Optimal Power Control Research Articles

Energy-efficient transmission policies for the linear quadratic control of scalar systems

This paper considers controlled scalar systems relying on a lossy wireless feedback channel. In contrast with the existing literature, the focus is not on the system controller but on the wireless transmit power controller that is implemented at the system side for reporting the state to the controller. Such a problem may be of interest, e.g., for the remote control of drones, where communication costs may have to be considered. Determining the power control policy that minimizes the combination of the dynamical system cost and the wireless transmission energy is shown to be a non-trivial optimization problem. It turns out that the recursive structure of the problem can be exploited to determine the optimal power control policy. As illustrated in the numerical performance analysis, in the scenario of a dynamics without perturbations, the optimal power control policy consists in decreasing the transmit power at the right pace. This allows a significant performance gain compared to conventional policies such as the full transmit power policy or the open-loop policy.

Reactive Power Optimization Control for Multi-Energy System Based on Pressure Limit of Hot and Gas Pipe Network

Reactive Power Optimization Control for Multi-Energy System Based on Pressure Limit of Hot and Gas Pipe Network

Optimization of the Structure of Power System Multi-Agent Control

The article provides an overview of the application of multi-agent control, provides a classification of multi-agent system architectures, and analyzes existing methods for constructing the structure of multi-agent control in the electric power industry. A method for constructing an optimal structure of multi-agent optimal control is proposed. A field of applications of proposed method for a multi-agent voltage and reactive power optimal control in a power system is discussed. The proposed method of optimal design of multi-agent power system control structure can be applied to various objective function of optimization. The application of multi-agent control for automatic voltage and reactive power control in the power system is currently being researched.

Coordinated energy management for an islanded microgrid with multi-energy and multi-storage units

Battery energy storage system is an attractive solution for stand-alone microgrid to make up the intermittent power of renewable energy sources. However, most studies on energy management are focused on the one-battery-unit condition while two or more battery units are recommended for system redundancy. In this paper, a coordinated energy management scheme has been proposed for an islanded microgrid, which consists of multiple renewable energy sources, battery energy storage units with different capacity and auxiliary sources such as diesel generators. The scheme aims at global optimization for power control as well as the improvement of security and economy of system, which takes into account both the state of charge (SOC) constraint of battery units and the global optimization of maximum available power of distributed generations. In order to achieve the SOC balance, the idea of hierarchical processing is adopted that the multi-battery system has been classified into various charging/discharging priority based on the SOC and capacity of single unit. Furthermore, the maximal utilization of renewable energy and the minimal run time of auxiliary units are realized under the premise of satisfying the load demand. The effectiveness and functions of the proposed energy management scheme is verified by simulation results.

Coordinated optimal control of active power of wind farms considering wake effect

In a large-scale wind farm, under the influence of the wake effect, the single-machine maximum power extraction control strategy would not be able to function at the ideal optimal value. It is important to study the coordinated operation strategy of the wind farm under the wake effect to improve the output power of wind farms and improve the economic benefit. In this paper, a practical wake model called the PARK model is used and a wake superposition model based on energy balance is derived. Based on these models, an optimization problem is formulated to maximize the output power of the wind farm considering the wake effect. Taking the Horns Rev offshore wind farm as an example, the stochastic points method, particle swarm optimization, and the pattern search algorithm are implemented and compared with the single-machine maximum power extraction algorithm. Test results show that the particle swarm optimization and the pattern search algorithm have better performance. The output power of the wind farm increases by about 10 percent. The particle swarm optimization requires less computation while the pattern search algorithm obtains better and more practical results. Finally, the pattern search algorithm is used to improve economic benefits under different wind conditions.

Review on Reactive Power and Voltage Optimization of Active Distribution Network with Renewable Distributed Generation and Time-Varying Loads

With a high proportion of renewable distributed generation and time-varying load connected to the distribution network, great challenges have appeared in the reactive power optimization control of the active distribution networks. This paper first introduces the characteristics of active distribution networks, the mechanism and research status of wind power, photovoltaic, and other renewable distributed generators, and time-varying loads participating in reactive power and voltage optimization. Then, the paper summarizes the methods of reactive power optimization and voltage regulation of active distribution network, including multi-timescale voltage optimization, coordinated optimization of network reconfiguration and reactive power optimization, coordinated optimization of active and reactive power optimization based on model predictive control, hierarchical and zoning control of reactive power, and voltage and power electronic switch voltage regulation. The pros and cons of the reactive power optimization algorithms mentioned above are summarized. Finally, combined with the development trend of the energy Internet, the future directions of reactive power and voltage control technology in the active distribution network are discussed.

