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With increasing wind farms scale, the practical problems become more complicated. One of the prominent problems is over-voltage production due to frequent switching activity. The over-voltage cruelty mainly depends on the wind farm topology, defined for an arrangement of the wind farm feeders between the turbines. In this paper, the switching over-voltages in different wind farm topologies are presented by simulating ZAAFRANA wind farm in Egypt with the support of DIGSILENT. First, the four different topologies named radial, single-sided ring, double-sided ring, and star, are examined by measuring the generated over-voltages. Finally, based on the more accurate and comprehensive analysis of the over-voltage produced by the four topologies, an effective methodology is proposed for reducing the amount of the over-voltage peaks, in the low-cost radial topology, by splitting the switching process into two stages. The proposed methodology is applied to ZAAFRANA wind farm and found that the destructive effects are reduced remarkably.

Mathematical design of a new fourth-order harmonic passive filter is presented and its optimal strategy is proposed with regards to various design scenarios. The considered objective function is total demand distortion minimization of the supply current. The crow spiral-based search algorithm (CSSA) is applied to solve the design problem formulated. This CSSA relies on a spiral search mechanism that improves the convergence and balances the exploration and exploitation abilities of the conventional crow search algorithm. Various power quality indices are taken into consideration like the individual and total harmonic voltage distortion values, individual and total current harmonic distortion values, active power loss, actual and displacement power factor percentages, and resonance damping capabilities. These indices were handled as non-linear constraints in the design. Additionally, a comparative investigation of the different damped filters is presented to assess the planned filter performance. The results obtained confirm the success of the filter design proposed in this paper.

The insecticidal efficacy of various baculovirus formulations against the cutworm Agrotis ipsilon was determined. The treatments consisted of molasses from suagrcane mixing with each of wheat germ, biochar, talc, chitosan, silica gel, pyrolysis bio-oilaqueous phase, pyrolysis bio-oilorganic phase, calcium carbonate, cornflour, calcium cassinate, aluminium potasium sulphate, Diatomaceous earth, dextrin, lignin PC 1307, soy screen, blankphor, skim milk powder, potassium cassinate, magnsium chloride, date molasses and pregelatinized starch. All applied in spray-dried at 2.2 x 109 occlusion body(OB) mL-1. The bioassay of each spray-dried formulation using the droplet feeding method by the blue solution containing 2% sugar and 0.1% blue dye. The resulting suspensions should all contain 0.377 x 106 OB mL-1, represent the LD70 for the unformulated virus. Exposure newly hatched larvae of cutwormsand transfer to individual diet cups for each treatment and incubated at 28oC in dark incubator for 7 days. The obtained results revealed that satisfactory control of the pest of 100% larval mortality compared to untreated control was achieved with the formulations containing molasses mixing with talc, silica gel, calcium carbonate, cornflour, calcium cassinate, diatomaceous earch, soy screen, and dextrin. However, the formulations containing chitosan, pyrolysis bio-oilaqueous phase and pyrolysis bio-oilorganic phase gave the lowest mortalities as 12.2, 11.1 and 6.7%, respectively. These findings is an attempt to provides an interesting alternative developed biopesticide formulations made with natural ingredients that could improve the efficacy and persistence of virus-based biopesticides.

Today, generation and transmission expansion planning (G&amp, TEP) to meet potential load growth is restricted by reliability constraints and the presence of uncertainties. This study proposes the reliability constrained planning method for integrated renewable energy sources and transmission expansion considering fault current limiter (FCL) placement and sizing and N-1 security. Moreover, an approach for dealing with uncertain events is adopted. The proposed planning model translates into a mixed-integer non-linear programming model, which is complex and not easy to solve. The problem was formulated as a tri-level problem, and a hybridization framework between meta-heuristic and mathematical optimization algorithms was introduced to avoid linearization errors and simplify the solution. For this reason, three meta-heuristic techniques were tested. The proposed methodology was conducted on the Egyptian West Delta system. The numerical results demonstrated the efficiency of integrating G&amp, TEP and FCL allocation issues in improving power system reliability. Furthermore, the effectiveness of the hybridization algorithm in solving the suggested problem was validated by comparison with other optimization algorithms.

