This paper examines a completely novel method for improving the transient stability of multi virtual synchronous generator (VSG) grids. In this method, it has been tried to control the oscillation of VSGs with respect to the center of inertia frequency (COI-frequency) of the grid, during short-circuit. It is also well demonstrated here that the proposed method is able to prevent the increase in irreversible distance angle of VSGs relative to each other, which is the main factor in preventing VSGs reaching to instability point. The method can enhance both the synchronizing and damping terms efficiently. Detailed analyzing of the direct Lyapunov method illustrates the non-linear proof of the method. Also, non-linear algebraic equations for a two-VSG system have been derived to prove the possibility of corroborating simulation results. Equal area criterion is also used to clarify this method further. One interesting feature of the method is that there is no conflict between the requirements of the low voltage ride-through and transient stability improvement.

New Transient Stability and LVRT Improvement of Multi-VSG Grids Using the Frequency of the Center of Inertia

DC microgrids (DCMGs) are becoming more popular in modern power systems due to their simplicity, efficiency, and reliability. Autonomous control of DCMG is primarily based on the droop control. Typically, the droop coefficients of each distributed generator (DG) are fixed and assigned based on their capacity. This article introduces a multiobjective optimization (MOO) based intelligent computation approach to derive the optimal droop coefficients for DGs in an islanded DCMG. The proposed approach takes into consideration not only the capacities of the DGs but also the system voltage regulation, system total loss minimization, and enhanced current sharing among the DGs. The Pareto optimal front of the constructed MOO problem is obtained using the elitist nondominated sorting genetic algorithm (NSGA II). A best compromise solution is extracted from the generated Pareto optimal front by employing a fuzzy membership function approach. Moreover, a state feedback linearization based controller is introduced to facilitate the control actions to experimentally validate the effectiveness and the applicability of the generated optimal droop relationships. The proposed approach was tested with a parallel connected dc 9-bus system, IEEE 30-bus system, and experimentally validated on a 5-bus system. However, the same concept can be extended to any other bus system without loss of generality.

Multiobjective Optimization of Droop-Controlled Distributed Generators in DC Microgrids

The paper presents a review of the approaches developed to solve the problem of primary voltage control and reactive power sharing (Q/V primary control) among converter interfaced production units present in a microgrid First of all, a general survey of the methods is proposed with specific focus on communication-less methods that are surely the most challenging Then, the article focuses on a detailed comparison of state-of-the-art communication-less approaches such as droop control (the most widely adopted) and three more recent alternative methods A comparative analysis is performed by means of dedicated simulations on a common benchmark network in different operational and topological set-ups to highlight their advantages and drawbacks The main result of this comparison is that the new methods are all improvements to the traditional droop technique, but network configuration and parameters have a great impact on the method performances and so a univocal ranking among them is not possible Therefore, the issue of designing an effective Q/V primary controller for microgrids is still a partly open issue which requires further investigation and research

A review of reactive power sharing control techniques for islanded microgrids

We consider energy storage systems having nonlinear efficiency functions, which are becoming increasingly important as shown in several recent works, and propose an optimal solution based on Pontryagin's minimum principle A central challenge in such problems is the hard limits on the state variable, which restrict the use of the minimum principle To address this challenge, we propose to include the capacity constraints in the objective function with a proper weighting constant We show that this approach allows formulation of the problem based on the classical minimum principle, and eventually leads to an efficient optimal control strategy The proposed solution is compared to a dynamic programming algorithm Numeric experiments reveal that for lossless storage devices dynamic programming is beneficial, since it enables fast and accurate solutions when a low number of samples is used However, for lossy storage devices the situation is the opposite, and the minimum principle provides faster and more accurate solutions, since its computational complexity is almost unaffected by changes in the system parameters

Optimal Control of Lossy Energy Storage Systems With Nonlinear Efficiency Based on Dynamic Programming and Pontryagin's Minimum Principle

This paper reviews recent works related to optimal control of energy storage systems. Based on a contextual analysis of more than 250 recent papers we attempt to better understand why certain optimization methods are suitable for different applications, what are the currently open theoretical and numerical challenges in each of the leading applications, and which control strategies will rise in the following years. The reviewed research works are divided to “classic” methods and “advanced” methods, in order to highlight the current developments and trends within each of these two groups. The classic methods include linear programming, dynamic programming, stochastic control methods, and Pontryagin’s minimum principle, and the advanced methods are further divided into metaheuristic and machine learning techniques.

