security performance of data distribution services on a real communication testbed

The concept of virtual inertia is adopted from the moment of inertia of synchronous generator (SG) rotating masses. The conventional power systems profit from the inertial function of numerous existing SGs to solve or improve the frequency challenges, e.g., low damping and high nadir due to the load/generation disturbances. However, the modern power systems are penetrated by a large number of the inertia-less power electronic–interfaced distributed energy resources (DERs). Hence, the rotational DER portion decreases impressively and the power system frequency experiences more intensive changes due to disturbances than the conventional SG-dominated power systems. In order to solve the low-inertia challenges of the power electronic–based power systems, the concept of virtual inertia is introduced, which is realized by applying a control function on the power electronic–interfaced DERs to mimic the SG inertial dynamics and provide the inertia, virtually. The main source of the virtual inertia is the short-term stored energy in the DC link of the DER power converters, which should be injected to the AC side according to the virtual inertia control objective. In fact, the DER power converters are controlled to surmount the low-inertia challenges including high-frequency nadir and high rate of change of frequency (RoCoF), low frequency/power oscillation damping, frequency instability, and severe changes triggering protection devices mistakenly.

Regarding the variability of renewable energy sources (RESs), especially in the operation time periods, their high penetration faces the net load pattern of the power system with a major ramp rate challenge. Although employing a market-based mechanism by the independent system operator (ISO) can address this challenge, it may not be possible to handle this challenge in all networks. In such networks, the required flexibility can be supplied through decreasing the ramp rate of the purchased power of distribution companies (Discos) from the market since their net load has an important impact on the system’s net load. Therefore, a flexibility-constrained operation problem for the distribution networks with distributed energy resources (DERs) and microgrids (MGs) is proposed in this paper to decrease the ramp-rate of the Disco’s purchased power from the market. This problem is formulated using a bi-level two-stage stochastic model where the problem of the Disco and the MGs are modeled as the upper-level and lower-level problems, respectively. The proposed model is applied to the IEEE 33-bus standard test network with three MGs. The results show the effectiveness of the proposed model to decrease the ramp-rate of the Disco’s purchased power from the market.

Growing the electrical and heat demand and increasing the need for the reliable and the cost-effective energy distribution systems facilitate using the multi-carrier energy distribution systems to supply demand. A multi-carrier energy network is a system that supports multiple types of energy carriers such as electricity, natural gas, and heat. This paper presents a new island-mode operation method for multi-carrier distribution systems where in case of the occurrence of a fault or critical event, the local network is disconnected from the main grid. This local network consisting of three energy hubs where the aim of these hubs is to supply their local energy demand with the minimum cost. For this purpose, the energy hubs decide to optimal scheduling of their resources and the optimal trading energy with other ones. To model such decision making framework, the Cournot competition model is employed in which the price of energy exchange among energy hubs is modeled based on the Time-Of-Use demand response program. This model is mathematically solved using Karush–Kuhn–Tucker conditions. For this purpose, these conditions are applied on the optimization problem of all hubs, simultaneously. To show the effectiveness of the model, it is applied on a test case with three hubs. The results show the optimal behavior of the hubs in such framework to minimize their operation cost.

A large share of greenhouse gases (GHGs) emissions is related to the transportation systems. These systems can be transformed into the clean transportation ones using the electric vehicles (EVs). Therefore, the power distribution grid (PDG) is required in the future sustainable cities to facilitate the integration of the EVs to these systems. In such systems, the operation problem of the power distribution grid operators (PDGOs) changes in the presence of electric vehicle parking lots (EVPLs). Although the different models are proposed for the operation problem of the PDGOs and parking lot (PL) owners (PLOs), the interaction among the PLOs in also needs new decision-making framework. Therefore, in this paper, an appropriate energy management model for the EVPL community is presented for the operational scheduling of several PLs which they trade energy with each other besides energy exchange with the PDGO to maximize their profits. This model is a mixed-integer linear programming (MILP) problem which is solved by stochastic programming and using a simple additive weighting (SAW) method. The model also compares with two common models consisting of: 1) the PLO only purchases energy from PDGO, and 2) the PLO purchases/sells energy from/to the PDGO. The results show that in the proposed model in this paper the PLOs gain more profit in comparison with the common models. The profit depends on EVs’ uncertainties and several factors that is investigated through the sensitivity analysis.