When a large power transformer is energized, a high magnitude inrush current may result in harmonic resonance overvoltage (HRO), if the system has resonance phenomenon. Such overvoltages may cause large stresses on the system. This paper investigates the energization of two winding 220/22 kV main power transformer in a weak system of a grid-connected wind farm. To achieve this aim, the produced HRO during the energization of the main power transformers and the affecting factors are investigated. In addition, the effect of the sympathetic inrush phenomena is studied. Finally, the sequential energization of the three-phase transformer and the pre-insertion resistor method are discussed as mitigation methods. The investigated scenarios and results will contribute in developing the power system restoration procedures for existent wind farm, its extension, and future-planned wind farms. Keywords: Grid-connected wind farms, Harmonic resonance overvoltage, Pre-insertion resistor, Sequential energization of transformers

The rapid increase in the use of nonlinear loads that inject harmonics into electrical distribution systems causes many power quality problems. A practical method to mitigate harmonic distortion and improve the system's technical performance is optimal capacitor allocation. This method aims to get the best value of installed shunt capacitors and also the best location of them while putting the financial aspect into consideration. To accurately optimize these shunt capacitors' size and location, achieving the minimum annual cost and considering IEEE Std. 519™-2014 constraints in distorted systems, optimization problem formulation, is needed. In the literature, many studies discussed this problem. However, most of them formulated their optimization technique based on the fundamental load flow while assuming that the distribution system's loads are operating at sinusoidal conditions, leading to inaccurate analysis of the system and erroneous actions. In this paper, the decoupled harmonic power flow approach (DHPF) is considered the base of the optimization problem, in which the so-called sine-cosine algorithm (SCA) is employed in this work on an 18-bus system working at non-sinusoidal conditions. The results obtained have been compared to obtained results by other optimization techniques to verify the algorithm's effectiveness.

This paper introduces a multi-stage dynamic transmission network expansion planning (MSDTNEP) model considering the N-1 reliability constraint. The integrated planning problem of N-1 security and transmission expansion planning is essential because a single line outage could be a triggering event to rolling blackouts. Two suggested scenarios were developed to obtain the optimal configuration of the Egyptian West Delta Network’s realistic transmission (WDN) to meet the demand of the potential load growth and ensure the system reliability up to the year 2040. The size of a blackout, based on the amount of expected energy not supplied, was calculated to evaluate both scenarios. The load forecasting (up to 2040) was obtained based on an adaptive neuro-fuzzy inference system because it gives excellent results compared to conventional methods. The linear population size reduction—Success-History-based Differential Evolution with semi-parameter adaptation (LSHADE-SPA) hybrid—covariance matrix adaptation evolution strategy (CMA-ES) algorithm (LSHADE-SPACMA)—is applied to solve the problem. The semi-adaptive nature of LSHADE-SPACMA and the hybridization between LSHADE and CMA-ES are able to solve complex optimization problems. The performance of LSHADE-SPACMA in solving the problem is compared to other well-established methods using three testing systems to validate its superiority. Then, the MSDTNEP of the Egyptian West Delta Network is presented, and the numerical results of the two scenarios are compared to obtain an economic plan and avoid a partial or total blackout.

Damping the oscillations of the wind energy conversion system of a grid connected Doubly Fed Induction Generator (DFIG) is the main objective in this article. PID controller is commonly used in many industrial process, but its parameter tuning is a challenging task. The PID parameters values are not optimally adjusted by conventional methods being used such as frequency response. Such that, a new algorithm is used which is hybrid Differential Evolution with Linearized Biogeography-Based optimization (LBBO-DE). Linearized-Biogeography Based optimization (LBBO) is a new version of Biogeography-Based optimization (BBO). Cauchy and Gaussian mutation operators are proposed to modify the mutation equation. The algorithm LBBO-DE with the proposed mutation operators had been tested with 53 benchmarks and then compared with the 40 algorithms that have been accepted for 2005 and 2011 Congress on Evolutionary Computation (CEC). The proposed algorithm achieved advanced rank between them and gave better results and lower variance, which proved to have competitive performance with state-of-the-art evolutionary algorithms. A simulation model is used to show the oscillation damping in case of symmetrical and asymmetrical fault occurrence at the grid connected to WECS-DFIG. As a result, the LBBO-DE with Gaussian mutation equation is used to optimize the controller parameters for achieving oscillations damping. The simulation results of direct-drive PMSG model is also used for the oscillations damping purpose under the case of wind speed variation, which is done by the LBBO-DE.

