Optimal voltage control in interconnected power distribution systems by a self-adaptive fuzzy logic controller

Integration of large-scale distributed generators (DGs) (such as wind turbines, solar photo-voltaic, fuel cells, and so on) into the microgrid triggers voltage deviation which can give rise to desynchronization and distortion of power flow. To solve this problem, this article presents a distributed optimal secondary voltage control to synchronize the output voltage deviations of the DGs to zero. Instead of designing a distributed linear optimal control for the DGs linearized near an operating point as in the existing literature, a two-loop control structure comprising an inner-loop and outer loop is put in place. The inner-loop linearizes the nonlinear dynamics of each of the DGs. Then, the outer-loop which consists of the optimal distributed controller solves an optimization problem with the aim to minimize the voltage deviation of each DG by exchanging information with neighbouring DGs through a communication network. The proposed control technique will force the voltage deviations of the DGs to zero based on consensus. The efficacy of the proposed technique is confirmed by simulation studies.

Summary A distribution network with distributed generation (DG) is usually called an active distribution network. The voltage quality in an active distribution network tends to degrade because of the bidirectional power flow in the network and the random output characteristic of DG. Existing voltage control methods cannot effectively address this issue. In this article, an improved differential evolution (DE) algorithm–based optimal series compensation voltage control method for an active distribution network is presented. It is assumed that the series compensating voltage is produced flexibly by modern power electronics equipment. The quantitative relationship connecting the node voltage deviation, network power loss and compensating voltage is analysed. The optimal control model, including the power loss and load node voltage, is constructed. Then an improved DE algorithm is proposed to solve the optimal model, which combines the standard DE approach with the simulated annealing and adaptive mutation operator method. The optimal control model can be solved effectively by the improved algorithm. A simulation model is developed based on the IEEE 33 standard distribution network with DG. Simulation results confirm the validity of the optimal control model and the advantages of the improved DE algorithm.

In this article, an optimal steady-state voltage control framework is developed based on a novel linear voltage-power dependence deducted from Gaussian process (GP) learning. Different from other point-based linearization techniques, this GP-based linear relationship is valid over a subspace of operating points and, thus, suitable for a system with uncertainties such as those in power injections due to renewables. The proposed optimal voltage control algorithms, therefore, perform well over a wide range of operating conditions. Both centralized and distributed optimal control schemes are introduced in this framework. The least-squares estimation is employed to provide analytical forms of the optimal control, which offer great computational benefits. Moreover, unlike many existing voltage control approaches deploying fixed voltage references, the proposed control schemes not only minimize the control efforts but also optimize the voltage reference setpoints that lead to the least voltage deviation errors with respect to such setpoints. The control algorithms are also extended to handle uncertain power injections with robust optimal solutions, which guarantee compliance with the voltage regulation standards. As for the distributed control scheme, a new network partition problem is cast, based on the concept of effective voltage control source (EVCS), as an optimization problem which is further solved using convex relaxation. Various simulations on the IEEE 33-bus and 69-bus test feeders are presented to illustrate the performance of the proposed voltage control algorithms and EVCS-based network partition.

Voltage and Frequency control are the two fundamental control problems in power systems. Unlike frequency control, voltage control is complicated by the fact that reactive power can't travel far distances from its source of generation. Due to this distributed nature of reactive power, voltage control is usually performed in decentralized manner. Typically, voltage control problem is divided into a three-level hierarchical structure namely primary, secondary and tertiary voltage control.;The aim of this thesis is to present an optimal secondary voltage control by decomposing a large power system into small subsystems called voltage control areas (VCAs) using the fast community detection algorithm. Each VCA is self-sufficient in satisfying its reactive power demand. A load bus, called pilot point/bus, is selected in each VCA as a representative of the voltage profile of the whole area. Singular value decomposition of Fast Decoupled Load Flow (FDLF) Jacobian is used to optimally control the voltages of these pilot buses.;The presented approach is tested on two standard IEEE test power systems i.e. 9-Bus and 39-Bus systems. The computational time comparison of the fast community detection algorithm with another algorithm called original-GN algorithm is also presented. Through simulation results, it is shown that the presented optimal voltage control (Opt-VC) is a better approach compared to sensitivity based voltage control (Sen-VC).

