Explanation for **reactive** **power** says that in an alternating current system, when the voltage and current go up and down at the same **time**, only **real** **power** is transmitted and when there is a **time** shift between voltage and current both active and **reactive** **power** are transmitted. But, when the average in **time** is calculated, the average active **power** exists causing a net flow of energy from one point to another, whereas average **reactive** **power** is zero, irrespective of the network

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This paper proposes a method to determine action sequence of **reactive** **power** **compensation** devices in wind **power** system at the **time** of voltage regulating. Characteristics of **reactive** **power** **compensation** devices have impact on grid and these characteristics include qualitative index and quantitative index which can’t be eva- luated by a certain judging standard. Fuzzy theory is introduced in this paper to solve this problem. Each index of **reactive** **power** **compensation** device can be expressed perfectly with fuzzy multi-attribute decision making theory and by using this theory result corresponds to **real** condition more accurately.

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Abstract: In the modern **power** system the **reactive** **power** **compensation** is one of the main issues, thus we need to work on the efficient methods by which Var **compensation** can be done easily and we can optimize the modern **power** system. Var control technique can provides appropriate placement of **compensation** devices by which a desirable voltage profile can be achieved and at the same **time** minimizing the **power** losses in the system. In this paper the hybrid systems is used for dual **compensation** of **reactive** **power** and DC magnetic bias in distribution systems, and it results in desired **real** **power** in the system.

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With the extensive use of distributed **power** supply, the permeability of distributed energy is increasing at all levels of the **power** system. The planning and operation of the **power** system, especially the distribution network, are also complicated, and the economy of the distribution network sexual and regulatory methods have also had a greater impact. Active network management (Active Management, AM) technology, is in the distribution network secondary system parameters (voltage and current) on the basis of **real**-**time** measurement of distributed generation and distribution network equipment for **real**-**time** monitoring. Roughly divided into three categories: active fault level management, active voltage control and active **power** flow management. Complex measurement, control and communication facilities are the hardware base for implementing the distribution network AM. Figure 1 shows the schematic diagram of AM. The active process is to send control instructions to the transformer, generator, circuit breaker, and **reactive** **power** **compensation** equipment to complete the control.

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A three-leg single-phase-VSC-based DSTATCOM [5] requires a total of 12 semiconductor devices, and hence, is not attractive, and the three-leg VSC with split capacitors [5] has the disadvantage of difficulty in maintaining equal dc voltage at two series-connected capacitors. The four-leg-VSC-based DSTATCOM [3] is considered as superior considering the number of switches, complexity, cost, etc. A three-leg VSC with T connected transformer [10] is reported recently and has shown improved performance. The three-leg VSC with T-connected transformer has the advantage of using a passive device for neutral current **compensation**, reduced number of switches, use of readily available three-leg VSC, etc. The proposed three-phase four-wire DSTATCOM is based on a three-leg VSC and a T-connected transformer. The T connected transformer requires two single-phase transformers. A star/delta transformer is also reported [19] for neutral current **compensation** and the kVA rating required is higher compared to T-connected transformer. Table I shows the rating comparison of the two transformer techniques for a given neutral current of 10 A. It is observed that the kVA rating of the T- connected transformer is much less compared to a star/delta transformer. Similarly, comparison with the four-leg converter shows that the numbers of switches are reduced in the proposed configuration, thus reducing the complexity and cost of the system.

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To estimate day ahead PV irradiance, we apply an ARIMA (1,0,0)(1,1,0) prediction model (as suggested and explained in [33]), with suitable model parameters estimated from 30 days of hourly irradiance data prior to the day being simulated. We also predict two-day ahead generation, which is used to determine an end of day goal SOC for the day ahead. The MATLAB ARIMA tool is used for parameter estimation and simulation, and ARIMA+2σ is used as the irradiance prediction; this is cautious, but reduces the risk of irradiance underestimation, and hence reduces the risk of prematurely filling BESSs before they are required for network violation control. Per site generation is estimated using a simple **power**-irradiance-temperature regression model [34], [35], and the hourly demand prediction is estimated using persistence with consideration of day- type (weekday or weekend); this appears crude, but [36] shows that little forecasting improvement is seen with more advanced predictive methods.

