BRPI1105416A2 - wireless power control system for smart grid application - Google Patents

Abstract

WIRELESS CONTROL SYSTEM OF ELECTRIC POWER FOR APPLICATION IN INTELLIGENT NETWORKS. The present application for a patent relates to a wireless electrical power control system for application in smart grids. Additionally, the invention deals with a system containing a wireless power coded deadbeat control system for application in smart grids and its application in a double-powered induction generator aimed at generating wind energy.

Description

WIRELESS ELECTRIC POWER CONTROL SYSTEM FOR APPLICATION IN

SMART NETWORKS

Field of the invention

The present patent application relates to a wireless power control system for application in smart grids. Additionally, the invention relates to a system containing a wireless encoded power deadbeat control system for application in smart grids and its application in a double powered induction generator aimed at wind power generation. Fundamentals of the invention

Renewable energy systems have attracted the interest and numerous efforts of various governments as opposed to other energy sources that increase CO2 emissions or cause huge environmental impacts. Such renewable networks generate electricity from wind, solar and tidal sources.

Recently, the concept of smart grids has been widely applied to these energy plants to enable and optimize this challenge (Blau, 2010). The work done to consolidate and implement the concept of smart grids using wind systems has been of great interest to the community and has been the focus of several recent scientific studies (Glinkowski et al., 2011; Wang et at., 2011; Xiwen et al. ., 2010).

Intelligent grids are an evolution of current electricity grids and are based on the most efficient use of the generation, transmission and distribution infrastructure, in order to manage the supply / demand relationship avoiding contingencies in the electricity system and for this it is necessary A tightly interacting suite of communication networks, data management and real-time monitoring applications. However, wireless transmission is subject to distortions and errors caused by the radiopropagation channel that can cause serious problems for controlled or monitored equipment and, consequently, for the power plant as a whole. In contrast, one of the advantages of using modern wireless systems is the ability to improve system robustness through the use of forward error correction (FEC) techniques. FEC coding is a technique employed in all current wireless systems and is essential for ensuring information integrity by significantly reducing error rates and system delay by adding redundancy to transmitted information.

There are currently several different FEC coding techniques being employed in commercial wireless systems. Among existing techniques, Low Density Parity Check (LDPC) encoding is currently the state-of-the-art technique that has an excellent compromise between decoding complexity and performance (MacKay and Neal1 1996; Richardson et al. 2001). LDPC encoding has recently been added to the IEEE 802.16e standard, better known as WiMAX (Worldwide Interoperability for Microwave Access) for mobile applications.

Importantly, there is some work in the scientific literature regarding the application of wireless technology in the monitoring of sensor network-based wind generators (Adamowicz et al., 2010), however there are no deeper studies related to the use of wireless technology for control applications in these systems. Additionally, the studies by (Li et al., 2009 and Wanzhi et al., 2009) present studies and implementations of wireless communication systems for control and monitoring applications in wind farms referenced to a remote plant, demonstrating their potential for applicability in the near future.

Although these works exemplify and highlight the real advantages and functionality offered by the use of wireless communication channels, none of them propose or analyze techniques that can guarantee the reliability and security of transmitted control and monitoring information regarding the robustness of transmission errors due to degrading effects of the wireless communication channel. Accordingly, such invention is intended to fill a gap in the state of the art by demonstrating the functional feasibility of using wireless systems for this type of application provided that suitable coding techniques are employed.

With regard to wind turbine generators, the

Double Powered Induction Generator (GIDA) is widely used because it has some advantages over other generators used, such as variable speed operation and the use of converters that process around 30% of the nominal power of the generator. In this type of generator the power control is performed through field orientation control techniques based on the spatial position of the stator voltage or flux space vector, which enables the decoupling of the direct and quadrature axis components, making possible the control. independent of the active and reactive powers. In the work of (Tapia et al., 2003) some

Investigations to control the power of a GIDA with the use of Proportional Integral (PI) controllers, however, this type of controller presents problems related to the design of its gains due to the operating conditions of the generator. In the works of (Xin-fang et al., 2004; Morren and Sjoerd W. H. of Haan et al., 2005; Guo et al., 2008) investigations were performed when functional predictive control and internal mode control techniques were employed. Although both controllers perform satisfactorily, they are difficult to implement due to their intrinsic formulations. It is therefore interesting that the state of the art has

a wireless power coded deadbeat control system utilizing LDPC coding, and its use in a wind powered dual induction generator for smart grid applications. BRIEF DESCRIPTION OF THE FIGURES AND ATTACHMENTS The invention will now be described with reference to the following

appended drawings, in which: Figure 1 shows a wireless control system diagram of smart grid application remote power stations. The system consists of a power generation system (1), a wireless communication system (2) which additionally integrates a set of transmit (2.1) and receive antennas (2.3) and the radio channel (2.2). ), and a remote control center (3) with smart grid connection (4).

