Development of a Fuzzy-Logic-Based Energy Management System for a Multiport Multioperation Mode Residential Smart Microgrid

Abstract

In this paper a grid-tied residential smart microgrid topology is proposed which integrates energies of a PV, a fuel cell and a battery bank to supply the local loads through a combination of electric and magnetic buses. In contrast to multiple-converter based micro-grids with a common electric bus, using a multi-port converter with a common magnetic bus can effectively reduce the number of voltage conversion stages, size and cost of the renewable energy system and isolates the conversion ports. The resultant topology utilizes a centralized system level control which leads to the faster and more flexible energy management. The proposed micro-grid is able to operate in multiple grid-connected and off-grid operation modes. A fuzzy controlled energy management unit (EMU) is designed to select the appropriate operation mode considering both real-time and long-term-predicted data of the energy generation and consumption. A mode transition process is designed to smooth the mode variation by using a state transition diagram and bridging modes. To improve the microgrid operation performance, appropriate control techniques such as synchronized bus-voltage balance are used. A prototype of the proposed micro-grid and the EMU are developed and experimentally tested for three different energy management scenarios. Energy distribution and energy cost analysis are performed for each scenario to validate the proposed control method.

Comparative analysis of DC to AC conversion cells for application in PV‐linked grid‐connected modular multi‐level cascaded converters

“…The feedback gains of K f 1 and K f 2 are selected according to the signal conditioning circuit parameters. The compensator blocks C v− PV and C i− PV are the proportional–integral (PI) controller transfer functions of the voltage and current control loops, respectively, and can be presented in the general form as follows: where the proportional ( K P ) and the integral ( K I ) gains are determined based on the required crossover frequency ( ω c ) and the phase margin (PM) ( φ m ) of the voltage and current control loops [37, 38]. Assuming that the PI controller transfer function is given as Then the design problem is to find K P and K I for a chosen crossover frequency ( ω c ) and PM ( φ m ) such that From (23), we can find the following equations: …”

Energy Management in Power Distribution Systems: Review, Classification, Limitations and Challenges

“…Ren et al [242] propose an energy management system in MG to ensure its stable operation using PV, storage battery, and fuel cells, and reference [243] discusses and compares different models for performing EMS on SG. Lee et al [244] improve the resiliency of the MGs, and Jafari et al [245] improve operational performance of MGs. Khan et al [246] propose a comprehensive communication framework to increase the privacy and security of the network.…”

Traffic-Condition-Prediction-Based HMA-FIS Energy-Management Strategy for Fuel-Cell Electric Vehicles

“…Accordingly, for battery protection and DC bus voltage support, the battery SoC is considered be bounded within the above range by the EMS proposed in this paper. An FIS was shown to be efficient in the energy-management applications for its intelligence and model free advantages [49]. Therefore, an FIS was adopted as the last stage of the proposed EMS.…”