The problem of energy management in the smart autonomous electrical grids (SAEGs) is a main challenge in the active distribution networks. In such systems, the operator of the network decides on the optimal scheduling of the resources to supply the local demand. In this paper, a multi-objective optimization model is developed for a SAEG considering responsive consumers (RCs) and a hydrogen storage system (HSS). The objective functions are maximizing the reliability and minimizing both the operation cost and the gap between the energy consumption and its optimal value. The participation of the RCs is modeled through the demand shifting strategy and the local generation of the plug-in electric vehicles. To model the uncertainties of the renewable energy sources and the demand, the Monte Carlo simulation approach is used. The resulted model is solved using the shuffled frog leaping algorithm (SFLA) regarding which the non-dominated solutions are generated. Then, the best solution is obtained using the fuzzy and the weighted sum methods. To investigate the effectiveness of the proposed model, it is applied on a 24-node test system through defining four case studies. The results shown that in the presence of the RCs and the HSS, the operation cost and the reliability of the system both improve.

Supplying the electrical energy demand of the industrial areas through the microgrid (MG) structure can increase the sustainable development indices in the electrical energy systems. Some of the MG’s load is met through renewable energy sources (RESs) regarding which the pollution emission of the system decreases. Also, the MG operator (MGO) can decrease the operation cost of the system using the optimal scheduling of the electrical energy storages (EESs) and the shiftable loads. In the end, since there are several energy resources in the MG, the MGO can meet the MG’s demand with a minimum amount of the energy not supplied (ENS). In this paper, a tri-objective function optimization model is developed for the energy management problem of an MG to minimize the operation cost, the pollution emission, and the ENS. The weighted goal programming approach is used to transform the proposed tri-objective function into a mixed-integer linear programming (MILP) model which can be solved through the CPLEX solver. To investigate the effectiveness of the proposed model and its solution approach, it is applied to an industrial MG. The results show that the MGO makes optimal decisions to schedule the MG’s resources.

This chapter aims to study the distribution expansion planning (DEP) problem considering flexibility providers. In this study, demand response providers (DRPs) are introduced as the flexibility service providers, which will play an important role besides other independent entities to satisfy the increasing electrical demand. Moreover, there are different autonomous entities with different behaviors in distribution systems whose behaviors should be modeled. It means several independent entities are playing their roles in the distribution systems with their objectives (that may conflict with the objectives of other players), while they can have interoperability with each other. Hence, an efficient modeling architecture is essential to optimally model such interactions. In this chapter, a system-of-systems (SoS) approach is proposed as an efficient framework to model the behavior of these independent entities. The SoS is an approach for modeling the collaboration of different entities with distinct objective functions, which are able to cooperate. Independent systems under the SoS framework aim at achieving their own goals. The outcome of the SoS is an optimum solution that will determine the strategies of all the entities in an optimal manner.

The important role of electricity generation in the power system is evident and is growing more and more with innovative technologies and requirements. Hence, addressing the combined heat and power economic dispatch (CHPED) as one of the relatively new issues in the power system operation and control is more importance. Since the CHPED problem is a non-smooth, highly non-linear, and non-convex one, it is required to solve it so that an optimal global solution can be achieved. In this paper, by applying the piece-wise linearization approach the CHPED problem is solved so that the problem reformulated to a quadratic optimization problem with linear and quadratic constraints. To demonstrate the applicability of the proposed model, four case studies are implemented in the GAMS software environment and the results compared to the literature

The small size of isolated microgrids (IMGs), high intermittency and fluctuations of renewable generations, and low inertia of distributed energy resources make the frequency an important factor in the operation of IMGs that should be managed considering technical and economic constraints. The fast response time and long lifecycle of vanadium redox flow batteries (VRFBs) make them a promising candidate for energy and frequency management of IMGs. Accordingly, this paper proposes a novel energy management system (EMS) for IMGs which aims to optimize energy and reserve scheduling of VRFBs in coordination with droop controlled distributed generators. The objective of the EMS is to minimize the total operation cost of the IMG while dynamic and static frequency securities are preserved. In the proposed EMS, the hierarchical control structure of IMGs is precisely formulated and the VRFB is incorporated in the EMS to provide both energy and reserve in primary and secondary control levels. Moreover, to get accurate results, the nonlinear characteristics of VRFBs are considered in the developed model and linearized by an efficient approach. The proposed EMS is formulated as a two-stage stochastic mixed-integer linear programming problem (MILP) that guarantees the global optimal solution. Case studies on a test IMG indicate that optimal coordination of VRFBs in energy and reserve scheduling can reduce the operation cost more than 11.67%.