In this paper, an enhanced directional overcurrent relays (DOCRs) coordination scheme is introduced. The proposed scheme considers the fault severity by applying weighting factors, calculated based on system fault currents at different locations in each relay zone of protection. This enhanced coordination reduces the operating time of the relays for severe fault currents avoiding the greater thermal and mechanical stresses that reduce equipment lifetime. The DOCRs coordination problem is formulated as a multi-objective optimization problem to accomplish better results than the single-objective methodology with respect to relays selectivity and speed. DOCRs coordination problem is solved using Goal Attainment method in MATLAB optimization Toolbox.A two-fault point coordination scheme is applied to IEEE 14 bus system for both the conventional and the proposed scheme. The results are analyzed according to several system performance indices including: the mean of the system’s relays operating times, the maximum primary relay operating time, the maximum backup relay operating time and maximum coordination time interval (CTl) between primary/backup pairs. The achieved results indicated that the proposed scheme considering the severity weighting factors has reduced the mean operating time of relays especially for the relays with faults with high severity. It means more reliable, faster protection system with less thermal and mechanical stresses for system equipment.

This chapter presents a complete design of maximum power point tracking control scheme applied to single-phase single-stage and two-stage grid-connected PV systems based on an adaptive fuzzy controller (AFLC). This technique is proposed to enhance the efficiency of a photovoltaic (PV) array and diminish the output power oscillations. The adaptive nature of the proposed controller provides online tuning of fuzzy rules parameters to deal with varying sun radiation and ambient temperature. Ranges of input variables of fuzzy system are defined using genetic algorithm. The adaptive MPPT controller is compared with existing setups, namely the “incremental conductance” (IC) technique and fuzzy logic controller (FLC). The inverter controller is designed in the synchronous frame so that a simplified controller such as PI-controller is implemented. Simulation and experimental results demonstrate the supremacy of the adaptive technique in terms of the speed of tracking and oscillations reduction around the maximum point of power–voltage (P–V) curve.

In this paper, a comparative study of single-objective and multi-objective optimization approaches for directional overcurrent relays (DOCRs) coordination is presented. Single-objective optimization approach is investigated using two methods; the fmincon function which is the gradient-based method, while the second method is the Genetic Algorithm which is a meta-heuristic technique. Multi-objective optimization approach is investigated using fmincon function and Goal Attainment method. All the methods are available in the MATLAB optimization Toolbox. Different fault locations on the meshed power distribution network of the IEEE 14 bus system are considered for the investigated methods. The results of single-objective and multi-objective approaches are compared regarding total relays operating times, mean fault clearing time, maximum primary and backup relays operating time and maximum coordination time interval. The results show that using the multi-objective optimization approach in solving the DOCRs coordination problem achieved less total relays operating time and coordination time intervals which ensure faster fault clearing.

The authors wish to make the following corrections to this paper [...]

In this paper, a grid-connected Doubly Fed Induction Generator controlled by a Sliding Mode Controller (SMC) is used to maximize the Wind Energy Conversion System (WECS) output power. A SMC is implemented using a PID controller that is tuned using a new algorithm based on hybrid Differential Evolution with a Linearized Biogeography-Based Optimization (LBBO-DE). Biogeography-Based Optimization (BBO) is an evolutionary optimization algorithm based on a mathematical model of organism distribution. BBO permits a recombination of the solutions features by migration. A new migration model based on the sigmoid function is proposed. An analysis of the LBBO-DE is conducted using six different models, including the sigmoid model. Their performance were tested with 23 benchmark functions. The comparison reveals that the sigmoid model has the best performance. Therefore, the LBBO-DE with a sigmoid model is used to optimize the controller parameters to maximize the WECS output power. The LBBO-DE with the sigmoid model is compared with the Tyreus-Luyben tuning method, Genetic Algorithm (GA) and Linearized BBO (LBBO). The results showed that the LBBO-DE has the best performance. The proposed algorithm is verified using an experimental setup for the maximization of the generated power from the WECS and reducing power loss.