Figure 2 presents a more detailed diagram of the wireless communication system (2) for controlling remote power stations via a radio channel (2.2). The transmission step of this system, implemented in the remote control unit, is composed of a set of analog to digital converters and a multiplexer (5), an LDPC channel encoder (6), a block interleaver (7), a modulator employing a QPSK (Quartenary Phase Shift Keying) scheme (8) and a transmit antenna (2.1). The receive step, implemented in the power generation system, comprises a receive antenna (2.3), a QPSK digital demodulator (9), a block deinterleaver (10), a channel decoder (11) and a demultiplexer. and a set of digital-analog converters (12).

Figure 3 shows a diagram of the Gl DA power controller system. It consists of a rotor electric speed integrating block (13), a stator flow estimator (14), a deadbeat power controller, whose function is to calculate the voltage to be applied to the generator rotor terminals so that the power references are met (15), the mains (16), a double-powered induction generator (17) and an electronic power converter (18). The stator terminals are connected directly to the mains and the rotor is connected to the mains through electronic power converters. Brief Description of the Invention

This patent application relates to a wireless power control system for application in smart grids, comprising: a power generation system, a wireless communication system and a remote control unit with connection for smart grid. The proposed system communicates between the power generator and the remote control center via a wireless communication system, without the need for cables, as it is done today. During transmission over the radiopropagation channel, errors may occur causing the system not to operate properly, as the power generation system may generate an electrical power value that is not in accordance with the value sent by the smart grid to the power station. remote command. In this context, an object of this invention is also to minimize the occurrence of errors in the reference information received in the power generation system and to ensure its perfect functioning.

In addition, the invention relates to a wireless power control system for application to dual-fed wind power generators containing a wireless coded deadbeat power control system for application to smart grids. Detailed Description of the Invention

This patent application relates to a wireless power control system for application in smart grids. The invention also relates to a new GIDA coded wireless deadbeat control system employed in wind generation for smart grid applications.

Wireless power control system for smart grid application

The wireless electric power control system comprises:

(a) a power generation system,

b) a wireless communication system,

c) a remote control center with connection to smart grid.

The wireless communication system involves all equipment related to the radio transmission of control information from the remote control center to the power generation system, without the need for wiring, robust and noise and interference resistant. For correct operation, this system also includes several steps such as carrier, frame and symbol synchronization, signal amplification, automatic gain control, digital modulation and demodulation, channel coding and decoding and other operations necessary for signal conformation to be performed. be transmitted.

The wireless communication system comprises:

(a) a set of analog to digital converters,

(b) a digital signal multiplexer;

c) an LDPC channel encoder,

d) a block interleaver,

e) a QPSK digital modulator,

f) a QPSK digital demodulator,

g) a block deinterleaver,

h) a channel decoder,

(i) a digital signal demultiplexer;

j) a set of digital-analog converters, and

k) means for transmitting and receiving signals.

The power generation system comprises the set of equipment responsible for the generation of electric power from a non-electric power source. Energy sources can be solar, wind, hydraulic or biomass. In the case of the use of hydraulic or wind energy, the generation system will consist of the generator, which is the machine that will convert the mechanical power to electrical, and the system that will drive the machine that will operate as generator, in this case, hydraulic or wind

The remote control center is the location responsible for the interaction between the smart grid system and the power generation systems. Its purpose is to send the power reference signals to the power generation systems. It can also monitor the variables related to power generation systems, in this case wind speed in wind turbines, solar incidence in solar panels, the active, reactive and apparent power values generated by the generation systems and the power factor of the same. .

The acquisition of active and reactive power references, Pref and

Qref, respectively, are made through the smart grid. Then are

The coding and modulation techniques applied for the transmission of reference information through the radiopropagation channel to the power generation system.

As the transmitted signals may suffer errors due to the degrading effects of the radiopropagation channel, the notation will be adopted.

Pre / e Qref P31 "3 represent power reference information

received in the power generation system.

Errors caused by the channel may cause the system to not operate properly, as the power generation system may generate a power value that is not in accordance with the value sent by the smart grid to the remote control center. As a result, the efficiency of the power generation system may be reduced and in some cases the system may not even generate electricity and consume it from the electrical system. Other possible problems would be the generation of undesirable harmonic components and even the damage to the electronic power converters responsible for processing power from the generator to the power grid.