Optimal constant power control of wind turbine generators based on Takagi-Sugeno fuzzy model

Resource shortages and environmental pollution of the world are becoming more and more serious, wind Turbine generation as a kind of clean energy power generation has attracted much attention. The difficulty of wind power generation lies in the randomness of natural wind energy, which leads to the instability of the output power of Wind Turbine Generators (WTGs). The traditional variable pitch controller cannot realize global precision control of the wind power system. To solve the problem, this paper combines Takagi-Sugeno (T-S) fuzzy model with optimal control theory to design a robust controller. The unique novelty of the controller is that when the wind speed is higher than the rated, no matter how much the wind speed is, even if it is far from the balance point of the system, the controller can make the output power at a constant value, that is, increase the global stability of the wind power system. Specifically, the wind power system was divided into several linear subsystems, and the state feedback controller of each subsystem was designed through optimal control. Then, the subsystem controllers were merged by superposing membership functions, forming a controller of the entire system. Finally, wind turbine generators (WTGs) were modeled and simulated in Matlab/Simulink. The results show that the proposed controller kept the output power of WTGs constant under the global step wind of 13–25 m/s and the stochastic wind of 14–15 m/s. Our design enables the precision control at any wind speed, and improves the stability of power output of WTGs.

Integration of Distributed Energy Resources and EV Fast-Charging Infrastructure in High-Speed Railway Systems

Low carbon emission transportation is attracting global attention where electric railway power systems (ERPS) and electric vehicles (EVs) act as a load. Besides the main utility grid, renewable energy sources (RES) including photovoltaic (PV) panels and wind turbines are implemented to supply the loads fully or partially. In this paper, a novel smart DC catenary system is proposed in which renewable sources, storage systems, and DC fast-charging stations are connected to the overhead DC catenary line of the high-speed railway power system. The generated power from renewable sources and consumed power by charging stations are processed by their dedicated DC-DC power electronics converters. Furthermore, a storage system is used as a backup system not only for the case of blackouts but also because of the intermittent nature of renewable energy sources to supply the loads continuously. The paper presents an optimal power control for various parts and a power management system (PMS) that manages the power flow from wind-PV-storage system to EV-ERPS system. The proposed system has been investigated using a real Italian Rome-Florence 3 kV high-speed line as a case study with real data of ERPS load. The EV fast-charging station power demand, wind speed, solar irradiance, and temperature were recorded for 24 h in order to provide us with realistic output data. The simulation results obtained by MATLAB/Simulink are presented to validate the effectiveness of the proposed system.

Modeling and Power Optimization Control of Tidal Energy Systems

As interest in emergency power has increased, research on engine generators has been actively conducted. Permanent magnet synchronous generators (PMSGs) are suitable for small-capacity engine generators because they have higher efficiency and faster response than other motors. In this paper, the static and dynamic characteristics of the tidal turbine have been modeled and implemented experimentally. The rotational speed of the PMSG is regulated to extract the generator maximum power at a variable tidal velocity using the conventional optimum tip-speed ratio method. has been implemented to the proposed tidal power system since it is a simple method. The performance of the PMSG in the tidal power system has been investigated at different tidal speeds. The experimental results have validated the efficiency of the proposed controller to extract the maximum power point.

Minimum Length Scheduling for Multi-Cell Full Duplex Wireless Powered Communication Networks.

Wireless powered communication networks (WPCNs) will be a major enabler of massive machine type communications (MTCs), which is a major service domain for 5G and beyond systems. These MTC networks will be deployed by using low-power transceivers and a very limited set of transmission configurations. We investigate a novel minimum length scheduling problem for multi-cell full-duplex wireless powered communication networks to determine the optimal power control and scheduling for constant rate transmission model. The formulated optimization problem is combinatorial in nature and, thus, difficult to solve for the global optimum. As a solution strategy, first, we decompose the problem into the power control problem (PCP) and scheduling problem. For the PCP, we propose the optimal polynomial time algorithm based on the evaluation of Perron–Frobenius conditions. For the scheduling problem, we propose a heuristic algorithm that aims to maximize the number of concurrently transmitting users by maximizing the allowable interference on each user without violating the signal-to-noise-ratio (SNR) requirements. Through extensive simulations, we demonstrate a 50% reduction in the schedule length by using the proposed algorithm in comparison to unscheduled concurrent transmissions.

