Proposed Power Control Scheme Research Articles

A novel power control scheme for distributed DFIG based on cooperation of hybrid energy storage system and grid-side converter

Due to the uncertainty of wind energy, the wind power is difficult to be dispatched and may cause the voltage fluctuations for distributed network. Therefore, a novel power control scheme is proposed to manage the output power of the distributed doubly-fed induction generator (DFIG) by cooperating the hybrid energy storage system (HESS). In the proposed scheme, the grid-side converter of DFIG is controlled to manage overall output power of the DFIG/HESS hybrid system in accordance to the power dispatching command. The HESS is utilized to deal with the power difference between DFIG generation power and the power dispatching command. The HESS is embedded in the DC-link bus of DFIG and is composed of superconducting magnetic energy storage and batteries. Additionally, in order to avoid HESS from overcharging and over-discharging, the pitch angle control and power dispatching command are adjusted by considering the state of charge (SOC) of HESS. Finally, the simulation model of distributed DFIG and HESS is built on the real-time digital simulation (RTDS) platform, and the simulation results validate the effectiveness and reliability of the proposed power control scheme.

Optimizing job shop scheduling with speed‐adjustable machines and peak power constraints: A mathematical model and heuristic solutions

AbstractThis paper addresses a job shop scheduling problem with peak power constraints, in which jobs can be processed once or multiple times on either all or a subset of the machines. The latter characteristic provides additional flexibility, nowadays present in many manufacturing systems. The problem is complicated by the need to determine both the operation sequence and starting time as well as the speed at which machines process each operation. Due to the adherence to renewable energy production and its intermittent nature, manufacturing companies need to adopt power‐flexible production schedules. The proposed power control strategies, that is, adjusting processing speed and timing to reduce peak power requirements may impact production time (makespan) and energy consumption. Therefore, we propose a bi‐objective approach that minimizes both objectives. A linear programming model is developed to provide a formal statement of the problem, which is solved to optimality for small‐sized instances. We also proposed a multi‐objective biased random key genetic algorithm framework that evolves several populations in parallel. Computational experiments provide decision and policymakers with insights into the implications of imposing or negotiating power consumption limits. Finally, the several trade‐off solutions obtained show that as the power limit is lowered, the makespan increases at an increasing rate and a similar trend is observed in energy consumption but only for very small makespan values. Furthermore, peak power demand reductions of about 25% have a limited impact on the minimum makespan value (4–6% increase), while at the same time allowing for a small reduction in energy consumption.

Unsupervised Deep Learning for Power Control of Cell-Free Massive MIMO Systems

The problem of power control for the uplink and the downlink in cell-free massive multiple-input multiple-output (CF mMIMO) systems is considered in this paper. In order to achieve a balance between the conflicting requirements of good performance levels and of low computational complexity, we employ unsupervised learning based on deep learning (DL). The proposed power control strategies can work using as input the large scale fading coefficients only and are capable to obtain very satisfactory performance levels, as compared to conventional, highly complex, optimization methods and to heuristic methodologies. Moreover, they can be used also in a user centric system wherein each mobile station is served by a subset of the active access points.

Interval type-2 fuzzy logic control for a space nuclear reactor core power system

The uncertain environment and delayed communications bring great challenges for the space nuclear reactor core power control. The imprecise knowledge about nonlinear and time varying parameters of the reactor make the problem further difficult. In this work, an anti-interference method is proposed for the core power control of space reactors. A new core power controller is designed to compensate the power deviation caused by model uncertainties and external disturbances. To further approximate nonlinear mapping functions between the control drum angle position and the deviation of the reactor core power, an interval type-2 fuzzy logic system is employed to deduce the correction of control drum angle position for its general approximation ability. Moreover, in order to solve control difficulties caused by physical constraints of the control drum and high stability requirements of the core power control system, an optimized iteration algorithm is proposed to ensure convergence to the optimal solution. A 1MWe space nuclear reactor is used as a reference object to carry out the research and verification of the newly proposed power control scheme. The numerical results verify the feasibility of the novel controller and show that load tracking performance of the system can be realized effectively.

An MPC based active and reactive power coordinated control strategy of PMSG wind turbines to enhance the support capability

As wind turbines are constantly replacing traditional units, it is becoming a consensus that wind turbines should participate in the grid support that was only responsible by traditional units in the past. In order to enhance the grid support capabilities (including active power support and reactive power support) of permanent magnet synchronous generator (PMSG) based wind turbines, this paper constructs an active and reactive power coordinated control strategy. Compared with the current active and reactive power coordinated control strategy of PMSG wind turbines, the method of the proposed one innovatively considers the climbing coordinated restriction between active and reactive power, flexible prioritization arrangement between active and reactive power, the accurate amplitude and climbing constraints of grid-side converters’ output voltage, and the model predictive control (MPC) technique. The simulation results verify that the proposed power control strategy can make PMSG wind turbines achieve excellent power output performance and thus better meet the requirements of power grid support.