This chapter focuses on the distribution network emergency operation in the presence of flexible resources and the microgrid concept. The concept of flexibility at the distribution level, the occurrence of emergency, and general approaches for enhancing the flexibility are reviewed in this chapter. The configuration of the microgrids including basic roles and strategies applied by microgrids for enhancing the flexibility of the distribution networks in single, networked, and multi-energy system frameworks, the flexibility of the communication system, and the decision-making framework in the presence of the microgrids are investigated in detail. Furthermore, the islanding strategies and demand response programs are also presented for emergency operation as the local emergency resources. Various mobile and stationary power generation sources including mobile emergency generators, mobile energy storage systems, battery energy storage system, and plug-in electric vehicles, and their impacts on the distribution networks flexibility during emergency operation are evaluated. Besides, the emergency power dispatch and balancing, and the restoration strategies are presented to comprehensively investigate the operating conditions in the emergencies. Then, the IEC-61850-based energy management system during emergencies is analyzed as a communication standard at the distribution level.

As an inevitable issue, voltage unbalancing can have some adverse effects on the power systems equipment. This paper investigates a double synchronous reference frame-based control method to compensate unbalanced voltage, helping to properly active and reactive power-sharing. This approach controls the positive and negative components of the voltage separately, which can be implemented in the primary and secondary control levels of islanded AC microgrids. The secondary control is based on the dynamic consensus algorithm that helps restore deviated voltage and frequency induced by the primary control, but it also improves the proposed control scheme performance. The proposed control strategy’s effectiveness is investigated based on some simulations in the MATLAB Sim/Powersystem environment.

In this paper, an individualized intelligent multiple-model technique is proposed to design automatic artificial pancreas (AP) systems for the glycemic regulation of type 1 diabetic patients. At first, using the multiple-model concept, the insulin-glucose regulatory system is mathematically identified by constructing some local models. In this step, trade-offs between the number of local models and the complexity of the overall closed-loop system are made by defining and solving a bi-objective optimization problem. Then, optimal AP systems are designed by tuning a bank of proportionalintegralderivative (PID) controllers via the genetic algorithm (GA). A fuzzy gain scheduling strategy is employed to determine the participation percentages of the PID controllers in the control action. Finally, two safety mechanisms, called insulin on board (IOB) constraint and pump shut-off, are installed in the AP systems to enhance their performance. To assess the proposed AP systems, in silico experiments are performed on virtual patients of the UVA/Padova metabolic simulator. The obtained results reveal that the proposed intelligent multiple-model methodology leads to AP systems with limited hyperglycemia and no severe hypoglycemia.

One of the major challenges in the real-time control of structures is the uncertainty in identifying the mechanical properties of the system, including mass, stiffness, and damping. However, the presence of uncertainty in time-varying systems (under severe environmental factors, the dynamic characteristics of the system change due to damage) is more noticeable. In this article, to deal with the problem of parametric uncertainties in seismic motion control of structures, an adaptive optimal controller is applied. The design procedure of the controller is straightforward, and there is no need to have the values of the structural parameters. In the proposed scheme, only the states of the system are measured, and it is not necessary to use the ground acceleration data which are difficult to be measured in real time. It is shown that the performance of the designed controller converges to the well-known linear quadratic regulator. Simulation results reveal that considerable reductions of the dynamic responses during the earthquakes are achieved using the utilized adaptive optimal controller, and also it is robust against any variation in the structural parameters due to the damages.

