Optimal Voltage Control Research Articles

Coordinated Voltage Control Scheme for SEIG-Based Wind Park Utilizing Substation STATCOM and ULTC Transformer

This paper presents a coordinated voltage control scheme for improving the network voltage profile and for minimizing the steady-state loading of the STATCOM to effectively support the system during contingencies. The paper addresses implementation issues associated with primary voltage control and optimal tracking secondary voltage control for wind parks based on self-excited induction generators which comprise STATCOM and under-load tap changer (ULTC) substation transformers. The voltage controllers for the STATCOM and ULTC transformer are coordinated and ensure the voltage support. In steady-state operation, the voltage is controlled by only stepping the tap changer when the voltage is outside the deadband region of the ULTC to minimize the number of taps changes. Thus, the STATCOM will be unloaded and ready to react with higher reactive power margin during contingencies. In the paper, the effects of the short circuit ratio of the interconnection and the inherent communication delay between the wind park and the remote bus on the performance of the controllers and the maximum critical clearing time of fault are considered. Simulation results are presented to demonstrate the performance of the controllers in steady-state and in response to system contingency situations.

A Novel Modal Wavefront Reconstruction Algorithm based on PSO Algorithm

Abstract The nonlinear response and strong coupling of control channels of micromachined membrane deformable mirror (MMDM) devices make it difficult to obtain the desired optimal surface shape of the MMDM. In order to overcome these limitations, the wavefront modal reconstruction algorithm based on particle swarm optimization (PSO) is proposed, which is used to find the optimal control voltages of the MMDM. It is initialized with a population of random solutions and searches for optima by updating generations. In this way the objective function can be optimum and influence of phase aberration can be reduced to minimum. The simulation results show that this algorithm could find the optimal MMDM shape which was applied to correct phase aberration.

Voltage regulator placement in radial distribution system using plant growth simulation algorithm

This paper presents selection of optimal locations and sizes of voltage regulators in radial distribution system using Plant Growth Simulation Algorithm (PGSA). Voltage has always been considered as an integral part of the power system response. There are several factors, which contribute to voltage collapse such as increased loading on distribution feeders, reactive power constraints, on load tap changer dynamics and load characteristics. The proposed method for voltage regulator placement is suitable for large radial distribution network. The VR problem consists of two sub problems, that of optimal placement and optimal choice of tap setting. The proposed method deals with initial selection of voltage regulator buses by using power loss indices (PLI). The candidate node identification technique and Plant Growth Simulation Algorithm (PGSA) are used for optimal location and number along with tap setting of the voltage regulators that maintain a smooth voltage profile throughout the network. The aim of this paper is to obtain optimal voltage control with voltage regulators and then to decrease the total cost and losses, to obtain the maximum net savings. The effectiveness of the proposed method is illustrated with 33 bus and 69 bus radial distribution systems and these results are compared with Discrete Particle Swarm Optimization method. International Journal of Engineering, Science and Technology, Vol. 2, No. 6, 2010, pp. 207-217

A Novel Hybrid Optimization Algorithm Based on Multi-Agent and Particle Swarm

A novel multi-agent particle swarm optimization algorithm (MAI'SO) is proposed for optimal reactive power dispatch and voltage control of power system. The method integrates multi-agent system (MAS) and particle swarm optimization algorithm (PSO). An agent in MAI.SO represents a particle to PSO and a candidate solution to the optimization problem. All agents live in a lattice-like environment, with each agent fixed on a lattice-point. In order to decrease fitness value, quickly, agents compete and cooperate with their neighbors. and they can also use knowledge. Making use of these agent interactions and evolution mechanism of I.SO. MAPSO realizes the purpose of' minimizing the value of' objective function. MAPSO applied for optimal reactive power is evaluated on an IEEE 30-bus power system. It is shown that the proposed approach converges to better solutions much faster than the earlier reported approaches

Optimal voltage control in distribution systems using PV generators

Recently, renewable energy technologies such as wind turbine generators and photovoltaic systems have been introduced as distributed generation. The connection of large number of distributed generators causes voltage deviation beyond the statutory range in a distribution system. In this paper, a methodology for voltage control in proposed by using the tap changing transformers and the inverters interfaced with the distributed generators. In the proposed method, information of the voltage and power is collected via a communication network. Based on these information, the optimal reference values are calculated at the control center, and sent to the transformers and the inverters. The proposed method accomplishes a coordinated operation among the control equipments and reduces the voltage deviation. Effectiveness of the proposed method is verified by the numerical simulation results.