Millimeter Wave MIMO-OFDM With Index Modulation: A Pareto Paradigm on Spectral- Energy Efficiency Trade-Off

Multiple-input multiple-output orthogonal frequency division multiplexing with index modulation (MIMO-OFDM-IM) has recently received increased attention, due to the potential advantage to balance the trade-off between spectral efficiency (SE) and energy efficiency (EE). In this paper, we investigate the application of MIMO-OFDM-IM to millimeter wave (mmWave) communication systems, where a hybrid analogy-digital (HAD) beamforming architecture is employed. Taking advantage of the Pareto-optimal beam design, we propose a feasible solution to approximately achieve a globally Pareto-optimal trade-off between SE and EE, and the collision constraints of the multi-objective optimization problem (MOP) can be solved efficiently. Correspondingly, the MOP of SE-EE trade-off can be converted into a feasible solution for energy-efficient resource usage, by finding the Pareto-optimal set (POS) towards the Pareto front. This combinatorial-oriented resource allocation approach on the SE-EE relation considers the optimal beam design and power control strategies for downlink multi-user mmWave transmission. To ease the system performance evaluation, we adopt the Poisson point process (PPP) to model the mobile data traffic, and the evolutionary algorithm is applied to speed up the search efficiency of the Pareto front. Compared with benchmarks, the experimental results collected from extensive simulations demonstrate that the proposed optimization approach is vastly superior to existing algorithms.

A Design and Modelling of PV-Diesel Hybrid Energy System with Fuzzy Logic Controller

— Renewable energy, such as wind and photovoltaic arrays, has become the core energy in micro-grids used for supplying remote areas and areas suffering from electricity outages. Many limitations, such as weather fluctuations and low efficiency, lead to designing and developing a hybrid energy system. The integration of photovoltaic arrays and diesel gensets has become one of the most common approaches to generating electricity for remote communities. Although the integration of photovoltaic arrays and diesel gensets has the potential to reduce the cost of electricity production by harnessing free energy from the sun to reduce the power generated by diesel engines, it tends to complicate the control of the entire system due to the intermittent nature of the renewable energy sources and changing load demand. This paper proposes a fuzzy logic controller of PV-Diesel hybrid energy system, which is used as an effective tool in facilitating optimum power-sharing between the PV power source, charging, and discharging batteries and diesel generator as a backup based on the dynamics of the available PV energy at any time. Optimizing power control in the PV-Diesel hybrid energy system is key to minimizing the cost of power generation and maximizing the overall efficiency of the PV-Diesel hybrid energy system. The MATLAB-Simulink is used to design the fuzzy logic controller of the PV-Diesel hybrid energy system and to validate its performance. Five scenarios during the day have been tested to show the performance of the fuzzy logic controller. The results showed the accurate controlling of the power flow in the PV-Diesel hybrid system and the power saved about 2%.

Quantum evolutionary algorithm based power optimization control strategy for China initiative accelerator driven subcritical system

The power optimization control strategy for China initiative Accelerator Driven subcritical System (CiADS), which focuses on the study of dynamic features and the stable operation of coupling nuclear system, is one of the most important research topics for the current engineering stage that is expected to be completed in the year 2025. However, the traditional way in handling the power control problem was carried out by specialists with transcendental knowledge and experiences, which has been believed as the high labor intensity and the brute force trial-and-error process. In this context, the Quantum Evolutionary Algorithm (QEA) has been employed to deal with the CiADS power optimization control strategy in order to fulfill the adaptive searching procedure continuously and automatically. The manipulation of proton beam intensity has been used as the main control approach, and the physical model in describing the dynamic characteristics of power control system has been constructed in coupling the lumped parameter method and the point reactor kinetics method. In addition, the logical structure of Proportional Integral Derivative (PID) controller has been established for the power control process, and the QEA has been adopted to obtain the suitable set of parameters in the PID controller. Finally, the performance of the optimization method has been verified in the predefined control scenarios, and all the numerical results show that the control method has the applicability and feasibility in solving the CiADS power control problems.

Dynamic Divide Grouping Non-Orthogonal Multiple Access in Terrestrial-Satellite Integrated Network.

Non-orthogonal multiple access (NOMA) has been extensively studied to improve the performance of the Terrestrial-Satellite Integrated Network (TSIN) on account of the shortage of frequency band resources. In this paper, the terrestrial network and satellite network synergistically provide complete coverage for ground users, and based on the architecture, we first formulate a constrained optimization problem to maximize the sum rate of the TSIN under the limited spectrum resources. As the terrestrial networks and the satellite network will cause interference to each other, we first investigate the capacity performance of the terrestrial networks and the satellite networks separately, in which the optimal power control factor expression is derived. Then, by constructing the relationship model between user elevation angle, beam angle and distance, we develop a dynamic group pairing schemes to ensure the effective pairing of NOMA users. Based on the user pairing, to obtain the optimal resource allocation, a joint optimization algorithm of power allocation, beam channel and base station channel resource is proposed. Finally, simulation results are provided to evaluate the user paring scheme as well as the total system performance, in comparison with the existing works.