The small-signal stability of large-scale interconnected microgrids needs to be analyzed to find the most dominant dynamic behaviors. In this paper, a comprehensive and easy-expandable module-based modeling method is proposed, which is expandable to many interconnected AC microgrids through circuit breakers, i.e. synchronous microgrids. Another certain requirement is validating such a large model, which is satisfied using a well-known Prony analysis method. The large-scale interconnected AC microgrids are implemented in a real-time digital simulator to provide input waveforms for the Prony analysis. On the other hand, the dynamic modes of the proposed model are calculated by eigenvalue analysis, and their contributions in each state variable are identified using the participation matrix. In the proposed validation method, the participating modes in each state variable are compared with the natural frequencies of its estimated waveform by Prony analysis. It is concluded that there is a good matching between the participating modes in the state variables and the contributing frequencies in their waveforms that verifies the proposed modeling method.

In this article, a decentralized scalable voltage control approach for islanded dc microgrids with a general structure is proposed. The microgrid system under study comprises several distributed generation (DG) units, every one containing an uncertain local ZIP [constant impedance (Z), constant current (I), and constant power (P)] load. We propose a voltage control strategy that ensures robust desired performance of the closed-loop islanded dc microgrid in addition to the robust stability under different uncertainty sources, including uncertain ZIP loads, topological changes, and plug-and-play functionality of DGs. The presented approach does not impose any restrictions on the dynamics of the distribution lines connecting different DG units. In the proposed control scheme, each local controller is the solution of a single convex optimization problem, which leads to the optimal performance of the dc microgrid. At first, an LTI state-space model with polytopic uncertainty is developed for islanded dc microgrid with different uncertainty sources. Then, a robust dynamic output-feedback-based controller with HH∞ performance criterion is proposed for the satisfaction of all control objectives. The final obtained problem is turned into an LMI-based optimization problem. Different scenarios are simulated in MATLAB to affirm the feasibility and efficiency of the proposed control technique in the dc microgrids.

In this paper, a virtual inertia control strategy based on linear feedback is presented that improves dynamic behavior of islanded dc microgrids interfaced with constant power loads (CPLs). In order to solve the stability challenges caused by low inertia and CPLs, the proposed control scheme is composed of a virtual capacitor and a virtual conductance. It is implemented in the inner loop control, i.e. current loop control to be fast enough emulating inertia and damping concept. In addition, the droop characteristic is modeled by using the virtual resistance which adjusts the steady-state response of the system. In this study a multi-level structure is considered, which comprises the source level, interface converter level, and common load level. In addition, an accurate small-signal model is used to investigate the stability of dc MG interlaced with CPLs, and then, an acceptable range of inertia response parameters is determined by using the root locus analysis. Performance of the proposed control structure is demonstrated through numerical simulations.

In this work, we study the bulk refractive index (RI) sensitivity  and intrinsic limit of detection  of a micro racetrack resonator (MRR) based RI-sensor. Sensing measurements are performed with solutions of sodium chloride (NaCl)-water. The sensing device includes an array of multiple silicon-oxy-nitride (SiON) MRRs, fibre-coupled to a vertical-cavity surface-emitting laser (VCSEL) operating at 850 nm. We particularly choose 850 nm for sensing measurement, since the water absorption coefficient at this wavelength is three orders of magnitude lower than at 1550 nm (another conventional wavelength in biosensing). Different concentrations of NaCl–water solutions (spanning from 0.0% to 1.8% weight/weight), are flowed on top of the MRR surface in the cladding layer. Measuring of whispering gallery mode (WGM) resonance wavelength shifts in NaCl–water solutions, confirming a and of 31.66 nm/RIU and RIU, respectively. Furthermore, with exact engineering of the physical parameters of the system, the best and of 325.85 nm/RIU and RIU are found, respectively. The parameter delineates the minimum amount of RI or correspondingly minimum concentration of a biological solution, which can be detected by a RI-sensor. In this regard, this device can find applications in the exact measurement of NaCl in real biological sample solutions.