Ambient Backscatter-Based Power Control Strategies for Spectrum Sharing Networks

Prior works on power control strategy need to estimate all users’ channel state information (CSI), which consumes both spectrum and time. Two efficient and low-complexity power control strategies, namely quality of experience (QoE) based power control scheme and distance based power control strategy, are proposed for an ambient backscatter based spectrum-sharing network. In the proposed power control schemes, there is no need to estimate all users’ CSI. In the QoE-based power control strategy, only the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> primary users with the highest priority feedback their CSI. We introduce an attenuation factor to reduce the transmit power to satisfy the interference threshold on primary users. Then, considering the short transmission distance of secondary backscatter communication and randomly distributed primary users, we propose the distance-based power control scheme, in which only the users within the backscatter distance need to feedback their CSI. Closed-form expressions for the outage probabilities of primary and secondary systems are derived over the Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${m}$ </tex-math></inline-formula> channels under the proposed two power control strategies. The system energy efficiency are also analyzed. Simulation results are conducted to verify the analytical results. Finally, outage performance and energy efficiency of the proposed schemes are compared with that of the existing nearest- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> users based power control strategy. It is shown that the proposed power control strategies have lower outage probabilities and higher energy efficiency.

Decoupled fractional-order harmonic filter for power quality enhancement of grid-connected DG units

The global expansion of power electronics interfaced distributed generator (DG) units has led to the incrementation of nonlinear loads in the distribution systems, which may impose negative effects on the power quality. To maintain the desired power quality while actively compensating the harmonics in the presence of frequency deviations, this work proposes a decoupled closed-loop fractional-order current controller that incorporates the harmonic alleviation with the DG power generation function. Accordingly, an optimal fractional-order proportional–integral–derivative (FOPID) is designed to control the DG unit fundamental current, while compensating the local nonlinear load harmonic current (LHC) effects. A noteworthy contribution of this paper is that the optimal control scheme delivers the desired performance without the need for LHC detection and effectively reduces the operational cost. Another contribution is the implementation of an optimal FOPI-based control scheme in the outer power control loop to extract the fundamental current reference with no phase-locked loop (PLL) components. This offers comprehensive solutions with several improvements, such as eliminating the power tracking steady-state error under fundamental current tracking errors and preventing harmonic disturbances from being imposed on the harmonic control by the power control part. The feasibility and effectiveness of the proposed power control scheme are validated in comparison with the conventional PI approach.

An Electrolytic Capacitor-Less PV Micro-Inverter Based on CLL Resonant Conversion With a Power Control Scheme Using Resonant Circuit Voltage Control Loops

A power control scheme with maximum power point tracking based on solely voltage feedback control loops is proposed in this paper for a dc/ac isolated high frequency PV micro-inverter. The presented power circuit topology consists of an integrated continuous conduction mode (CCM) boost converter with an asymmetrical pulse-witch modulation (APWM) controlled CLL step-up resonant converter and a half-bridge grid-side inverter. The presented topology is capable of achieving CCM input current and a wide range of zero voltage switching (ZVS) operation for the front-end stage. The proposed power control scheme, as well as the developed maximum power point tracking (MPPT) control technique utilize the resonant circuit’s resonant capacitor voltage and the APWM input voltage of the resonant circuit only to achieve MPPT and to control the active power of the overall system. By doing so, a large electrolytic input filtering capacitor is not needed. This allows small size film capacitors to be used and improves the system lifetime expectancy. The theoretical analysis and the detailed descriptions of the proposed power control scheme for the presented PV micro-inverter are provided. Simulation and hardware results on a 220 W with 120 Vac, 60 Hz output hardware prototype are presented to demonstrate the performance of the proposed PV inverter system.

Performance Analysis and Optimization of NOMA-Based Cell-Free Massive MIMO for IoT

This article investigates the performance of nonorthogonal multiple access (NOMA)-based cell-free massive multiple-input–multiple-output (mMIMO) for the Internet of Things (IoT) considering spatially correlated Rician fading channels. The exact closed form of downlink spectral efficiency (SE) and energy efficiency expressions is derived with three estimators and the maximum ratio transmission by taking the impacts of imperfect successive interference cancellation and pilot contamination into account. Subsequently, the performance of a local-MMSE precoder with the three aforementioned estimators is analyzed. Then, a large-scale fading-based user pairing scheme is proposed to further analyze the system SE. Besides, we formulate the optimum power control design as a max–min problem and a computational efficient suboptimal algorithm is proposed based on the successive convex approximation. Furthermore, our results reveal that the magnitude of the spatial correlation negligibly effects the SE in spatially correlated Rician fading channels. Then, numerical results confirm the positive effect of the proposed power control scheme. Also, our results further illustrate that NOMA-based cell-free mMIMO for IoT provides significant performance gain compared with its counterpart deploying conventional orthogonal multiple-access schemes.

