1. Introduction

In the past decades, the ever-increasing penetration of renewable energy (wind, solar, wave, hydro, and biomass) requires an extraordinarily reliable and effective transmission of electrical power from these new sources to the main power grid [1], in which hydropower has already

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

been fully exploited in many grids, such that a sustainable development can be achieved in future [2]. The problems and perspectives of converting present energy systems (mainly thermal and nuclear) into a 100% renewable energy system have been discussed with a conclusion that such idea is possible, which, however, raises that advanced transmission technologies are needed to realize this goal [3].

in the state space via an appropriate switching logic; it features the simple implementation, disturbance rejection, fast response, and strong robustness [15]. While the malignant effect of chattering phenomenon can be reduced by predictive variable structure [16] and self-tuning sliding mode [17], SMC has been applied on electrical vehicles [18], power converters [19], induction machines [20], wind turbines [21], etc. Moreover, a feedback linearization sliding-mode control (FLSMC) has been developed for the VSC-HVDC system to offer invariant stability to modeling uncertainties by [22]. Basically, SMC assumes perturbations to be bounded and the prior knowledge of these upper bounds is required. However, it may be difficult or sometimes impossible to obtain these upper bounds, thus the supreme upper bound is chosen to cover the whole range of perturbations. As a consequence, SMC based on this knowledge becomes over-conservative which

Sliding-Mode Perturbation Observer-Based Sliding-Mode Control for VSC-HVDC Systems

http://dx.doi.org/10.5772/intechopen.74717

21

During the past decades, several elegant approaches based on observers have been proposed to estimate perturbations, including the unknown input observer (UIO) [24], the disturbance observer (DOB) [25], the equivalent input disturbance (EID)-based estimation [26], enhanced decentralized PI control via advanced disturbance observer [27], the extended state observer (ESO)-based active disturbance rejection control (ADRC) [28], and practical multivariable control based on inverted decoupling and decentralized ADRC [29]. Among the above listed approaches, ESO requires the least amount of system information, in fact, only the system order needs to be known [30]. Due to such promising features, ESO-based control schemes have become more and more popular. Recently, ESO-based SMC has been developed to remedy the over-conservativeness of SMC via an online perturbation estimation. It observes both system states and perturbations by defining an extended state to represent the lumped perturbation, which can be then compensated online to improve the performance of system. Related applications can be referred to mechanical systems [31], missile systems [32], spherical

This chapter uses an ESO called sliding-mode state and perturbation observer (SMSPO) [35, 36] to estimate the combinatorial effect of nonlinearities, parameter uncertainties, unmodeled dynamics, and time-varying external disturbances existed in VSC-HVDC systems, which is then compensated by the perturbation observer-based sliding-mode control (POSMC). The motivation to use POSMC, in this chapter, rather than SMC and our previous work [35–37]

• The robustness of POSMC to the perturbation mostly depends on the perturbation compensation, while the ground of the robustness in SMC [18–22] is the discrete switching input. Furthermore, the upper bound of perturbation is replaced by the smaller bound of its estimation error, thus an over-conservative control input is avoided and the tracking

• POSMC can provide greater robustness than that of nonlinear adaptive control (NAC) [35, 36] and perturbation observer-based adaptive passive control (POAPC) [37] due to its

Compared to VC [11], POSMC can provide a consistent control performance under various operation condition of the VSC-HVDC system and improve the power tracking by eliminating the power overshoot. Compared to FLSMC [22], POSMC only requires the measurement of

may cause a poor tracking performance and undesirable control oscillations [23].

robots [33], and DC-DC buck power converters [34].

inherent property of disturbance rejection.

can be summarized as follows:

accuracy is improved.

The need for more secure power grids and ever-increasing environmental concerns continue to drive the worldwide deployment of high voltage direct current (HVDC) transmission technology, which enables a more reliable and stable asynchronous interconnection of power networks that operate on different frequencies [4]. HVDC systems use power electronic devices to convert alternative current (AC) into direct current (DC), they are an economical way of transmitting bulk electrical power in DC over long distance overhead line or short submarine cable, while advanced extruded DC cable technologies have been used to increase power transmissions by at least 50%, which is also an important onshore solution. HVDC enables secure and stable asynchronous interconnection of power networks that operate on different frequencies. Different technologies have been used to design two-terminal HVDC systems for the purpose of a point-to-point power transfer, such as line-commutated converter (LCC) based HVDC (LCC-HVDC) systems using grid-controlled mercury-arc valves or thyristors, capacitor-commutated converter (CCC)-based HVDC (CCC-HVDC) systems, or controlled series commutated converter (CSCC)-based HVDC (CSCC-HVDC) systems [5].