In this context, one of the objectives of this invention is to minimize the occurrence of errors in the reference information received in the power generation system and to guarantee its perfect functioning.

For the proposed wireless system, the remote control unit shall have a set of analog-to-digital converters, a digital signal multiplexer, an LDPC channel encoder, a block interleaver, a QPSK digital modulator and a transmit antenna. They will be responsible for coding and transmitting the active and reactive power references from the smart grid. The coded and modulated control information will be transmitted through a radio propagation channel to a receiver installed in the power generation system. The receiver consists of a receiving antenna, a QPSK demodulator, a block deinterleaver, a LDPC1 channel decoder, a digital signal demultiplexer, and a set of digital-analog converters and is responsible for robustly retrieving control information for eliminate or significantly reduce transmission errors caused by the radiopropagation channel.

The wireless communication system proposed for the control is presented in Figure 2 and uses a coding scheme to correct LDPC errors, seeking to improve the system reliability and performance. LDPC codes are linear block codes (/ Vc, N13) that have an H parity check matrix that can be described by a Tanner (1981) graph. Each bit in a codeword corresponds to a variable node and each parity check equation corresponds to a check node. A check node j is connected to a variable node k if the element hj.k of H is equal to 1.

The parity check matrix of this code family can be represented by H = [Hi H2], where Hi is a sparse matrix (Nm) x (Nc) that can be irregularly constructed by the density evolution method according to a weighted distribution of weights (Zhang et al., 2005; Sripimanwat, 2010) and H2 is the square matrix of double diagonal (Nm) χ (Nm) given by:

<formula> formula see original document page 9 </formula> where Nc is the amount of code bits and Nm is the amount of parity bits.

Given the constraint imposed on matrix H, the coding depends on Hit and H2T and the generation matrix can be expressed in systematic form by the following matrix (Nb) χ (Nc) '.

G = [I]

where Nb is the total number of control information bits transmitted, Ψ = H /. H2t and H2t is the upper triangular matrix given by:

1

1

1 1 1

1 1 1

1 1 1

1 1

The coding process can be performed by multiplying,

first, the control information vector q <, = [qb (1) ... qb (Nb)] T by the sparse matrix H /, and then differentially encoding this partial result to obtain the parity bits.

The vector of systematic codewords qc = [qrc (1) ... qc (Nc)] T can be obtained by simply combining the control information and the parity bits:

qc = [q & φ]

In the transmission process, the codeword vector is first interlaced and then modulated in QPSK employing Gray1 encoding resulting in the symbol vector s = [s (1) ... s (Ns)] J in which Ns is the number of coded control symbols transmitted. At the end, the coded symbols are filtered, frequency translated and transmitted through the radiopropagation channel. Assuming that channel variations are slow enough that intersymbol interference (ISI) can be neglected, the fading channel can be considered as a sequence of complex zero-mean Gaussian random variables and with the modeling of the autocorrelation function due to an isotropic dispersion (Barbieri et al „2007):

Rh (τ) = J0 (27rfDTs)

where J0 is the zero-order Bessel function, Ts is the symbol time and fo is the Doppler scatter.

Thus, in the reception process, the equivalent complex received low pass signal can be represented by:

<formula> formula see original document page 11 </formula>

where r = [/ - (1) ... r (Ns)] J is the received signal vector, γ = [K1) ■ ·· γ (Ν3)] Ύ is the channel-related complex coefficient vector with time variant fading and η = [n (1) ... n (Ns)] J is an AWGN (Additive White Gaussian Noise) vector. Note that the vector multiplication presented is performed element by element.

Once the transmitted vector s is recovered at the receiver, considering a perfect estimation of the radiopropagation channel, it becomes possible to obtain the transmitted control bits by demodulating the received symbols, deinterlacing the code bits and finally decoding the information bits. .

Bit decoding can be performed by an iterative process of message passing based on the Maximum a Posteriori (MAP) criterion:

<formula> formula see original document page 11 </formula>

where d is the coded bit vector resulting from the demodulation and deinterlacing processes. The message passing algorithm, also known as Belief Propagation when messages are represented by probabilities, iteratively exchanges smooth information between variable and check nodes. Nodes can be updated by first updating the variable nodes and then the check nodes.

