Coordinated voltage control of three-phase step voltage regulators and smart inverters to improve voltage profile and energy efficiency in unbalanced distribution networks

This paper proposes a coordinated voltage control by three-phase step voltage regulators (3ϕSVRs) and photovoltaic (PV) units with smart inverters. An optimization problem is formulated to improve the voltage profile of distribution networks and reduce the active power curtailment of PVs. The tap positions of 3ϕSVRs and the active and reactive power output of PVs are coordinated by whale optimization algorithm. The effectiveness of the proposed approach is verified by case studies on the IEEE 123 node test feeder. The results show that the proposed approach achieves lower voltage unbalance while avoiding excessive PV curtailment, improving utility, consumer, and environmental benefits

Output Control of Three-Axis PMSG Wind Turbine Considering Torsional Vibration Using H Infinity Control

Due to changes in wind, the torque obtained from the wind turbine always fluctuates. Here, the wind turbine and the rotor of the generator are connected by a shaft that is one elastic body, and each rotating body has different inertia. The difference in inertia between the wind turbine and the generator causes a torsion between the wind generator and the generator; metal fatigue and torsion can damage the shaft. Therefore, it is necessary to consider the axial torsional vibration suppression of a geared wind power generator using a permanent magnet synchronous generator (PMSG). In addition, errors in axis system parameters occur due to long-term operation of the generator, and it is important to estimate for accurate control. In this paper, we propose torque estimation using H ∞ observer and axial torsional vibration suppression control in a three inertia system. The H ∞ controller is introduced into the armature current control system (q-axis current control system) of the wind power generator. Even if parameter errors and high-frequency disturbances are included, the shaft torsional torque is estimated by the H ∞ observer that can perform robust estimation. Moreover, by eliminating the resonance point of the shaft system, vibration suppression of the shaft torsional torque is achieved. The results by the proposed method can suppress axial torsional vibration and show the effect better than the results using Proportional-Integral (PI) control

Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm

This article offers a multi-objective framework for an optimal mix of different types of distributed energy resources (DERs) under different load models. Many renewable and non-renewable energy resources like photovoltaic system (PV), micro-turbine (MT), fuel cell (FC), and wind turbine system (WT) are incorporated in a grid-connected hybrid power system to supply energy demand. The main aim of this article is to maximize environmental, technical, and economic benefits by minimizing various objective functions such as the annual cost, power loss and greenhouse gas emission subject to different power system constraints and uncertainty of renewable energy sources. For each load model, optimum DER size and its corresponding location are calculated. To test the feasibility and validation of the multi-objective water cycle algorithm (MOWCA) is conducted on the IEEE-33 bus and IEEE-69 bus network. The concept of Pareto-optimality is applied to generate trilateral surface of non-dominant Pareto-optimal set followed by a fuzzy decision-making mechanism to obtain the final compromise solution. Multi-objective non-dominated sorting genetic (NSGA-III) algorithm is also implemented and the simulation results between two algorithms are compared with each other. The achieved simulation results evidence the better performance of MOWCA comparing with the NSGA-III algorithm and at different load models, the determined DER locations and size are always righteous for enhancement of the distribution power system performance parameters

A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels

In this paper, the performance of different optimization techniques namely, multi-objective dragonfly algorithm (MODA) and multi-objective differential evolution (MODE) are presented and compared. The uncertainty effect of a wind turbine (WT) on the performance of the distribution system is taken into account. The point estimate method (PEM) is used to model the uncertainty in wind power. Optimization methods are applied to determine the multi-objective optimal allocation of distributed generation (DG) in radial distribution systems at a different load level (light, normal, heavy load level). The multi-objective function is expressed to minimize the total power loss, total operating cost, and improve the voltage stability index of the radial distribution system (RDS). Multi-objective proposed algorithms are used to generate the Pareto optimal solutions; and a fuzzy decision-making function is used to produce a hybrid function for obtaining the best compromise solution. The proposed algorithms are carried out on 33-bus and IEEE-69-bus power systems. The simulation results show the effectiveness of installing the proper size of DG at the suitable location based on different techniques

Applications of hybrid model predictive control with computational burden reduction for electric drives fed by 3-phase inverter

Model predictive control (MPC) is recently emerging as an efficient and promising technique for the control of power converters. In the conventional MPC algorithm, the control objectives are usually estimated and evaluated for a large/definite number of switching states. Since prediction and evaluation are done for all possible states, massive amounts of estimations are needed, moreover, the computational burden is more challenging with the increase of control objectives. In this paper, a computationally efficient version of the finite control set-MPC (FCS-MPC) is proposed to decrease the calculation effort of the MPC algorithm likewise minimizing its execution time to enforce its vast application for the control of three-phase power converters. The suggested procedure is to eliminate the current predictions as well as reduce the number of available switching states that need to be estimated by the algorithm which reduces considerably the amount of time consumed by these computations. The studied techniques achieved nearly the same performance with an interesting reduction in the algorithm execution time accomplished by the proposed modified FCS-MPC algorithms

Unbalanced Voltage Compensation with Optimal Voltage Controlled Regulators and Load Ratio Control Transformer