Voltage source converter-based high voltage direct current (VSC-HVDC) systems using insulated gate bipolar transistor (IGBT) technology have attracted increasing attentions due to the interconnection between the mainland and offshore wind farms, power flow regulation in alternating current (AC) power systems, long distance transmission [6], and introduction of the supergrid, which is a large-scale power grid interconnected between national power grids [7]. The main feature of the VSC-HVDC system is that no external voltage source is needed for communication, while active and reactive powers at each AC grid can be independently controlled [8, 9].

Traditionally, control of the VSC-HVDC system utilizes a nested-loop d-q vector control (VC) approach based on linear proportional-integral (PI) methods [10], whose control performance may be degraded with the change of operation conditions as its control parameters are tuned from one-point linearization model [11]. As VSC-HVDC systems are highly nonlinear resulting from converters and also operate in power systems with modeling uncertainties, many advanced control approaches are developed to provide a consistent control performance under various operation conditions, such as feedback linearization control (FLC) [12], which fully compensated the nonlinearities with the requirement of an accurate system model. Linear matrix inequality (LMI)-based robust control was developed in [13] to maximize the size of the uncertainty region within which closed-loop stability is maintained. In addition, adaptive backstepping control was designed to estimate the uncertain parameters by [14]. In [8, 9], power-synchronization control was employed to greatly increase the short-circuit capacity to the AC system. However, the aforementioned methods may not be adequate to simultaneously handle perturbations such as modeling uncertainties and time-varying external disturbances.

Based on the variable structure control strategy, sliding-mode control (SMC) is an effective and high-frequency switching control for nonlinear systems with modeling uncertainties and timevarying external disturbances. The main idea of SMC is to maintain the system sliding on a surface in the state space via an appropriate switching logic; it features the simple implementation, disturbance rejection, fast response, and strong robustness [15]. While the malignant effect of chattering phenomenon can be reduced by predictive variable structure [16] and self-tuning sliding mode [17], SMC has been applied on electrical vehicles [18], power converters [19], induction machines [20], wind turbines [21], etc. Moreover, a feedback linearization sliding-mode control (FLSMC) has been developed for the VSC-HVDC system to offer invariant stability to modeling uncertainties by [22]. Basically, SMC assumes perturbations to be bounded and the prior knowledge of these upper bounds is required. However, it may be difficult or sometimes impossible to obtain these upper bounds, thus the supreme upper bound is chosen to cover the whole range of perturbations. As a consequence, SMC based on this knowledge becomes over-conservative which may cause a poor tracking performance and undesirable control oscillations [23].

been fully exploited in many grids, such that a sustainable development can be achieved in future [2]. The problems and perspectives of converting present energy systems (mainly thermal and nuclear) into a 100% renewable energy system have been discussed with a conclusion that such idea is possible, which, however, raises that advanced transmission technologies are needed

The need for more secure power grids and ever-increasing environmental concerns continue to drive the worldwide deployment of high voltage direct current (HVDC) transmission technology, which enables a more reliable and stable asynchronous interconnection of power networks that operate on different frequencies [4]. HVDC systems use power electronic devices to convert alternative current (AC) into direct current (DC), they are an economical way of transmitting bulk electrical power in DC over long distance overhead line or short submarine cable, while advanced extruded DC cable technologies have been used to increase power transmissions by at least 50%, which is also an important onshore solution. HVDC enables secure and stable asynchronous interconnection of power networks that operate on different frequencies. Different technologies have been used to design two-terminal HVDC systems for the purpose of a point-to-point power transfer, such as line-commutated converter (LCC) based HVDC (LCC-HVDC) systems using grid-controlled mercury-arc valves or thyristors, capacitor-commutated converter (CCC)-based HVDC (CCC-HVDC) systems, or controlled

series commutated converter (CSCC)-based HVDC (CSCC-HVDC) systems [5].

while active and reactive powers at each AC grid can be independently controlled [8, 9].

modeling uncertainties and time-varying external disturbances.