An Opportunistic Power Control Scheme for Mitigating User Location Tracking Attacks in Cellular Networks

Cellular networks have been successfully evolved over the decades. Especially, Long-Term Evolution (LTE) has been exceedingly successful and the security threats against LTE systems have increased rapidly. Particularly, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">tracking</i> LTE user devices has been shown to be effective as the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">temporary</i> user identifiers (IDs) are easily extracted and used to locate targeted devices by passive eavesdroppers. We notice that naive approaches, such as frequent updates of temporary user IDs, are <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">insufficient</i> to mitigate user-tracking attacks since the new and old temporary IDs for the same user device are easily <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">linkable</i> by adversaries who can measure the wireless channel characteristics between the user device and herself. In this paper, we propose an opportunistic uplink power control scheme to minimize the probability of successful user tracking by an adversary whose location is unknown. We devise the notion of average inference error probability in order to measure the level of users’ location privacy. Moreover, we derive the closed-form expression of the approximated average inference error probability and formulate an optimization problem to maximize the average inference error probability under a constraint of an allowable power budget for each user. Against a passive adversary, our proposed power control scheme effectively degrades an adversary’s inference ability by 50% when 10 users are scheduled in each transmission time slot, which will lead to almost 100% inference error at the adversary over multiple time slots.

Steady-State Rate-Optimal Power Adaptation in Energy Harvesting Opportunistic Cognitive Radios With Spectrum Sensing and Channel Estimation Errors

We consider an uplink opportunistic cognitive radio network, operating in frequency division duplexing (FDD) mode and consisting of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N_{\mathrm {u}}$ </tex-math></inline-formula> secondary users (SUs) and an access point (AP), that can access a spectrum band licensed to a primary user. Each SU is capable of harvesting energy, and is equipped with a finite size battery, for energy storage. The SUs operate under a time-slotted scheme, where each time slot consists of three non-overlapping phases: 1) spectrum sensing phase; 2) channel probing phase; and 3) data transmission phase. The AP feeds back its estimates of fading coefficients of SUs–AP link to SUs. To strike a balance between the energy harvesting and the energy consumption, we propose a parametrized power control strategy that allows each SU to adapt its power, according to the feedback information and its stored energy. We establish a lower bound on the achievable uplink sum-rate of SUs–AP links, in the presence of both spectrum sensing and channel estimation errors. We optimize the parameters of the proposed power control strategy, such that the derived uplink sum-rate lower bound is maximized, subject to an interference constraint. Via simulations, we corroborate our analysis and explore spectrum sensing-channel probing-data transmission trade-offs.

Uplink transmission design for crowded correlated cell-free massive MIMO-OFDM systems

In cell-free massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, user equipments (UEs) are served by many distributed access points (APs), where channels are correlated owing to finite angle-delay spread in realistic outdoor wireless propagation environments. Meanwhile, the number of UEs is growing rapidly for future fully networked society. In this paper, we focus on the uplink transmission design in crowded correlated cell-free massive MIMO-OFDM systems with a limited number of orthogonal pilots. For the pilot transmission phase, we identify active UEs based on non-orthogonal pilot phase shift hopping patterns and non-orthogonal adjustable phase shift pilots (APSP). We derive a closed-form expression of mean square error of channel estimation (MSE-CE) and obtain an optimal condition for minimizing MSE-CE. According to this condition, the APSP set allocation scheme is proposed. Furthermore, for the data transmission, the max-min power control algorithm is devised to maximize the minimum spectral efficiency (SE) lower bound among active UEs. Simulation results indicate significant performance gains in terms of MSE-CE for the proposed APSP set allocation scheme. The proposed power control scheme can further improve the minimum SE among active UEs. Hence, they are crucial for crowded correlated cell-free massive MIMO-OFDM systems.