This paper presents an optimal voltage control algorithm developed to increase the efficiency of operation of power systems and minimizing the reaction time for compensating voltage deviations due to load fluctuations. Because of the many variables of influence in the optimal voltage control (e.g. line power flow limits, bus voltage limits, etc.), the mathematical formulation is a constrained optimization problem with continuous and discrete variables, known as Optimal Power Flow (OPF), which is non-linear and non-convex. We propose a methodology to convexify the OPF problem based on Semidefinite Programming (SDP), with a novel formulation to include discrete decision variables such as shunt elements and tap changers positions as discrete variables. Finally, the SDP formulation of the case of a DC network is included.

A new approach to optimal reactive power and voltage control problem in a radial distribution system is proposed in this paper. The optimal control problem is to find a proper dispatch schedule for shunt capacitor banks and on-load tap changer at substation and shunt capacitor banks on feeders such that the power loss is minimized and the voltage profile is improved. To reduce computation burden, the whole problem is decomposed into two sub-problems, namely sub-problem on substation level and sub-problem on feeder level. A simplified dynamic programming and a fuzzy logic control algorithm are used to deal with the two sub-problems respectively. Coordination of the two algorithms provides an appropriate solution to the whole control problem. The numerical results demonstrate that the proposed approach is effective and feasible.

To cope with the volatility and randomness of wind power, photovoltaic (PV) power, and load demands in the islanded microgrid, and also to ensure the safety and economic operation of the islanded microgrid system. A collaborative Distributed model predictive control (Di-MPC) based voltage optimization control strategy is proposed, which considers the strong coupling characteristic of active and reactive power due to the impedance ratio of islanded microgrid, and the requirements of real-time and robustness in the optimization as well. By coordinating the controllable devices in the source-grid-load side of the islanded microgrid, the proposed strategy aims to make full use of the voltage regulation capability of each controllable device. Firstly, by considering the different operating characteristics of the controllable devices, a multi-time scale distributed voltage optimal control model is established. It divides the optimal control process into long-time scale and short-time scale and optimizes for respective objective functions and control variables in different time scales. Secondly, a collaborative Di-MPC-based voltage optimal control strategy is proposed. With the proposed collaboration mechanism, the power output increments of the distributed generators (DGs) are solved in the short-time scale, and the errors in the long-time scale control are also fixed. Finally, the simulation results show that compared with a traditional optimal control method and a centralized model predictive control (CMPC) method, the proposed voltage optimization control strategy can effectively reduce the voltage deviation and fluctuation at each node while ensuring the economic operation of the islanded microgrid system.

Diverse consensus-based distributed secondary control mechanisms of isolated AC micro-grids (MG) have been proposed for achieving the autonomous steady-state power sharing and frequency synchronizations. However, their transient responses are not specified. To tackle out this issue, a fully distributed optimal control strategy is studied in this paper in which their transient responses are characterized in the objective function. A two cascaded loops control strategy for each distributed generator (DG) is proposed to achieve this control objective. In the local inner loop, auxiliary inputs are designed for adjusting local frequency and voltage. In the outer control loop, the distributed optimization problem is proposed under both agent dynamics and consensus constraints. By defining the augmented Lagrangian, a fully distributed optimization algorithm can be developed by integrating the method of alternating direction method of multipliers (ADMM) and Lyapunov function approach. To demonstrate the applicability of the proposed method, real-time simulation studies of IEEE 34-node MG are performed. Comparison studies between the proposed approach and the distributed PI-based consensus control also indicate the effectiveness of the proposed method.

This paper present a new approach for optimal voltage control in power distribution systems considering the minimization of the voltage deviation from reference in all power systems busses using a modified line drop compensation method. Taking into account that the main purpose of the automatic voltage regulator (AVR) for power transformers with on-load-tap-changer (OLTC) is to keep the voltage within a preset limit. By using a fictitious network an algorithm for automatic control of the OLTC transformation ratio has been proposed, which follows practically to maintain the optimum voltage value at a “controlled” point through a fictitious voltage and an imaginary impedance. A MATLAB specialized software was applied to a real distribution network to confirm the feasibility, and numerical results demonstrate the effectiveness and efficiency of the proposed method.