Voltage source converter-based high voltage direct current (VSC-HVDC) systems using insulated gate bipolar transistor (IGBT) technology have attracted increasing attentions due to the interconnection between the mainland and offshore wind farms, power flow regulation in alternating current (AC) power systems, long distance transmission [6], and introduction of the supergrid, which is a large-scale power grid interconnected between national power grids [7]. The main feature of the VSC-HVDC system is that no external voltage source is needed for communication,

Traditionally, control of the VSC-HVDC system utilizes a nested-loop d-q vector control (VC) approach based on linear proportional-integral (PI) methods [10], whose control performance may be degraded with the change of operation conditions as its control parameters are tuned from one-point linearization model [11]. As VSC-HVDC systems are highly nonlinear resulting from converters and also operate in power systems with modeling uncertainties, many advanced control approaches are developed to provide a consistent control performance under various operation conditions, such as feedback linearization control (FLC) [12], which fully compensated the nonlinearities with the requirement of an accurate system model. Linear matrix inequality (LMI)-based robust control was developed in [13] to maximize the size of the uncertainty region within which closed-loop stability is maintained. In addition, adaptive backstepping control was designed to estimate the uncertain parameters by [14]. In [8, 9], power-synchronization control was employed to greatly increase the short-circuit capacity to the AC system. However, the aforementioned methods may not be adequate to simultaneously handle perturbations such as

Based on the variable structure control strategy, sliding-mode control (SMC) is an effective and high-frequency switching control for nonlinear systems with modeling uncertainties and timevarying external disturbances. The main idea of SMC is to maintain the system sliding on a surface

to realize this goal [3].

20 Perturbation Methods with Applications in Science and Engineering

During the past decades, several elegant approaches based on observers have been proposed to estimate perturbations, including the unknown input observer (UIO) [24], the disturbance observer (DOB) [25], the equivalent input disturbance (EID)-based estimation [26], enhanced decentralized PI control via advanced disturbance observer [27], the extended state observer (ESO)-based active disturbance rejection control (ADRC) [28], and practical multivariable control based on inverted decoupling and decentralized ADRC [29]. Among the above listed approaches, ESO requires the least amount of system information, in fact, only the system order needs to be known [30]. Due to such promising features, ESO-based control schemes have become more and more popular. Recently, ESO-based SMC has been developed to remedy the over-conservativeness of SMC via an online perturbation estimation. It observes both system states and perturbations by defining an extended state to represent the lumped perturbation, which can be then compensated online to improve the performance of system. Related applications can be referred to mechanical systems [31], missile systems [32], spherical robots [33], and DC-DC buck power converters [34].

This chapter uses an ESO called sliding-mode state and perturbation observer (SMSPO) [35, 36] to estimate the combinatorial effect of nonlinearities, parameter uncertainties, unmodeled dynamics, and time-varying external disturbances existed in VSC-HVDC systems, which is then compensated by the perturbation observer-based sliding-mode control (POSMC). The motivation to use POSMC, in this chapter, rather than SMC and our previous work [35–37] can be summarized as follows:


Compared to VC [11], POSMC can provide a consistent control performance under various operation condition of the VSC-HVDC system and improve the power tracking by eliminating the power overshoot. Compared to FLSMC [22], POSMC only requires the measurement of active and reactive power and DC voltage, which can provide a significant robustness and avoid an over-conservative control input as the real perturbation is estimated and compensated online. Four case studies are carried out to evaluate the control performance of POSMC through simulation, such as active and reactive power tracking, AC bus fault, system parameter uncertainties, and weak AC gird connection. Compared to the author's previous work on SMSPO [35, 36], a dSPACE simulator-based hardware-in-the-loop (HIL) test is undertaken to validate its implementation feasibility.

The rest of the chapter is organized as follows. In Section 2, the model of the two-terminal VSC-HVDC system is presented. In Section 3, POSMC design for the VSC-HVDC system is developed and discussed. Sections 4 and 5 present the simulation and HIL results, respectively. Finally, conclusions are drawn in Section 6.