An augmented state observer-based sensorless control of grid-connected inverters under grid faults

The increasing integration of grid-connected renewable energy systems impose major challenges of reliability and power quality within power grid system. Grid-connected systems must ensure grid stability, accommodate low voltage ride-through capability, and comply with grid codes under unbalanced voltage dips to avoid any grid-disconnection. In this context, this paper proposes a novel control strategy to improve grid-connected inverter control under unbalanced grid voltage conditions. Positive and negative sequence components of grid voltage are estimated using an augmented state and disturbance observer. The estimated values of grid voltage and phase-angle are used to protect the inverter from any over-current tripping even at unbalanced grid voltage dips. This can be achieved by reducing active power and suppressing its fluctuations with new current references, which are obtained in the synchronous reference frame according to grid codes. The effectiveness and flexibility of the proposed power control strategy have been demonstrated by numerical simulation and validated by experiments in both balanced and unbalanced grid fault conditions.

Direct Parallel and Hybrid Power Control Scheme of a Low-Power PV and Piezoelectric Energy Harvesting Module

This paper presents a novel direct parallel power control scheme with independent current paths for the proposed hybrid energy-harvesting system that consists of a low-power photovoltaic panel, a piezoelectric harvesting module, and an energy storage system. A battery is connected to store the generated power from the two renewable power sources to provide a continuous power supply for the users. The designed power converter controls both battery state and power supply without any power conditioning system. To achieve this, a low-power DC–DC converter with battery charging function and control algorithm is designed for the hybrid power source. Therefore, in the proposed system, no additional battery charge controller is required. To control the battery, however, an additional current sensor to detect the battery power is simply added to each DC–DC converter. In the proposed power control scheme and controller, each power input, output, and the combined power flow are connected with neither communication protocols nor additional controller. Moreover, the converters can adjust the supplied power for parallel power-sharing. For maximum output current protection in each converter and constant current control for the battery, a hybrid power connection and its related current path are also proposed in this paper. The effectiveness of the proposed hybrid power system and the direct parallel power control scheme was verified through experiments.

A Power Control Scheme to Exploit Capture Effect with Fairness Consideration in WLAN

In this paper, we develop a physical/medium-access-control cross layer design to improve system throughput with the consideration of fairness for IEEE 802.11 WLAN. From PHY layer perspective, when an access collision occurs, the access point can still decode the corresponding data successfully if the received signal to interference plus noise ratio is larger than the threshold. This phenomenon is referred to as the capture effect. To improve system throughput, this work proposes a Differential Reception-Power Power Control scheme to take advantage of the capture effect. However, the proposed power control scheme cannot provide a fair transmission environment even though it improves the system throughput. To resolve this problem, this work proposes two methods: the adjustment of contention window size and the modification of probability mass function for the selection of the backoff value. The simulation results demonstrate that the proposed schemes can not only remarkably improve system throughput, but also provide a fair transmission environment.

Radio Resource Allocation and Power Control Scheme in V2V Communications Network

Reasonable resource management scheme is the premise to ensure system reliability and practicability of vehicle-to-vehicle (V2V) communications network. In this paper, spectrum resource allocation and power control scheme is studied. Firstly, the problem of resource block (RB) sharing is considered. Assuming that each V2V link occupies at most one resource block while multiple links can share the same RB. In this work, a factor graph model is proposed corresponding to the RB allocation problem through function mapping. Therefore, the RB allocation problem is equivalent to studying the message update and belief inference problem on the factor graph model. We propose a Belief Propagation based on Real-time Update of Messages (BPRUM) algorithm, in which the message of each node is calculated based on the new messages of other nodes rather than the messages calculated in the last iteration. Secondly, after the RB allocation is completed, a power control scheme under the maximum power limit is proposed by utilizing the Lagrange dual decomposition. And the total throughput of the system is maximized by using the proposed power control scheme. Simulation results show that the resource allocation and power control scheme can achieve a significant increment in spectrum utilization and throughput of the V2V communications network.

Performance analysis of Multi-Phase cooperative NOMA systems under passive eavesdropping

A key feature of the non-orthogonal multiple access (NOMA) technique is that users with better channel conditions have prior knowledge about the information of other weak users. Given this prior knowledge, the idea that a strong user can serve as a relay node for other weak users in order to improve their performance, is known as cooperative NOMA. In this paper, we study the physical layer security of such a cooperative NOMA system. In order to reduce the complexity of the analytical process, the considered system in this paper has three users, in which the performance of the weaker users are enhanced by the stronger users. Given that there is an eavesdropper in the system that can hear all the transmissions, we study the secrecy performance of all the users. More specifically, we make an attempt to derive the ergodic secrecy capacity (ESC) and secrecy outage probability (SOP) of all the users. Due to the intractable nature of the exact analysis for the weak users, we provide the closed form expressions of the ESC and SOP for these users at the high SNR regime, while providing the exact analysis for the strongest user. Targeting on the optimality, we further reveal that better secrecy performance of the system is achievable through an appropriate power control mechanism. Finally, based on the analytical methodology of the three-user cooperative system, we provide insightful observations on the performance (in terms of ESC and SOP) of a multi-phase cooperative NOMA system with N users at the high SNR regime. Through rigorous numerical simulations, we verify the correctness of our analytical derivations under different practical scenarios while providing evidence of achieving optimal secrecy performance with the proposed power control scheme.

