A Virtual Impedance Optimization Method for Reactive Power Sharing in Networked Microgrid

Abstract

2 power sharing strategies have considered the impacts of DG output impedances, feeders and local loads. However, in a networked (multi-bus) microgrid, besides above mismatched factors, the networked structure is also an important factor that affects the system reactive power sharing. Without a complete consideration of these mismatched factors, previous methods can't work properly as desired in networked microgrids.To solve the reactive power sharing issue in networked microgrids, communication based solutions become shortcuts. In [19], [20], intercommunication among DG units is utilized to improve the reactive power sharing accuracy. However, this manner is subject to the DG install locations. Synchronizing signals are utilized in [21]-[23] to trigger an extra regulation for reactive power sharing, but the control performance is easy to be influenced if load changes during the regulation period. With the communication between microgrid central controller (MCC) and DG units, reactive power sharing methods based on set-point regulation, also known as secondary control [24]-[28], can be well applied in networked microgrids. With a similar communication mechanism, virtual impedances can also be adjusted to realize reactive power sharing [29]-[31]. However, it seems that the communication based virtual impedance methods have no significant benefits compared with set-point regulation methods.Although communication can help improving the reactive power sharing accuracy, it also introduces some new issues, such as cost increase and expansion capability decrease. In this paper, a wireless reactive power sharing control strategy that employs optimized virtual impedance controllers and local load measurements is proposed for networked microgrids. Based on the microgrid network modeling, the cause of reactive power sharing issue is revealed. Meanwhile, an estimation method for network reactive power sharing error is proposed. Through the estimation method based network feature analyses, virtual impedance controller is designed accordingly; then detailed controller parameters are optimized by using genetic algorithm (GA), which is to introduced to minimize the system global reactive power sharing error. The optimization process is performed offline in microgrid configuration stage. With the optimized virtual impedance controllers, DG units can well share the loads in microgrid. Throughout the whole strategy, communication is not used; instead, local load measurement is added for the virtual impedance control, which has no effect on the wireless manner of droop control. Finally, simulation and experimental results are provided to verify the proposals. 0885-8993 (c)

A Review on Impacts of Power Quality, Control and Optimization Strategies of Integration of Renewable Energy Based Microgrid Operation

“…Yixi Zhu et al [56] developed a virtual impedance control to determine with the help of genetic algorithm (GA) optimized to reduce the reactive power sharing error. Also, DG units share the loads in MG network that is unbalanced power and harmonic power.…”

Validação Experimental de uma Microrrede com Controle Centralizado e Despachável

“…otimização [25] podem ainda ser integradas para considerações ótimas locais de EGs; • Sob a segunda condição, que ocorre no caso de falha de comunicação, o modo de otimização e controle local é ativado, fazendo com que toda a energia gerada localmente seja injetada na rede, mantendo funcionalidades específicas como MPPT e proteção de ilhamento. Embora metodologias de MPPT tenham sido amplamente adotadas para diversas fontes alternativas de geração, assim como em células a combustível [26], em caso de não existência de tais algoritmos, o gerenciamento e operação local deve ocorrer atendendo à capacidade de geração e as respectivas normativas do determinado tipo de conversor utilizado na interconexão com a rede; • Já a terceira, determinada por um modo de controle de sobretensão, é ativada quando a tensão local excede valores normativos, o que normalmente ocorre em casos de excesso de injeção de potência ativa na rede.…”

Containment and Consensus-Based Distributed Coordination Control to Achieve Bounded Voltage and Precise Reactive Power Sharing in Islanded AC Microgrids

“…In addition, the centralized controller can cause the single point of failure. In [8], according to the electrical topology of the MG, the relationship between active/reactive load changes and reactive power sharing error is analyzed, and a genetic algorithm is applied to optimize the virtual impedance, in order achieve reactive power sharing. However, when the topology of MG is changed, the whole optimization problem needs to be reformulated.…”