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The PCS100 ESS range is part of a family of energy storage system converter products available from ABB. Based around a low voltage converter platform the PCS100 ESS provides wide bandwidth performance with a flexible and highly modular **power** electronic configuration. New energy storage devices such as new generation batteries, flywheel and super capacitors provide the opportunity to store energy from the electricity grid and return it when required. This offers a huge range of options to strengthen and enhance the performance, quality and

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(RPC), RPC can make comprehensive **compensation** of negative sequence components, harmonics and **reactive** **power**. Reference carries a dual-loop control strategy in order to improve the control effect and performance of RPC. Taken into account the disturbance and variation of electrified railway environment, a recursive PI control based on fuzzy algorithm is adopted to realize a fast and smooth tracking to reference current. Reference raises a method of setting up two groups of thyristor control reactors (TCR) and two groups of thyristor control 3rd harmonic wave filter besides RPC. The RPC is used to transfer active **power**; the **reactive** **power** is supplied by the TCR and the filter. These works prove that RPC is a effective way to solve the **power** quality problems in railway system. Half-bridge-converter-based (RPC) (HBRPC) which consists of two half-bridge converters connected by two capacitors connected series. As compared with the traditional railway **power** conditioners (RPC), the HBRPC requires only a pair of **power** switch legs and two capacitors. The same function of RPC, this conditioner can reduce half of the **power** switches, which can make it with lower hardware complexity at lower cost. A double-loop control is this for HBRPC to keep the dc-link voltage stable and achieve the dynamic tracking of

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Abstract––Shunt **compensation** for medium voltage distribution systems requires higher rating for voltage source converters (VSCs). Ratings of the semiconductor devices in a VSC are always limited; therefore, for higher rated converters it is desirable to distribute the stress among the number of devices using multilevel topology. Cascaded multilevel configuration of the inverter has the advantage of its simplicity and modularity over the configurations of the diode-clamped and flying capacitor multilevel inverters. Application of cascaded multilevel converters for shunt **compensation** of distribution systems has been described in Literature. This paper presents an investigation of five-Level Cascaded H – bridge (CHB) Inverter as Distribution Static Compensator (DSTATCOM) in **Power** System (PS) for **compensation** of **reactive** **power** and harmonics. The advantages of CHB inverter are low harmonic distortion, reduced number of switches and suppression of switching losses. A CHB Inverter is considered for shunt **compensation** of a 11 kV distribution system. Finally a level shifted PWM (LSPWM) and phase shifted PWM (PSPWM) techniques are adopted to investigate the performance of CHB Inverter. The results are obtained through Matlab/Simulink software package. The proposed DSTATCOM is simulated for both linear and nonlinear loads.

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Voltage sag and swell is the most important **power** quality problems faced by many industrials and domestic users. It contributes more than 80% **power** quality (PQ) problems that exist in distribution system. According to definition, Voltage sag is the RMS reduction in the AC voltage at **power** frequency from half of a cycle to a few seconds duration. Similarly, Voltage Swell is the RMS increase in the AC voltage at **power** frequency from half cycles to a few seconds[1]. Voltage sag and swell are not tolerated by sensitive equipment used in modern industrial plants, such as process controllers, programmable logic controllers (PLC), adjustable speed drives (ASD), and robotics. It has been reported that high intensity discharge lamps used for industrial illumination get extinguished at voltage sags of 20% and industrial equipment like PLC and ASD are about 10%[5].