A Multi-Period Optimal Reactive Power Dispatch Approach Considering Multiple Operative Goals

The optimal reactive power dispatch (ORPD) problem plays a key role in daily power system operations. This paper presents a novel multi-period approach for the ORPD that takes into account three operative goals. These consist of minimizing total voltage deviations from set point values of pilot nodes and maneuvers on transformers taps and reactive power compensators. The ORPD is formulated in GAMS (General Algebraic Modeling System) software as a mixed integer nonlinear programming problem, comprising both continuous and discrete control variables, and is solved using the BONMIN solver. The most outstanding benefit of the proposed ORPD model is the fact that it allows optimal reactive power control throughout a multi-period horizon, guaranteeing compliance with the programmed active power dispatch. Additionally, the minimization of maneuvers on reactors and capacitor banks contributes to preserving the useful life of these devices. Furthermore, the selection of pilot nodes for voltage control reduces the computational burden and allows the algorithm to provide fast solutions. The results of the IEEE 118 bus test system show the applicability and effectiveness of the proposed approach.

Internal model control based proportional-integral controller with class topper optimization for power control of molten salt breeder reactor core

Internal model control (IMC) method is based on mathematical process model to design the controller. In IMC method, the approximated object model is parallelized with the actual model. The inverse of invertible part of the approximated dynamic model and a low pass filter is considered in the proposed controller design. As an IMC approach has an intuitive design with simple structure and it does not need an accurate model of the object, to explore its application in power control, molten salt breeder reactor (MSBR) core is chosen. A proportional-integral (PI) controller based on IMC technology is designed to control core power of MSBR. The filter constant of IMC technology is optimized with Class topper optimization (CTO) algorithm which improves robustness of the control scheme. Power control of MSBR core is studied for load tracking with step disturbance. This study shows that core power is controlled by CTO based IMC-PI controller.

Loss of energy in electrical networks with capacitor banks under optimal reactive power control

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Optimization of Rate Allocation and Power Control for Rate Splitting Multiple Access (RSMA)

In this paper, the sum-rate maximization problem is studied for wireless networks that use downlink rate splitting multiple access (RSMA). In the considered model, the base station (BS) divides the messages that can be transmitted to its users into a “private” part and a “common” part. Here, the common message is a message that multiple users want to receive and the private message is a message that is dedicated to only a specific user. The RSMA mechanism enables a BS to adjust the split of common and private messages so as to control the interference by decoding and treating interference as noise and, thus optimizing the data rate of users. To maximize the users' sum-rate, the network can determine the rate allocation for the common message to meet the rate demand, and adjust the transmit power for the private message to reduce the interference. This problem is formulated as an optimization problem whose goal is to maximize the sum-rate of all users. To solve this nonconvex maximization problem with a single-antenna BS, the optimal power used for transmitting the private message to the users is first obtained in closed form for a given rate allocation and common message power. Based on the optimal private message transmit power, the optimal rate allocation is then derived under a fixed common message transmit power. Subsequently, an iterative algorithm is proposed to obtain a suboptimal solution of common message transmit power. To solve this nonconvex maximization problem with a multiple-antenna BS, a successive convex approximation method is utilized. Simulation results show that the RSMA can achieve up to 15.6% and 21.5% gains in terms of data rate compared to non-orthogonal multiple access (NOMA) and orthogonal frequency-division multiple access (OFDMA), respectively.

A Multi-Jammer Power Control Game

We consider a single carrier communication system subjected to multi-jammer interference, and study optimal power control in the framework of game theory. The Nash and Stackelberg equilibria are derived in closed form. Conditions involving the background noise variance and the transmission cost are established for determining whether the equilibria are unique. It is proven that in the case of multiple equilibria, the user has the same payoff at each equilibrium, which reflects the stability of the communication. Also, consistent with the literature on single-jammer scenarios, it is shown that when the jammers are in a Stackelberg game, although they act as followers, they gain in payoffs as compared to the Nash game.

Joint optimization of BS-VS association and power control in secure HSR communication systems

In this paper, the secure transmission for high-speed railway (HSR) communication system is studied. The considered HSR wireless communication system consists of a macro base station, B roadside base stations, and K vehicle stations (VSs) on the top of the train, and the eavesdropping user is a mobile unmanned aerial vehicle (UAV). We consider maximizing the sum of the minimum security rate of each time slot as the objective function, and the constraint conditions contain the quality of service (QoS), switch requirements and the total power constraint. The original optimization problem is mixed-integer and non-convex, it is intractable to solve directly. The block coordinate descent (BCD) method is applied, and the original problem can be decoupled into two sub-problems. The one is the joint BS-VS association problem, and the other is the power control problem. The first sub-problem of optimizing BS-VS association can be solved by the successive convex approximation (SCA) algorithm, and the second one of optimizing transmit power can be solved by the lagrangian dual method. Simulation results show that the proposed algorithms have good convergence.