The message exchange can be represented by the following log-likelihood ratio (LLR): <formula> formula see original document page 12 </formula>

The LLR message from the jth check node to the kth variable node is given by: <formula> formula see original document page 12 </formula>

Set Vi contains all variable nodes connected to the jth check node and set Ck contains all check nodes connected to the kth variable node. The subset Vj / k is the set Vi without the jth members, and the subset Ck / j is the set Vj without the jth members.

The kl variable node LLR message for the jth check node can be represented by: <formula> formula see original document page 12 </formula>

and the LLR message for the kth code bit is given by: <formula> formula see original document page 12 </formula> At the end of each iteration, the Lqr message provides an updated estimate of the LLR A after the code bit. transmitted qc (k). If Lqr> O, then qc (k) = 1, otherwise qc (k) = 0. GIDA Power Controller System It is a further object of this invention a power controller system

power to a double-powered induction wind power (GlDA) generator. This system is part of a wind power generation system and its purpose is to control the active and reactive power of GI DA.

GIDA's power controller system consists of:

a) Integrator block, whose purpose is to integrate the rotor electrical speed

b) Stator flow estimator, which has the purpose of acquiring the stator voltage and current signals, and from this data make the

transformation of the abe three-phase coordinate system to the stationary αβ biphasic coordinate system and obtain the spatial position of the stator flux and the magnitude of the stator flux vector,

c) Deadbeat power controller, whose purpose is to calculate the voltage to be applied to the generator rotor terminals such that the

power references are met,

(d) power grid,

e) Double powered induction generator,

f) Electronic power converter.

The stator terminals are connected directly to the mains and the rotor is connected to the mains through electronic power converters, as shown in Figure 3.

GIDA in the synchronous frame can be represented by:

Vidq = RÁdg + - ^ Tm + <formula> formula see original document page 14 </formula>

where ν, i, λ are, respectively, the voltage, current and flow spatial vectors, R is the winding resistance, L is the winding inductance, B is the number of pole pairs, cox is the synchronous speed, color is the rotor speed and the subscripts 1 and 2 are respectively stator and rotor references.

The active and reactive powers can be obtained by:

<formula> formula see original document page 14 </formula>

Using the stator flow orientation technique, which decouples the d and q components, the relationships between stator and rotor currents become:

<formula> formula see original document page 14 </formula>

where Lm is the mutual inductance. Thus, the active and reactive powers will be:

<formula> formula see original document page 14 </formula>

These equations show that the system can provide active and reactive power control independently by changing the rotor current. The deadbeat power control proposal, shown in Figure 3, considers precisely this relationship. Consequently, control of the stator active and reactive powers can be accomplished by controlling the GIDA rotor current with its stator connected directly to the mains.

The discretized equations of the rotor currents in the synchronous reference operating with a sampling time T, considering the stator flow position at time (k + 1) T and can be represented (Filho and Ruppert1 2010) by:

<formula> formula see original document page 15 </formula> 1

where msl = ωχ-ΒωΓ is the slip frequency and σ = I-L2m / (L1L2) is the global dispersion factor.

The rotor voltage, which is calculated to guarantee a zero steady state error with the use of the control technique, is given by:

<formula> formula see original document page 15 </formula>

For active power control, the quadrature axis rotor current reference i2q is given by: • / l. ι Λ \ · ZPrefLi

". <* + 1J =» * - / = -ISIS

and for reactive power control, the i2ci direct shaft rotor current reference is given by:

• (i. I 1 \ · ^ QrefLi λχ

where Pref is the active power reference and Qref is the reactive power reference.

Thus, if the voltage components d and q calculated by the above equations are applied to the generator rotor, then the convergence of the active and reactive powers to their respective command values will occur at some sampling intervals. The desired rotor voltage in the ô-rotor frame generates the switching signals for the converter connected to the rotor using spatial vector modulation. The deadbeat power controller is intended to perform the following steps:

a) Acquire the signals of voltage, current, rotor speed, active and reactive power, magnetic flux and the spatial position of the magnetic flux of the stator.

b) Transform the data from the three phase coordinate system abe to the two-phase stationary αβ coordinate system and then to dq with

the use of the spatial position of the δ5 stator flow,

c) Acquire rotor current signals,

d) Transform the three phase abe coordinate system from the rotor to the synchronous coordinate system dq through the spatial position of the 5S stator flow and the rotor position δΓ

e) Calculate rotor voltages using equations 1 and 2,

f) Transform rotor voltages from synchronous reference dq to rotor reference (αβΓ), g) Calculate switching times to drive the drive using a pulse width modulation technique. Stator flow estimator

For the control of deadbeat power, it is necessary to calculate the values of the active and reactive power, their errors, the magnitude and position of the stator flow, the slip speed and the synchronous operating frequency.