Harmonic phenomena is one of the main problems affecting power quality in the electrical distribution networks. Harmonics transmit from customer to neighbours causing impacts on many network elements. In the industrial section, there are many traditional solutions to the harmonics problem; each solution has advantages and disadvantages. For residential customers, no one cares about harmonics due to the insignificant individual power consumption compared with industrial loads. However, with the wide increase of electronics loads in the residential sector, the researchers in this area are forced to pay more attention to reduce the impacts of harmonics in the residential sector. This Paper presents a technique for harmonic mitigation and cancellation in the residential distribution network with no added equipment or extra cost. The proposed technique only need to analyze the performance of residential loads to choose a specific arrangement of such loads in order to reach the harmonic cancellation goal. The paper also presents a simple modification to the manufactures to fulfil the same goal.

Power Transformer is the heart of the electric power system. One of the main causes of power transformers' insulation failure is Partial discharge (PD). Partial discharges are electrical sparks which occur within the insulation material of power transformers. Degradation of insulation material is indicated by the presence of partial discharges. PD detection in transformers is an intricate task due to the inductive behavior of the transformer windings. The two main categories of PD detection are on-line detection techniques and off-line detection techniques. Off-line PD detection techniques incur high costs due to the downtime of power transformers alongside the utilization of expensive instrumentation. In contrast, on-line PD detection techniques are less expensive and can be performed on energized power transformers. Due to the variable nature of PD activity in power transformers, continuous on-line monitoring of PD activity is an optimal solution for gaining deeper insights into the characteristics of the PD activity. This paper provides an overview of PD activity in power transformers including its mechanism and mathematical modeling. Off-line and on-line PD detection techniques are reviewed and compared.

Optimization techniques have got much attention for solving complex problems related to different fields. Most of the planning researches deal with primary and secondary distribution systems separately because of complexity of both. This may lead to a local minimum for each but not a global minimum for both. In this paper, we try to reach the global minimum of joined primary and secondary distribution systems planning problem, which is essentially more complicated than planning each of them separately. To overcome such complexity, biogeography-based optimization (BBO) is employed in this work. BBO is a new technique for problem solving, developed by Dan Simon and has attracted wide attention in the last years. BBO is not a reproductive technique and this makes it distinguished from other strategies. Besides, BBO solutions can last or “survive” forever and are modified directly via migration from other solutions, so that BBO solutions directly share their features with other solutions. All of those above mentioned features of BBO algorithm may prove that it can perform efficiently for solving optimization problems and that it might be able to provide better performance compared to other optimization algorithms. In this paper, BBO is employed for solving the problem of optimal planning of a distribution system (OPDS) including both medium voltage (MV) and low voltage (LV) networks and based on uniform or non-uniform load density, where a planning procedure is employed iteratively to find the optimal location and rating of distribution transformers and substations, as well as the type and route of MV and LV feeders. The results are compared with genetic algorithm (GA) and particle swarm optimization (PSO), which indicate that BBO provides better performance in all cases.

The Maximum Power Point Tracking (MPPT) is an instrument which extracts the maximum power available from the PV array at any given moment. The power available from a PV module passes through a peak at a particular operating point and this peak also changes with atmospheric conditions. Hence the changing peak power needs to be continuously tracked.This paper explains the performance of two different MPPT used tosolar modules: perturb and observe (P&O) and incremental conductance (IC). It starts with a description of each method and then it compares them considering capability to follow irradiance variations in the required measurements.

In this paper, the crow search algorithm (CSA), a novel metaheuristic method for solving constrained engineering optimization problems, is used to solve the economic dispatch (ED) and economic emission dispatch (EED) problems for Abu-Rudeis Field Power Plant (ARFPP) in Egypt, while fulfilling the local energy demand. The existing ARFPP microgrid, consisting of eleven gas generator sets, is extensively tested to evaluate the annual fuel cost and emissions with/without unit commitment. Incorporating wind farm (WF) as a renewable energy resource is proposed for upgrading ARFPP microgrid to minimize fuel consumption and reduce released oxides of nitrogen emissions (NOx) to permissible value. Taking into account the capital cost of offshore wind power systems and the average wind speed at each month of the year at Egypt's Red Sea Coast region, where ARFPP is located, the WF size is optimally estimated using CSA.

