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In this paper, a day-ahead profit-maximizing energy management scheme for a grid-tied microgrid operation is proposed. The microgrid contains various types of distributed energy resources (DERs) and an inverter-interfaced battery-bank storage system. The average of day-ahead hourly forecasted data for loads, wind speed, and solar radiation are inputted into the framework of energy management (EMF). To optimize the microgrid performance, EMF determines the hourly dispatch of reactive and active power for each DER. Also, it specifies the discharging and charging times of the energy storage system and the onload tap changer position setting of the transformer connected to the main grid. The main aim is to maximize the revenue of microgrid meeting all technical limitations. The main grid can sell/buy reactive and active powers to/from the microgrid with a variable daily energy price of the market. A collective rule base-BAT algorithm is implemented as a solver of the energy management optimization problem for a grid-tided microgrid. Furthermore, the ability of the suggested EMF is proved in comparison with recent approaches.

A mechanism to demodulate a two-tone high-frequency oscillation in nonlinear electronic devices due to an external electromagnetic field is investigated. The results of a demodulation are low-frequency disturbances to the internal circuits of electronic devices. A method for the synthesis of nonlinear compensators on the basis of the operational equations of electronic devices is offered for protection against low-frequency noise. The nonlinear operator of the compensator is designed so that a cascade connection of the electronic device and the compensator is described by the linear Volterra functional. As an example, the compensation of nonlinear transformations of a detector at high-frequency oscillation is synthesized with the use of results of measurements. The accuracy of the executed compensation is estimated. Index Terms--Low-frequency noise, nonlinear compensation, nonlinear operator, Volterra polynomial.

The paper treats an inverse problem posed in the time domain for a circuit described by a stiff system of ordinary differential equations (ODEs). Identification of model parameters (circuit elements) is performed by processing transient characteristics measured in the circuit. An illustrative example discussed throughout the paper shows that reducing the identification problem to curve fitting, which is the most general way, may be hardly used for a stiff model due to a ravine shape of the objective functional. Moreover, a necessity of solving the stiff ODE system to get a functional value makes the inverse problem be practically unsolvable. It has been shown that the initial inverse problem may be simplified significantly by taking into account linear relations which are observed between the experimental characteristics measured for a stiff system. The relation coefficients are discussed in the paper with regard to the accuracy of the approximation. Finally the initial identification problem has been reduced to a nonlinear system of algebraic equations which may be easily solved considering different sensitivity of the relation coefficients to the model parameters. The final solution is presented for different levels of 'measurement' error involved in the simulation. Index Terms--Analog circuit fault diagnosis, analog circuit identification, ill-conditioned matrix, stiff problem.

A new method of deembedding a test fixture effect from the data of microwave measurements is presented in this paper. It is shown that the traditional unterminating problem (the problem of finding fixture characteristics) being posed in a finite frequency range may be reduced to a problem of fitting the characteristics of the 'thru' experiment. The latter is proposed to be solved by using the genetic algorithm (GA). A special trick is suggested to take fixture power loss into consideration, which is sometimes necessary to increase the goodness of fitting the characteristics. Physically correct constraints for optimization variables and optimal parameters of the GA are discussed in this paper. The method is applicable for all microwave fixtures, except for those whose characteristics are influenced by the relative position of the adapters comprising the fixture. The method does not have any specific frequency limitation and does not require any calibration standards. The results of the experiments performed have validated a high efficiency of the method proposed, and confirm that the accuracy of a deembedding problem solution is close to the goodness of fitting data of the 'thru' experiment. Index Terms--Calibration, deembedding, genetic algorithm (GA), microwave network analyzer (NA), scattering-parameter measurement, test fixture.

This paper treats the problem of identification of a linear electric circuit described by an ill-conditioned mathematical model. The identification problem is considered as the problem of model parameters determination by means of processing experimental data measured for the objective circuit. Topological singularities (low-admittance cutsets and low-impedance loops) in a circuit are found to be origins of ill-conditionality of a circuit model. For more in-depth investigation the classification of electric circuits is made in respect to singularities position. It is shown that the first set of experimental data obtained for an ill-conditioned model is useless for getting the required solution of the identification problem. In this case a solution error amounts to a huge value that exponentially increases with growth in condition number of a model matrix. It is found that linear relations between model parameters can be determined in an ill-conditioned problem. Accuracy of these relations does not depend on condition number, but is defined only by measurement precision. An approach named as repeat measurements principle (RMP) and based on linear relations is suggested to solve an ill-conditioned identification problem. A new RMP-based algorithm of linear circuit identification is developed. The algorithm shows a high efficiency and allows us to determine model parameters accurate to measurement precision as applied to any type of reciprocal and nonreciprocal linear circuits. Index Terms--Analog circuit fault diagnosis, analog circuit identification, ill-conditioned matrix, singular cutset, singular loop, stiff problem.

This paper presents the application of Flexible Alternating Current Transmission System (FACTS) devices based on heuristic algorithms in power systems. The work proposes the Autonomous Groups Particle Swarm Optimization (AGPSO) approach for the optimal placement and sizing of the Static Var Compensator (SVC) to minimize the total active power losses in transmission lines. A comparative study is conducted with other heuristic optimization algorithms such as Particle Swarm Optimization (PSO), Timevarying Acceleration Coefficients PSO (TACPSO), Improved PSO (IPSO), Modified PSO (MPSO), and Moth-Flam Optimization (MFO) algorithms to confirm the efficacy of the proposed algorithm. Computer simulations have been carried out on MATLAB with the MATPOWER additional package to evaluate the performance of the AGPSO algorithm on the IEEE 14 and 30 bus systems. The simulation results show that the proposed algorithm offers the best performance among all algorithms with the lowest active power losses and the highest convergence rate. [ABSTRACT FROM AUTHOR]