SUMMARYIn the future, renewable energy (RE) generation systems will be constructed and interconnected to the power system by nonutility entities such as generation companies and residential customers. Therefore, generation expansion planning (GEP) should consider the effects of RE generation. The purpose of this paper is to discuss the best GEP from the economic, supply reliability, and environmental aspects considering the penetration of RE generation. For this purpose, this paper proposes a model of a utility's GEP process considering RE generation. The proposed method is based on stochastic dynamic programming (SDP) in which long‐term uncertainties are modeled by geometric Brownian motion (GBM) and the binomial lattice process. The variation of RE generation output due to the weather conditions (short‐term uncertainty) is also considered in the proposed method by means of the net load curve.

A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid particle swarm optimisation (PSO) is proposed. The objective is to minimise comprehensive cost, consisting of power loss and operation cost of transformers and capacitors, and subject to constraints such as minimum and maximum reactive power limits of distributed generators, maximum deviation of bus voltages and maximum allowable daily switching operation number. PSO is used to solve the corresponding mixed integer non‐linear programming problem and the hybrid PSO (HPSO) method, consisting of three PSO variants, is presented. In order to mitigate the local convergence problem, fuzzy adaptive inference is used to improve the searching process and the final fuzzy adaptive inference‐based HPSO is proposed. The proposed algorithm is implemented in VC++ 6.0 program language and the corresponding numerical experiments are finished on the modified version of the IEEE 33‐node distribution system with two newly installed distributed generators and eight newly installed capacitors banks. The numerical results prove that the proposed method can search a more promising control schedule of all transformers, all capacitors and all distributed generators with less time consumption, compared with other listed artificial intelligent methods.

For the lack of the fuzzy self-adaptive PID controller which applied in the industrial process control,a new kind of fuzzy self-adaptive PID controller was introduced. Fuzzy Control part will have the ability to automatically adjust the control rules by plusing a fuzzy self-adjustment factor based on the original fuzzy self-adaptive control system. And PID part adopts integral separated PID control.Then, the control system will have a stronger accommodation, satisfactory control effect is equally provided for different control object.Based on the simulation contrast of the traditional fuzzy self-adaptive PID controller and the fuzzy adaptive PID controller with self-adjustment factor introduced in this paper to show that, the new intelligent controller has a better control effect and robustness. Good control effect is got by simulation when it used for electro-hydraulic control system of proportional valve.

This paper proposes a fractional-order proportional integral (FOPI) current control method with fractional-order proportional integral differential (FOPID) error voltage control. The disturbance voltages caused by the dead-time effect are compensated by the FOPID controller and fed to the reference voltage. The particle swarm optimization (PSO) algorithm is utilized to design the parameters of the FOPID controller. The FOPI current control method with FOPID error voltage control has a beneficial effect on eliminating the dead-time effect. The simulation results show that the proposed method using optimal FOPID error voltage control makes the current ripple smaller and the response speed faster than that of the traditional optimal integer-order PID control. Considering the uncertainty of motor parameters, the method proposed in this paper has been proven to have a good compensation effect and robustness through theoretical and simulation analysis.

Recently, renewable energy such as wind turbine generator and photovoltaic system are introduced as distributed generators (DGs). Connection of a large amount of distributed generator causes voltage deviation beyond the statutory range in distribution system. Reactive power control of inverter interfaced with DG is one of the solutions against this problem. Additionally, reactive power control has a possibility to contribute for reduction of distribution loss. In this paper, we propose a voltage control method in distribution system by reactive power control of inverters interfaced with DGs. The proposed method has been developed with the aim of reduction of distribution loss and voltage regulation into statutory range without any telecommunications. In the proposed method, each interfaced inverter controls reactive power based on voltage control reference, which is calculated from local measurements. The calculation rule of control reference has been developed using optimal data, which consist of relations between ramdomly given inputs and corresponding optimal outputs calculated by an optimization technique. Simulations are conducted to show the effectiveness of the proposed method.

In this letter, we propose an optimal voltage feedback control algorithm for wind farms where the voltage set-point of wind-farm-side voltage source converter (WFVSC) and reactive powers of wind turbines (WTs) are coordinated. The proposed control establishes on the gradient descent and operates in an online fashion. Each WT updates its reactive power based on the local instantaneous terminal voltage and therefore, the proposed control can be implemented in a decentralized manner. Besides, we also address its asynchronous counterpart to enhance the practical applicability in real world.