A detailed investigation of the performance of four-wave mixing (FWM) in non-flared- and flared-waveguide semiconductor optical amplifiers (FW-SOAs) has been reported. A standard rate equation model has been used which considers the effect of the distribution of carrier density of the transverse direction based on numerical calculation along with the nonlinear Schrödinger equation (NSE). The results have been reported in saturated and unsaturated states of the FW-SOAs. Features of the FWM pulse, such as peak pulse deviation, pulse width, and pulse energy along the length of the SOA cavity have been studied and compared in detail for three waveguide geometrics (non-flared, linearly flared, and exponentially flared). Evolution in time and spectral domain of the FWM pulse has been shown for three different structures. It has been found that the FW-SOAs perform better under saturated regime since the FWM pulse has less distortion compared to the non-flared SOA. In an FW-SOA, pulse-width variations of the FWM pulse are almost insignificant whereas in the non-flared SOA, the FWM pulse suffers from broadening.

In this work, we present an ultra-high sensitivity (S) refractive index (RI) sensor for biological applications. Silicon on insulator (SOI) ring resonator (RR) based RI sensors have been extensively investigated. Light propagation is studied in the small SOI RRs based on sub-wavelength grating (SWG) waveguides with aqueous claddings. For the device analysis, the two-dimensional conformal transformation method is jointly used with the effective index method. Furthermore, FEM simulations of this structure have been also performed in both the air and water claddings. These good-matched results are further compared with experimental and FDTD results in other valid references. Having found a high data matching between our results and experimental results, we repeat our calculation for different side-widths (d=150-225 nm) and ring radii (7-10 µm). For each ring radius, the best amount of side-width is found. Then bulk refractive index sensing experiments are simulated using changing cladding RI in the range of nc=1.332-1.350 RIU. These RI changes correspond to concertation changes of glucose-water solutions in the cladding. Finally, we obtain the highest sensitivity of 24946 nm/RIU in the case of a radius 7 µm, 500 nm width, 220 nm height, 150 nm side-width, and T of 50 nm between the grating arrays on the RR. It is worth noting that this proposed structure shows 150 times sensitivity enhancement compared to a standard SOI RR-based biosensor with the same radius, w, and h. In addition, the RI sensor suggested in this work shows ultra-high sensitivity in a dynamic range of 1.332-1.352 RIU. This range of RI variation covers almost all the RI variations of the blood components. These results show excellent potential for employing the proposed SOI RR based on SWG waveguides in a liquid-biopsy analysis of patients with cancer. These might pave the way toward the early detection of cancers.

A decentralized voltage control scheme to achieve robust stability and robust performance of islanded direct current (DC) microgrids is presented in this paper. The investigated microgrid consists of multiple distributed generation (DG) units with a general topology, each one comprising a local uncertain ZIP (constant impedance (Z), constant current (I), and constant power (P)) load. The proposed controller confers the following main advantages: 1) the design procedure is scalable, 2) it has a completely decentralized structure, 3) it prepares stability and desirable performance of the nominal closed-loop microgrid, 4) it preserves robust stability as well as robust performance of microgrid system under different sources of uncertainty, including plug-and-play (PnP) functionalities of DGs, microgrid topology changes, uncertain ZIP load, and unmodeled load dynamics, 5) every local controller is the solution of a unique convex optimization problem, resulting in the optimal performance and robustness to several different successive changes. First, a linear time-invariant (LTI) state-space model is developed for each DG subsystem with capturing disturbances, and different uncertainty sources are modeled as a new single polytope. Then, all control objectives are converted into a robust dynamic output-feedback-based controller for an LTI polytopic system with H∞

The coordination between distribution system and transmission system operation in the presence of distributed energy resources (DERs) is a new framework that needs appropriate modeling. Moreover, local energy market models are emerging, and there is the need to describe the decision-making occurring in active distribution systems including the distribution company (Disco) and the DER aggregators. This paper investigates the coordination between transmission, distribution, and DER aggregators that interact in a local market model. The individual objectives of the decision-makers are conflicting with each other. For this purpose, a bi-level optimization approach is proposed, in which the operation problem of the Disco and the day-ahead market clearing managed by the wholesale market operator are considered as the upper- and lower-levels problems, respectively. Moreover, to model the uncertainties of output power of renewable energy sources in the Disco’s problem, the information gap decision theory is used. The resulting model is a non-linear bi-level problem, which is transformed into a linear single-level one through the exploitation of the Karush-Kuhn-Tucker conditions and the duality theory. To investigate the effectiveness of the model, two case studies are defined in which the IEEE 33- bus and a real 43-bus distribution systems are connected to the RTS 24-bus power system.