Abstract
Microgrid (MG) is a novel concept for a future distribution power system that enables renewable energy sources (RES). The intermittent RES, such as wind turbines and photovoltaic generators, can be connected to the MG via a power electronics inverter. However, the inverter interfaced RESs reduce the total inertia and damping properties of the traditional MG. Consequently, the system exhibits steeper frequency nadir and the rate of change of frequency (RoCoF), which may degrade the dynamic performance and cause the severe frequency fluctuation of the system. Smart loads such as inverter air conditioners (IACs) tend to be used for ancillary services in power systems. The power consumption of IACs can be regulated to suppress frequency fluctuation. Nevertheless, these IACs, regulating power, can cause the deviation of indoor temperature from the temperature setting. The variation in indoor temperature should be controlled to fulfill residential comfort. This paper proposes a multi-objective decentralized model predictive control (DMPC) for controlling the power consumption of IACs to reduce MG frequency fluctuation and control the variation in indoor temperature. Simulation results on the studied microgrid with the high penetration of wind and photovoltaic generator demonstrate that the proposed DMPC is able to regulate frequency deviation and control indoor temperature deviation as a user preference. In addition, the DMPC has a superior performance effect to the proportional-integral (PI) controller in terms of reducing frequency deviation, satisfying indoor temperature preferences, and being robust to the varying numbers of IACs.
Highlights
The capacity of installed inverter-based distributed generations (DG) in power systems is rapidly growing [11]; the converter-interfaced DG to the power system causes the absence of rotational masses from synchronous generators (SGs), which leads to a lack of inertia and damping properties [9,11]
The temperature weights of multi-objective decentralized model predictive control (DMPC) are optimized by the firefly algorithm (FA) to minimize the frequency deviation and control the indoor temperature, which varied inside the preference ranges
1, with parameters ulation studies, it is supposed that the studied microgrid in Figure 1, with parameters inin
Summary
The MG is generally referred to as a self-sustained small distribution power system comprised of loads, DG, and/or energy storage systems [3,4,5,6,7]. The MG can be operated in two modes, i.e., grid-connected or islanded modes [3,4,5,6,7,8]. The islanded operational mode of MG is significantly more challenging than the grid-connected mode because the voltage and frequency regulation of the MG is no longer dominated by the main grid [1,2,3,4,5]. The DG, based on RES such as wind and photovoltaic (PV) generation, is conventionally connected to the MG by a power electronic inverter [9,10,11]. In September 2016, a black out occurred in South Australia due to the lack of inertia; the system could not accommodate rapid changes in frequency during sudden load imbalance [11]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