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tor (usually 0.85 or 0.9 lagging) which they can carry continuously without overheating. The active **power** output is limited by the prime mover capability to a value within the MVA rating. The continuous **reactive** **power** output capability is limited by three considerations: ar- mature current limit, field current limit, and end region heating limit. The **reactive** **power** production cost of gen- erator is called opportunity cost. According to the load- ing capability diagram of a generator (Figure 2), **reactive** **power** output may reduce active **power** output capacity of generators which can at least serve as spinning reserve, therefore causes implicit financial loss to generators. Actually, opportunity cost depends on the **real**-**time** bal- ance between demand and supply in the market, so it is difficult to determine the **real** value. For simplicity, an opportunity cost can be represented as:

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As can be seen from Fig. 6-a and Fig 6-b, TSC located at Bus 2 provides the enough **reactive** powers for the static load around its base value to keep the load voltage at the acceptable level. From Fig. 6-a, it is clearly seen that if the capacitor in the TSC structure is not charged before the simulation starts, TSC produces the transient component of the load voltage. On the other hand, if the capacitor is charged before the simulation starts, the transient component of the load voltage is eliminated as seen from Fig. 6-b.

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In this case the reference signal to be amplified will be the voltage at the point of common coupling. So the voltage calculated in the **real** **time** simulation is transferred to the **Power** Amplifier control unit after an ADC and DAC respectively. Once the signal is in the control unit of the **power** amplifier, it is processed through the DFT transforms. The DFT algorithm used allows for a variable frequency of the processed signal, so being accurate during frequency changes. The DFT output values, in the frequency domain, will be phase-shifted harmonic by harmonic and phase by phase according to the measured loop delay, hence compensating the **time** delay. Then, the reconstruction of the signal into the **time** domain will be carried out. The reconstructed phase-shifted waveform is then introduced as reference for the PI-Resonant controller type of the **Power** Amplifier that finally will amplify the voltage to that of the reference and applies it to the device under test as shown in Fig 2. In this manner the **time** delay **compensation** will not affect to the system topology and therefore the dynamic behaviour of the original system will stay as it originally was in terms of **power** angles and V-I phase relationships for all the harmonics processed. The main limitation of this algorithm is that it is not appropriate for the accurate reproduction of fast transients, i.e. sub-cycle step- changes to the fundamental or harmonic amplitudes. The DFT window length is finite, and in this paper a 2-cycle triangular window, adaptive to fundamental frequency, is used. So, any step change in fundamental or harmonic content or voltage within the simulation will be represented as a smoothed “ramp” of the component’s amplitude/phase over 2 cycles in the PHIL environment. This is the drawback of the proposed approach. On the other hand, the benefit is that ALL the voltage-to-voltage and voltage-to-current amplitude and phase relationships for the fundamental and harmonics should be maintained accurately for quasi-steady-state operation, i.e. for all dynamic cases except the most abrupt “sub-2-cycle” step changes which will be “smoothed” over 2 cycles.

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stability are closely linked [26]. The advantages of using the SSV as a voltage stability margin are that 1) it captures any direction of changes in **power** injections and 2) there exist approximate mathematical formulations suitable for inclusion in optimization problems, e.g., [11], [27], [28]. It is simpler to work with than the distance to the closest SNB because there is only one SSV, while there can be a large number of locally closest SNBs. The disadvantages of using the SSV are that 1) it only provides implicit information on the distance to the solvability boundary, 2) it does not capture the impact of all engineering constraints (e.g., **reactive** **power** limits could be reached prior to **power** flow singularity [29]), and 3) it may not be well-behaved, specifically, [30] found that the SSV at voltage collapse varies significantly as function of the loading direction (see Fig. 3 of [30]). Additionally, 4) its numerical value is system-dependent [24] and so the threshold value for a particular system would need to be determined from operator experience. Moreover, 5) the nonlinear programming (NLP) algorithm for solving approximate mathematical formulation [28] does not scale to realistically-sized system. Despite these issues, we base our approach on the SSV in order to exploit the approximate mathematical formulation [27], [28] and we de- velop an improved solution algorithm that scales significantly better. Recognizing the potential advantages of other stability margins, our ongoing work is exploring the development of analogous formulations based on other stability margins.