A review of optimal control methods for energy storage systems - energy trading, energy balancing and electric vehicles

Along with the rapid growth in green energy utilization, microgrids are becoming an interesting part of the future power systems. This paper presents a transient trajectory optimization of parallel connected inverter system in an islanded microgrid. Optimal state and control transient trajectories are generated which drive each individual inverter from given initial conditions to their respective desired steady state equilibrium. This trajectory optimization is performed in decentralized manner and they are the open loop, local optimal control signals of the inverters. The Pontryagin’s minimum principle is employed to obtain the optimal state and control signal trajectories. Then, a stability analysis of the system with the local optimal control signals is done by a Lyapunov approach. Dynamic model of the system and the optimum trajectories are obtained in the d-q reference frame. Two example microgrid systems, one with three inverters and the other one with five inverters, were used to demonstrate the effectiveness and performance of the proposed approach which can be easily extended to any type of microgrid such as AC, DC, hybrid microgrids in both islanded or grid connected mode.

Transient Optimization of Parallel Connected Inverters in Islanded AC Microgrids

Application of power electronic converters and their controls play a vital role in modern industry. Advanced nonlinear controls with adaptation are required to control these converters when all or some of the system parameters are unknown or uncertain. Design of a passivity based nonlinear adaptive controller to control the output voltage of power electronic converter is proposed in this paper. Unlike most of the other adaptive controllers which require the input voltage information of the converter, the proposed controller require neither input voltage information nor output load resistance. Taking the duty cycle as the control input of the boost converter, the adaptive passivity based controller is designed to regulate the output voltage of the converter to a desired value. However, the proposed approach can be easily extended to control any other DC-DC converter without loss of generality. Simulation and experimental verifications were carried out to analyze the performance and the effectiveness of the proposed controller.

Adaptive Passivity Based Control of DC-DC Power Electronic Converters

With the high demand and interest for the small scale, renewable and distributed energy resource integration, microgrids have been gaining more popularity during past few decades An online, decentralized game theoretic optimal resource management strategy for load players in a DC microgrid is proposed in this paper Power electronic interfaces which make the connection between the end load and the power system are modeled as variable admittances and considered as players in the game The optimal input admittance which minimizes individual player cost function is calculated online using only the locally available measurements and a feedback control methodology is implemented to regulate the input admittance to the computed optimal value Simulation results are provided considering IEEE 9 bus system to illustrate the performance of the proposed concept

Online game theoretic feedback control of DC microgrids

This article proposes a decentralized, online optimal feedback control strategy to optimally stabilize active loads in islanded DC microgrids (DCMGs). Each active load is modeled as a control affine dynamical system with an interconnected coupling term in the energy and admittance domain. Then the decentralized, constrained input of each active load is obtained online in the feedback form to minimize the infinite horizon quadratic state cost and non quadratic control effort while supplying the active load demand. The approximate dynamic programming (ADP) approach is employed to solve the feedback optimal control problem online by successive approximation of the value function via two linear in the parameter (LIP) neural networks (NNs). A concurrent reinforcement learning (RL) based method is introduced to update the unknown weights in the NN. The convergence of the unknown weights to a neighborhood of the optimal weights and the uniformly ultimately bounded stability of the system are analyzed by a Lyapunov direct method. Series of simulation results are presented to demonstrate the effectiveness and the applicability of the proposed concept.

Anushka M. Dissanayake

Papers

Multiobjective Optimization of Droop-Controlled Distributed Generators in DC Microgrids

Transient Optimization of Parallel Connected Inverters in Islanded AC Microgrids

Adaptive Passivity Based Control of DC-DC Power Electronic Converters

Online game theoretic feedback control of DC microgrids

Decentralized Optimal Stabilization of Active Loads in Islanded Microgrids