Optimal Seasonal Voltage Control in Rural Distribution Networks with Distributed Generators

Optimal Seasonal Voltage Control in Rural Distribution Networks with Distributed Generators This paper proposes a procedure for determining the optimal tap changer positions of off-voltage tap changing transformers in radial rural distribution networks in presence of distributed generators (DGs). The procedure is based on spatial network decomposition and as well as bringing down a branchy LV network to an equivalent line. Optimal voltage module values of PV nodes in the optimal seasonal control plan are determined by the application of a genetic algorithm. The proposed procedure is examined in two real distribution networks: a radial 33-node network with 11 DGs modelled as PQ nodes and a radial 40-node network with three DGs in total, two of which are modelled as PV nodes and one modelled as a PQ node.

Optimal voltage control in distribution systems with coordination of distribution installations

In recent years, distributed generations based on natural energy or co-generation systems are increasing due to global warming and reduction of fossil fuels. Many of the distributed generations are set up in the vicinity of customers, with the advantage that this decreases transmission losses and transmission capacity. However, output power generated from renewable energy such as wind power and photovoltaics, is influenced by weather conditions. Therefore if the distributed generation increases with conventional control schemes, the voltage variation in a distribution system becomes a serious problem. In this paper, an optimal control method of distribution voltage with coordination of distributed installations, such as On Load Tap Changer (OLTC), Step Voltage Regulator (SVR), Shunt Capacitor (SC), Shunt Reactor (ShR), and Static Var Compensator (SVC), is proposed. In this research, the communication infrastructure is assumed to be widespread in the distribution network. The proposed technique combines genetic algorithm (GA) and Tabu search (TS) to determine the control operation. In order to confirm the validity of the proposed method, simulation results are presented for a distribution network model with distributed (photovoltaic) generation.

Inter-signal timing skew compensation of parallel links with current-mode incremental signalling

This study proposes a new inter-signal timing skew compensation technique for parallel links with current-mode incremental signalling. The maximum deskew range is one bit time in both directions. Both the transmitters and receivers of the links are current-mode configured to take the advantages of current-mode signalling. Each receiver maps the direction of its channel current representing the logic state of the incoming data to two voltages of different values, enabling a convenient recovery of both the logic state and timing information of the received data. The feedback at the front-end of the receiver minimises the dependence of the input impedance of the receiver on the direction of the channel current so that data-dependent impedance mismatch is minimised. Inter-signal timing skews are compensated by inserting a delay line in each channel whose time delay is determined by the phase difference between the master sampling clock and data. A voltage replication circuit is proposed to copy the obtained optimal control voltage of the delay line of each channel so that the optimal deskew control voltage of the delay line is sustained. To assess the effectiveness of the proposed inter-signal timing skew compensation technique, a 2-bit 1 Gbytes/s parallel link has been implemented in UMC-0.13 mum 1.2 V CMOS technology and analysed using SpectreRF with BSIM3V3 device models. Simulation results demonstrate that the proposed inter-signal timing skew compensation method can compensate inter-signal timing skew up to one bit time in both directions.

Optimal Control of Voltages on Two-dimensional Electrophoresis Microchips

Abstract Based on the construction characteristics of two-dimensional microfluidic electrophoretic chips (2D-EMC), an equivalent resistance model of the microchips was established to calculate the rational ranges of voltages applied in the microchip reservoirs. Through the adjustment or optimization of electrophoretic voltages according to the measurements of electroosmotic flows, a group of optimal control voltages was obtained from the reasonable value scope of the reservoir voltages with the equivalent resistance model. The optimized control voltages were successfully applied to the two-dimensional separations of Arg and Gly derivatives on 2D-EMC with chemiluminescence detection. The experiment results indicate that this method significantly reduced the trial times needed for optimizing electrophoretic voltages of 2D-EMC separation.

Optimal Control of Voltage in Distribution Systems by Voltage Reference Management

AbstractRecently, renewable energy technologies such as wind turbine generators and photovoltaic (PV) systems have been introduced as distributed generations (DGs). Connections of a large amount of distributed generations may cause voltage deviation beyond the statutory range in distribution systems. A reactive power control of DGs can be a solution of this problem, and it also has a possibility to reduce distribution loss. In this paper, we propose a control methodology of voltage profile in a distribution system using reactive power control of inverters interfaced with DGs and tap changing transformers. In the proposed method, a one‐day schedule of voltage references for the control devices are determined by an optimization technique based on predicted values of load demand and PV power generation. Reactive power control of interfaced inverters is implemented within the inverter capacity without reducing active power output. The proposed method accomplishes voltage regulation within the acceptable range and reduction of distribution loss. The effectiveness of the proposed method is confirmed by simulations. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Optimal tracking secondary voltage control for the DFIG wind turbines and compensator devices

The optimal tracking secondary voltage control (OTSVC) is a new developed voltage control scheme for wind park based Doubly Fed Induction Generator (DFIG). The proposed controller is developed to achieve efficient voltage regulation and provided optimal reactive power compensation to the interconnected power system. The performance of the controller for enhancing the network voltage profile is compared with secondary voltage control, primary voltage control and optimal voltage profile obtained from the optimal power flow analysis. Furthermore, the OTSVC is employed for controlling wind park based DFIG and other sources of reactive power such as static var compensator ( svc). The dynamic performance of the controller for multiple sources of reactive power is tested for steady state operation and in response of system contingencies with considering the impact of communication time delays. Simulation results are presented and the capability of the controller in providing the desired reactive power compensation and voltage support for the power system are verified.