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The increasing demand of electricity with high **power** quality along with more reliable and secure **power** system is fulfilled by providing the electricity which operates more flexibly and with best utilization. This increasing demand can be fulfilled either by installing new transmission lines or by increasing **power** transfer capability of the transmission line. The effective and economical solution is to increase transfer capability of transmission line giving attention to more utilization. To operate the **power** system in a flexible manner, controlling action should be made fast by utilizing the advance research and development in **power** electronics technology. The **power** transmission capacity has been enhanced without exceeding the thermal limit of transmission line and is achieved by incorporating Flexible AC Transmission System (FACTS) technology [1][2].

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344 | P a g e efficient solutions for **power** quality problems. These modern solutions have been given the name of active compensators or active **power** filters. The objective of these active **power** filter abbreviated mostly APF is to compensate harmonic currents and voltages in addition to selective **reactive** **power** **compensation**. The use of APFs for harmonic and **reactive** **power** **compensation** and DC **power** generation was proposed in [4]. The main advantages of the APFs are their flexibility to fit load parameters’ variations and harmonic frequencies in addition to high **compensation** performance.

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Abstract – **Reactive** **Power** **Compensation** plays a vital role to minimize the losses, to control the voltage and to improve the **power** transfer capability in a long transmission line. This paper employs the shunt connected FACTS device such as Static Var **compensation** (SVC) to control voltage and the **power** flow and also to minimize the losses in a long distance transmission line about 100Km, 200Km, 300Km & 400Km. The proposed device was used in different locations such as sending end of the transmission line, middle and receiving end of the transmission line. The PWM control strategy was used to generate the firing pulses for the controller circuit. Simulations were carried out using MATLAB Simulink environment. The suitable location and the performance of the proposed model were examined. The results were obtained with and without **compensation**. The simulation results reveals that the **reactive** **power** generated and injected is better at the sending end of the transmission line and it was 62.03MVAr when compared with the other ends of the transmission line and also the voltage is controlled at the sending end of the line. The line losses and the **power** transfer capability of the line were obtained at the midway and receiving end of the line. The results show that the line losses are reduced and the **power** transfer capability is better when SVC is connected at the sending end of the line. These results were shown in table 1 and 2. Henceforth the location of SVC is optimum when connected at the sending end of the line.

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Abstract — This paper presents a novel concept of energy management software for developing efficient home energy management system. The investigator has developed highly powerful energy management software by using NI LabVIEW, which is capable of doing very complex calculations in fraction of seconds, giving the online data immediately, hence increasing the efficiency of energy managers several times. This software will also give direction regarding energy saving, energy management, money back period, harmonics, **power** quality and many more. By using this software millions and millions dollar energy of the country can be saved because a simple person can also operate this software and can get proper energy saving directions without any help.

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Generally, electric **power** sector has three sectors which are: generation, transmission and distribution. In generation sector, different kind of energies is converted into electrical energy. Transmission activity is dedicated for transporting electrical energy from sending end to end centers. In distribution activity energy is transferred from utility grid to consumers. This paper concludes generation sector with transmission in which wind energy conversion system is connected with main **power** transmission system which are supplied by conventional **power** station. Wind energy is a large renewable energy source. Global wind **power** potential is of the order of 11,000 GW [1]. It is about 5 times the global installed **power** generation capacity. This excludes offshore potential as it is yet to be properly estimated. About 25,000 MW is the global installed wind **power** capacity. It is about 1% of global installed **power** generation capacity [3]. Wind produces about 50 billion kWh per year globally with the average utilization factor of 2000 hours per year. The Wind Turbine Generator is designed for optimal operation at a wind speed of 10-14 m/s. The Turbine Generator starts at a cut-in speed of 3-3.5 m/sand generate **power** at speeds 4.5 m/s and above. In India, the best wind speed is available during monsoon from May to September and low wind speed during November to March. The annual national average wind speed considered is 5-6 m/s. Wherever average wind

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