Penetration of equipment such as photovoltaic power generations (PV), heat pump water heaters (HP), and electric vehicles (EV) introduces voltage unbalance issues in distribution systems. Controlling PV and energy storage system (ESS) outputs or coordinated EV charging are investigated for voltage unbalance compensation. However, some issues exist, such as dependency on installed capacity and fairness among consumers. Therefore, the ideal way to mitigate unbalanced voltages is to use grid-side equipment mainly. This paper proposes a voltage unbalance compensation based on optimal tap operation scheduling of three-phase individual controlled step voltage regulators (3ϕSVR) and load ratio control transformer (LRT). In the formulation of the optimization problem, multiple voltage unbalance metrics are comprehensively included. In addition, voltage deviations, network losses, and coordinated tap operations, which are typical issues in distribution systems, are considered. In order to investigate the mutual influence among voltage unbalance and other typical issues, various optimization problems are formulated, and then they are compared by numerical simulations. The results show that the proper operation of 3ϕSVRs and LRT effectively mitigates voltage unbalance. Furthermore, the results also show that voltage unbalances and other typical issues can be improved simultaneously with appropriate formulations

A Real Distribution Network Voltage Regulation Incorporating Auto-Tap-Changer Pole Transformer Multiobjective Optimization

A number of studies realized operation of power systems are unstable in developing countries due to misconfiguration of distribution systems, limited power transfer capability, inconsistency of renewable resources integration, paucity of control and protection measures, timeworn technologies, and disproportionately topology. This study underlines an Afghanistan case study with 40% power losses that is mainly pertinent from old distribution systems. The long length of distribution systems, low-power transfer capability, insufficient control and protection strategy, peak-demand elimination, and unstable operation (low energy quality and excessive voltage deviations) are perceived pre-eminent challenges of Afghanistan distribution systems. Some attainable solutions that fit challenges are remodeling (network reduction), networks reinforcement, optimum compensation strategy, reconfiguration options, improving, and transfer capability. This paper attempts to propose a viable solution using multiobjective optimization method of auto-tap-changer pole transformer (ATCTr). The proposed methodology in terms of optimal numbers and placement of ATCTr can be known as a novel two-dimensional solution. For this purpose, a real case of Kabul City distribution system is evaluated. Simulation results indicate the effectiveness of the proposed method in reducing system losses and improving system overall performance. This approach tends to regulate the voltage deviation in a proper and statutory range with minimum number and optimum placement of ATCTrs. The proposed method is simulated using MATLAB® environment to compare and evaluate performance of the proposed network under different situations and scenarios

Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation

Electric vehicle charging station have become an urgent need in many communities around the world, due to the increase of using electric vehicles over conventional vehicles. In addition, establishment of charging stations, and the grid impact of household photovoltaic power generation would reduce the feed-in tariff. These two factors are considered to propose setting up charging stations at convenience stores, which would enable the electric energy to be shared between locations. Charging stations could collect excess photovoltaic energy from homes and market it to electric vehicles. This article examines vehicle travel time, basic household energy demand, and the electricity consumption status of Okinawa city as a whole to model the operation of an electric vehicle charging station for a year. The entire program is optimized using MATLAB mixed integer linear programming (MILP) toolbox. The findings demonstrate that a profit could be achieved under the principle of ensuring the charging station’s stable service. Household photovoltaic power generation and electric vehicles are highly dependent on energy sharing between regions. The convenience store charging station service strategy suggested gives a solution to the future issues

Modern Temperature Control of Electric Furnace in Industrial Applications Based on Modified Optimization Technique

In this paper, an enhanced version of whale optimization algorithm (EWOA) is presented to be applied in adaptive control techniques as a parameter tuner. One weakness point in this control scheme is the low efficiency of its objective function. Balloon effect (BE) is a modification introduced to increase the efficiency of the objective function of the optimization method and the ability of the controller to deal with system problems increase consequently. Controlling of the temperature of electric furnaces is considered as one of the important issues in several industrial applications. Conventional controllers such as PID controller cannot deal efficiently with the problem of parameters variations and step disturbance. This paper proposes an adaptive controller, in which the gain of the temperature controller is tuned online using EWOA supported by balloon effect. System responses obtained by the proposed adaptive control scheme using EWOA + BE have been compared with an electric furnace temperature control (EFTC) scheme response using both the PID controller-based modified flower pollination algorithm (MoFPA) and PID-accelerated PIDA-based MoFPA. From the results, it can be observed that the proposed controller tuned by the EWOA + BE method improves the time performance compared with the other techniques (PID and PIDA-based MoFPA) in case of EFTC application

Modern Temperature Control of Electric Furnace in Industrial Applications Based on Modified Optimization Technique

In this paper, an enhanced version of whale optimization algorithm (EWOA) is presented to be applied in adaptive control techniques as a parameter tuner. One weakness point in this control scheme is the low efficiency of its objective function. Balloon effect (BE) is a modification introduced to increase the efficiency of the objective function of the optimization method and the ability of the controller to deal with system problems increase consequently. Controlling of the temperature of electric furnaces is considered as one of the important issues in several industrial applications. Conventional controllers such as PID controller cannot deal efficiently with the problem of parameters variations and step disturbance. This paper proposes an adaptive controller, in which the gain of the temperature controller is tuned online using EWOA supported by balloon effect. System responses obtained by the proposed adaptive control scheme using EWOA + BE have been compared with an electric furnace temperature control (EFTC) scheme response using both the PID controller-based modified flower pollination algorithm (MoFPA) and PID-accelerated PIDA-based MoFPA. From the results, it can be observed that the proposed controller tuned by the EWOA + BE method improves the time performance compared with the other techniques (PID and PIDA-based MoFPA) in case of EFTC application