Synthetic Ciguatoxins Selectively Activate Nav1.8-derived Chimeric Sodium Channels Expressed in HEK293 Cells

The synthetic ciguatoxin CTX3C has been shown to activate tetrodotoxin (TTX)-sensitive sodium channels (Na(v)1.2, Na(v)1.4, and Na(v)1.5) by accelerating activation kinetics and shifting the activation curve toward hyperpolarization (Yamaoka, K., Inoue, M., Miyahara, H., Miyazaki, K., and Hirama, M. (2004) Br. J. Pharmacol. 142, 879-889). In this study, we further explored the effects of CTX3C on the TTX-resistant sodium channel Na(v)1.8. TTX-resistant channels have been shown to be involved in transducing pain and related sensations (Akopian, A. N., Sivilotti, L., and Wood, J. N. (1996) Nature 379, 257-262). Thus, we hypothesized that ciguatoxin-induced activation of the Na(v)1.8 current would account for the neurological symptoms of ciguatera poisoning. We found that 0.1 mum CTX3C preferentially affected the activation process of the Na(v)1.8 channel compared with those of the Na(v)1.2 and Na(v)1.4 channels. Importantly, without stimulation, 0.1 mum CTX3C induced a large leakage current (I (L)). The conductance of the I (L) calculated relative to the maximum conductance (G (max)) was 10 times larger than that of Na(v)1.2 or Na(v)1.4. To determine the molecular domain of Na(v)1.8 responsible for conferring higher sensitivity to CTX3C, we made two chimeric constructs from Na(v)1.4 and Na(v)1.8. Chimeras containing the N-terminal half of Na(v)1.8 exhibited a large response similar to wild-type Na(v)1.8, indicating that the region conferring high sensitivity to ciguatoxin action is located in the D1 or D2 domains.

A Voltage Control Method based on Constants of Four Terminals Network Modeling of Distribution Networks

In this paper, a new algorithm of optimal voltage control is proposed for the Distribution Automation System (DAS) based on constants of four terminal network modeling. In the proposed method, the voltage profiles along feeders are estimated from the measurement of the current and power factor by a Feeder Remote Terminal Unit (FRTU) installed at each node. Whenever the voltage profile violates the restriction, the voltage control strategy is applied to keep the voltage levels along the feeders within the pre-specified range through the modification and coordination of the transformer under-load tap changers (ULTC), step voltage regulator (SVR), as well as shunt condenser. In the case studies, the estimation and control of the voltages have been testified in a radial distribution system with 11 nodes.

Reactive power and voltage control based on general quantum genetic algorithms

This paper presents an improved evolutionary algorithm based on quantum computing for optimal steady-state performance of power systems. However, the proposed general quantum genetic algorithm (GQ-GA) can be applied in various combinatorial optimization problems. In this study the GQ-GA determines the optimal settings of control variables, such as generator voltages, transformer taps and shunt VAR compensation devices for optimal reactive power and voltage control of IEEE 30-bus and 118-bus systems. The results of GQ-GA are compared with those given by the state-of-the-art evolutionary computational techniques such as enhanced GA, multi-objective evolutionary algorithm and particle swarm optimization algorithms, as well as the classical primal-dual interior-point optimal power flow algorithm. The comparison demonstrates the ability of the GQ-GA in reaching more optimal solutions.

A Secondary Voltage Control Strategy for Transmission Level Interconnection of Wind Generation

This paper addresses implementation issues associated with secondary voltage control in a doubly-fed induction generator based wind farm. The effects of different system parameters on the performance of the control are considered, namely the short circuit ratio of the interconnection and the inherent communication delay between the wind park and the remote bus. In addition, a strategy for allocation reactive power requirements to each of the generators within the wind park is proposed. The system is developed and simulated for a wind park consisting of six wind generators connected to a typical transmission system. The paper proposes an optimal tracking secondary voltage control method developed to achieve effective voltage regulation, enhance the network voltage profile and provide optimal reactive power compensation to the interconnected power system. The performance of the controller is compared with secondary voltage control at one selected bus, primary voltage control and the optimal voltage profile obtained from the optimal power flow analysis. The performance of the controllers is tested for steady state operation and in response to system contingencies, taking into account the impact of communication time delays and short circuit ratio (SCRs). Simulation results are presented to demonstrate the capability of the controllers to provide the desired reactive power compensation and voltage support to the electric power grid.