Multiobjective Beamforming Power Control for Robust SINR Target Tracking and Power Efficiency in Multicell MU-MIMO Wireless System

This study proposes a multiobjective beamforming power control scheme to achieve the robust quality of service (QoS), the optimal signal-to-interference-plus-noise ratio (SINR) target tracking and the minimum average power consumption simultaneously in multicell multiuser MIMO (multicell MU-MIMO) wireless system with imperfect channel. The advantages of the proposed multiobjective beamforming power control optimization method are threefold. First, the proposed power control scheme can simultaneously achieve three objectives as follows: 1) the optimal H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> robust SINR target tracking performance, 2) the optimal H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> SINR target tracking performance, and 3) the minimum average power consumption in the multicell MU-MIMO wireless system. The proposed multiobjective optimization problem (MOP) is equivalently derived as aMOP by minimizing their corresponding upper bounds under the constraint of a set of linear matrix inequalities (LMIs). Second, without the requirement of statistical information and the norm-bounded condition of the channel uncertainty, the effect of inter-cell interference, intra-cell interference, channel uncertainty, round trip delay, and noise can be efficiently attenuated by the proposed robust SINR target tracking method. Third, through the proposed LMIs-constrained multiobjective evolution algorithm (MOEA), the designer can obtain Pareto optimal solutions efficiently with a good distribution along the Pareto front to achieve the proposed multiobjective power control design. Several simulation examples with the proposed multiobjective control scheme are produced with favourable results under the guarantee of the theoretical analysis.

Efficient Angle-Domain Processing for FDD-Based Cell-Free Massive MIMO Systems

Cell-free massive MIMO communications is an emerging network technology for 5G wireless communications wherein distributed multi-antenna access points (APs) serve many users simultaneously. Most prior work on cell-free massive MIMO systems assume time-division duplexing mode, although frequency-division duplexing (FDD) systems dominate current wireless standards. The key challenges in FDD massive MIMO systems are channel-state information (CSI) acquisition and feedback overhead. To address these challenges, we exploit the so-called angle reciprocity of multipath components in the uplink and downlink, so that the required CSI acquisition overhead scales only with the number of served users, and not the number of AP antennas nor APs. We propose a low complexity multipath component estimation technique and present linear angle-of-arrival (AoA)-based beamforming/combining schemes for FDD-based cell-free massive MIMO systems. We analyze the performance of these schemes by deriving closed-form expressions for the mean-square-error of the estimated multipath components, as well as expressions for the uplink and downlink spectral efficiency. Using semi-definite programming, we solve a max-min power allocation problem that maximizes the minimum user rate under per-user power constraints. Furthermore, we present a user-centric (UC) AP selection scheme in which each user chooses a subset of APs to improve the overall energy efficiency of the system. Simulation results demonstrate that the proposed multipath component estimation technique outperforms conventional subspace-based and gradient-descent based techniques. We also show that the proposed beamforming and combining techniques along with the proposed power control scheme substantially enhance the spectral and energy efficiencies with an adequate number of antennas at the APs.

Power Control for Two-Way AF Relay Assisted D2D Communications Underlaying Cellular Networks

As a key technology of the 5G communication system, device-to-device (D2D) communications have drawn significant research interests. However, the advantage of D2D communications may be limited when D2D users are far away from each other or the communication environments are harsh. In order to extend the range of D2D communications, a promising way is to use relaying technique to assist the communications. In this paper, we use a two-way amplify-and-forward (AF) relay to assist the underlay D2D communications and investigate the power control problem. Specifically, we formulate the power control problem as the optimization of the performance of the D2D link while fulfilling the quality-of-service (QoS) requirement of the cellular link. Two optimization objectives are considered for the D2D link, i.e., maximization of the minimum SINR at D2D users and maximization of the sum-rate of D2D users. For the first optimization objective, we can compare the possible optimal solutions for the three boundary conditions and obtain the optimal solutions. For the second optimization objective, we can convert the objective function into a concave function based on difference of convex (D. C.) structure, and use an iterative algorithm to solve the optimization problem. The simulation results show that the proposed power control scheme can improve the performance of the D2D link.