The estimation of the stator flow <formula> formula see original document page 17 </formula> i in the stationary reference is

given by:

<formula> formula see original document page 17 </formula> This expression can be implemented to allow stator flow estimation even when the machine operates at low speeds in an induction motor direct torque control system such as presented in Filho e Filho (2009).

The position of the stator flow using a as:

<formula> formula see original document page 17 </formula> The estimation of synchronous velocity ωι is given by:

<formula> formula see original document page 17 </formula> and the estimation of slip velocity using rotor speed and synchronous velocity is given by: <formula> formula see original document page 17 </formula> while the position of the rotor in the rotor frame is given by: <5S - ar = j ustdt

Therefore, the magnetic flux estimator is responsible for performing the following steps:

(a) acquire stator voltage and current signals,

(b) transform the three-phase coordinate systems abe to the stationary coordinate system αβ,

c) Calculate stator flow, position, and synchronous velocity according to equations 3, 4 and 5 respectively.

References

(Blau, 2010) - J. Blau, "Europe plans a north sea grid," IEEE Spectrum, pp. 08-09, March (2010).

Filho and Filho (2009) - Filho, A. J. S. and Filho, E. R .. "The complex controller for three-phase induetion direct torque control motor", SBA Control and automation, vol. 20, pp. 256-262 (2009).

(Glinkowski et al., 2011) - Glinkowski, M., Hou, J. and Rackliffe, G., "Advances in Wind Energy Technologies in the Context of the Smart Grid", Proceedings of the IEEE 99: 1083-1097 (2011) .

Tanner (1981) - R. M. Tanner, "A Recursive Approach to Iow Complexity Codes," IEEE Transactions on Information Theory, Vol. 27, no. 5, pp. 533-547 (1981). Wang et at., (2011) - Wang, J., DU, X. and Zhang, X .. "Comparison of wind power generation interconnection technology standards", Asia-Pacific Power and Energy Engineering Conference (2011).

Xiwen et al., 2010 - Xiwen, W., Xiaoyan, Q., X. and Xingyuan, L., "Reactive power optimization in smart grid with wind power generator", Asia-Pacific Power and Energy Engineering Conference (2010).

Claims (10)

1. Wireless power control system for application in smart grids, comprising: a) a power generation system; b) a wireless communication system, and c) a remote control center with connection for smart grid. System according to Claim 1, characterized in that the power generation system may be wind, solar, hydraulic and / or biomass. System according to claim 2, characterized in that the power generation system is wind power and further comprises a deadbeat power controller system for a double-fed induction generator. System according to claim 3, characterized in that said power control system comprises: a) an integrating block; b) a stator flow estimator; c) a deadbeat power controller; d) an electric grid; e) a double-powered induction generator, and f) an electronic power converter. System according to Claim 4, characterized in that the stator flow estimator is responsible for performing the following steps: a) Acquiring the stator voltage and current signals; b) Transform the three-phase coordinate systems abe to the stationary coordinate system αβ, and c) Calculate stator flow, its position, and synchronous velocity. System according to claim 5, characterized in that step (c) is performed according to equations 3, 4 and 5 respectively. System according to claim 4, characterized in that the deadbeat power controller performs the following steps: a) acquiring the signals of voltage, current, rotor speed, active and reactive power, magnetic flux and the spatial position of the magnetic flux. stator; (b) transform the data from the three phase abe coordinate system to the stationary αβ two-phase coordinate system; c) acquire the rotor current signals; d) transforming the three-phase coordinate system abe from the rotor to the synchronous coordinate system dq through the spatial position of the stator flux δ8; and rotor position δΓ. e) calculate rotor voltages. f) transform rotor voltages from synchronous reference dq to rotor reference (αβΓ), g) calculate switching times to drive the drive System according to claim 7, characterized in that step (e) calculates the rotor stresses from equations 1 and 2. A system according to claim 7, characterized in that step (g) calculates the switching times for driving the converter from a pulse width modulation technique. System according to Claim 1, characterized in that the wireless communication system comprises: a) a set of analog to digital converters, b) a digital signal multiplexer, c) an LDPC channel encoder, d) an interleaver in e) a QPSK digital modulator, f) a QPSK digital demodulator, g) a block deinterleaver, h) a channel decoder, i) a digital signal demultiplexer, and j) a set of digital-analog converters,