This paper exhibits a complete design of maximum power point tracking (MPPT) control scheme based on an adaptive fuzzy controller. This controller is intended to upgrade the efficiency of a photovoltaic (PV) array and to diminish the output power oscillations. The adaptive nature of the proposed controller provides online tuning of fuzzy rules parameters to deal with varying sun radiation and ambient temperature. The adaptive MPPT controller is compared with existing setups, namely the “incremental conductance’ (I.C) technique and fuzzy logic controller (FLC). Simulation results demonstrate the supremacy of the adaptive technique in terms of the speed of tracking and oscillations reduction around the maximum of power-voltage (P-V) curve.

Power stabilization is a critical issue in nuclear reactors. The conventional proportional derivative (PD) controller is currently used in the Egyptian second testing research reactor (ETRR-2). In this paper, we propose a modified biogeography-based optimization (MBBO) algorithm to design the interval type-2 fuzzy logic controller (IT2FLC) to improve the performance of the Egyptian second testing research reactor (ETRR-2). Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. A modified version of the BBO is applied to design the IT2FLC to get the optimal parameters of the membership functions of the controller. We test the optimal IT2FLC obtained by modified biogeography-based optimization (MBBO) using the integral square error (ISE) and is compared with the currently used PD controller.

The effect of direct release (inside bags) of faba bean seeds or wheatgrains with the release ofAnisopteromalus calandrae was studied on insects populations, percentage damage seeds and percentage weight loss of stored seeds or grains due to infestation with Callosobruchus maculates (F.), Callosobruchus chinensis (L.) on faba bean seeds, Rhyzopertha dominica (F.)and Sitophilus oryzae (L.) on wheat grains at Ismalia and Sharkia governorates locations. Results showed release of A. calandrae reduced the monthly rate of increase of tested beetles on faba bean at rates between 35.20 and 42.14%. These rates resulted in populations reduction at the end of 6 month storage period at rates between 31.24 and 36.71%. In case of wheat grains the monthly rate of increase was reduced at rates between 29.05 and 46.80%. These rates resulted in populations reduction at the end of storage period at rates between 31.51 and 47.98%. The relative faba bean damage after the storage period was reduced in the range of 32.71 to 40.99% as a result of the parasitoid release. In case of wheat grains the obtained reduction in grain weight ranged between 72.67 and 81.66.

Three tested treatments of the entomopathogenic fungus Verticillium lecanii (Zimmermann)Vieges, the predator Chrysoperla carnea(Stephens) and V. lecanii followed by release of C. carnea in faba bean field for controlling cowpea aphid, Aphiscraccivora (Koch) compared with control were conducted. The first treatmentwasV. lecanii repeated 4 times at15-days intervals at the rate of 108 spores/ml. The second was C.carnea at the same intervals at the rate of 12,000 predator [larvae(L2)]/feddan/releases.The third was V. lecanii applied 2 times at15-days intervals at the same rate followedby release of C. carnea 2 times at 15-days intervals at the samerate. Treatments were conducted during 2006-2007 and 2007-2008at a location in Ismailia Governorate. These treatmentsindicated the potential use of these treatments to control A.craccivora on faba bean. Reduction in A.craccivora population and subsequent yields weresignificant between treatments. Highest reduction and yield gain was observedwhen fungus V. lecanii was applied

Proportional Integral Derivative (PID) controller is commonly used in process control systems. Tuning PID controller parameters are a very challenging problem to improve performance and stability of a process. This paper presents a novel method for PID controller tuning problem using Linearized Biogeography-Based Optimization (LBBO) algorithm. Biogeography-Based Optimization (BBO) is an evolutionary optimization algorithm based on mathematical model of Biogeography, it permits of sharing the features among candidate solutions (habitats) represented by emigration and immigration. By using Matlab/Simulink and the squared error integral criterion as objective function. The algorithm is applied to benchmarks functions optimization design, and is then compared with Particle Swarm Optimization (PSO), BBO, and Modified Biogeography-Based Optimization (MBBO). Simulation results shown that the LBBO is an effective tuning method and has better performance compared with PSO, BBO, and MBBO.