Optimal Distribution Voltage Control and Coordination With Distributed Generation

In recent years, distributed generation, as clean natural energy generation and cogeneration system of high thermal efficiency, has increased due to the problems of global warming and exhaustion of fossil fuels. Many of the distributed generations are set up in the vicinity of the customer, with the advantage that this decreases transmission losses. However, output power generated from natural energy, such as wind power, photovoltaics, etc., which is distributed generation, is influenced by meteorological conditions. Therefore, when the distributed generation increases by conventional control techniques, it is expected that the voltage change of each node becomes a problem. Proposed in this paper is the optimal control of distribution voltage with coordination of distributed installations, such as the load ratio control transformer, step voltage regulator (SVR), shunt capacitor, shunt reactor, and static var compensator. In this research, SVR is assumed to be a model with tap changing where the signal is received from a central control unit. Moreover, the communication infrastructure in the supply of a distribution system is assumed to be widespread. The genetic algorithm is used to determine the operation of this control. In order to confirm the validity of the proposed method, simulations are carried out for a distribution network model with distributed generation (photovoltaic generation).

Secondary Voltage Regulation for Improved Power Plant Reactive Power Coordination

An inter-plant voltage control (IPVC) scheme is introduced for improving the voltage stability margin by coordinating reactive power reserves. The emphasis of the proposed scheme is on improvement of the system dynamic performance using an optimized voltage control of a series of power plants. Besides facilitating controllability by individual generator voltage regulators, this scheme also allows emergency boosting, power plant transmission-side voltage control, as well as coordination of closely-coupled power plants for reactive power reserve management. The IPVC is based on solving an optimal control problem with the dual objectives of minimizing pilot bus voltage deviations from their set-points, and of achieving similar reactive power loadings at control generators. Results, shown on two test systems, are very promising.

Voltage regulation in MV networks with dispersed generations by a neural-based multiobjective methodology

This paper puts forward the role of learning techniques in addressing the problem of an efficient and optimal centralized voltage control in distribution networks equipped with dispersed generation systems (DGSs). The proposed methodology employs a radial basis function network (RBFN) to identify the multidimensional nonlinear mapping between a vector of observable variables describing the network operating point and the optimal set points of the voltage regulating devices. The RBFN is trained by numerical data generated by solving the voltage regulation problem for a set of network operating points by a rigorous multiobjective solution methodology. The RBFN performance is continuously monitored by a supervisor process that notifies when there is the need of a more accurate solution of the voltage regulation problem if nonoptimal network operating conditions ( ex post monitoring) or excessive distances between the actual network state and the neuron's centres ( ex ante monitoring) are detected. A more rigorous problem solution, if required, can be obtained by solving the voltage regulation problem by a conventional multiobjective optimization technique. This new solution, in conjunction with the corresponding input vector, is then adopted as a new train data sample to adapt the RBFN. This online training process allows RBFN to (i) adaptively learn the more representative domain space regions of the input/output mapping without needing a prior knowledge of a complete and representative training set, and (ii) manage effectively any time varying phenomena affecting this mapping. The results obtained by simulating the regulation policy in the case of a medium-voltage network are very promising.

High-performance voltage control scheme for wind park integration

The design and implementation of a new control scheme for reactive power compensation and voltage regulation in the transmission system, as provided and controlled by a wind park is presented. It proposes an optimal tracking secondary voltage control scheme applied to doubly fed induction generator-based wind generators. The ability of the controller to regulate transmission network voltage profiles is demonstrated and compared with primary voltage control, an alternate secondary voltage control approach, and the voltage profile obtained from optimal power flow analysis. The dynamic performance of the controller is also validated in response to system contingencies, namely short circuits. The impact of communication time delays and of the short-circuit ratio on the dynamic performance of the voltage controller are considered. Results show that the controller properly regulates the voltage in steady state and performs properly during transients resulting from short circuits. Decoupling between primary and secondary loops should be applied to mitigate the effects of the time delay.

Improving the mixing performance of side channel type micromixers using an optimal voltage control model

Electroosmotic flow in microchannels is restricted to low Reynolds number regimes. Since the inertia forces are extremely weak in such regimes, turbulent conditions do not readily develop, and hence species mixing occurs primarily as a result of diffusion. Consequently, achieving a thorough species mixing generally relies upon the use of extended mixing channels. This paper aims to improve the mixing performance of conventional side channel type micromixers by specifying the optimal driving voltages to be applied to each channel. In the proposed approach, the driving voltages are identified by constructing a simple theoretical scheme based on a 'flow-rate-ratio' model and Kirchhoff's law. The numerical and experimental results confirm that the optimal voltage control approach provides a better mixing performance than the use of a single driving voltage gradient.