In this paper we apply the modified biogeography-based Optimization (MBBO) to design type-2 fuzzy logic controller (T2FLC) to improve the performance of the plant control system. Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. A modified version of the BBO is applied to design the T2FLC to get the optimal parameters of the membership functions of the controller. We test the optimal T2FLC obtained by modified biogeography-based Optimization (MBBO) using benchmark plants and is compared with Particle swarm optimization (PSO).

Proportional integral derivative (PID) controller tuning is an area of interest for researchers. This paper presents a novel method for PID controller tuning using a modified biogeography-based optimization(MBBO) algorithm. Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. In this paper, a modified version of the BBO is proposed to improve its convergence. The MBBO algorithm is compared with the BBO using benchmarks functions. The proposed algorithm is applied to the problem of PID controller tuning and is compared with conventional biogeography-based optimization (BBO), and Particle swarm optimization (PSO).

PID control is used widely in hydraulic servo control system. The PID control parameters are very important to performance of hydraulic servo control system and how to find rapidly the optimum values of PID control parameters is a very difficult problem. Based on Matlab/simulink software and taking the IATE standards of the optimization design as objective function, a global search optimization method with the modified Biogeography-Based optimization (MBBO) was applied for the optimization of the three parameters of PID controller of electric-hydraulic servo system of parallel platform. Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. In this paper, a modified version of the BBO is proposed to improve its convergence. The MBBO is used to deal with the PID Controller tuning. Simulation results show that the proposed parameter optimum method is an effective tuning strategy and has good performance compared with adopted NN network optimization method. (5 pages)

The recent growth in millimeter wave applications has created a corresponding demand for millimeter wave tests and instrumentation. Network analyzers, signal analyzers, signal generators, power meters and noise figure analyzers were discussed in this article. Optimum choice of instrumentation for specific applications were also be presented.

The transmission of 300 Mbit/s BPSK data on a 39 GHz subcarrier over 2.2 km of optical fibre using feedforward optical modulation is reported. This is the highest subcarrier frequency transmission reported to date. The authors show that this technique can be used to transmit gigabit data at carrier frequencies up to 100 GHz and beyond.

Emitter ballasting in class C microwave power transistors is shown to cause a sacrifice of output power and collector efficiency. The use of base impedance balasting resulted in the development of an experimental 4 GHz microwave power transistor which is capable of providing 3 watts of output power with a 6.4 dB power gain and a 65% collector efficiency. The experimental data on the collector current dependence of the power gain, and the spatial temperature distribution of the device working in class C and class A operations are presented. General guidelines for designing class C microwave transistors for optimum performance are given.

The unsteady state behaviour of a solar receiver under a concentrated solar flux has been studied theoretically. This behaviour is here examined under unsteady insolation condition and for structural disturbance. The results indicate a significant increase in the time delay before the receiver temperature reaches its steady state value. Actions are proposed to reduce this time delay. The results obtained suggest several interesting design criteria for a solar receiver to improve its unsteady state performance.

The Hall mobilities of two examples of vanadium-bronze are reported using microwave techniques. The hopping conduction mechanism is confirmed for the copper-vanadium-bronze by comparing the d.c. conductivity and mobility to the microwave conductivity and mobility.

Accelerated life tests show that CdS/Cu2S solar-cell lifetimes increase with lower temperature, cyclic light and a nitrogen-gas ambient. A normal Arrhenius type of temperature dependence was found. Extrapolated lifetime for cells kept below 50°C in nitrogen gas with earth deployment exceeded twenty years. The probable decay mechanisms are thermal diffusion, formation of recombination centres and voltage-induced decomposition.

The Hall mobilities of two examples of 1-dimensional conducting systems are reported; for the first time, a microwave technique has been used. The microwave technique was the only appropriate method for these very small crystals.