Abstract:

Replacing coal and fossil fuel with clean energy sources has become one of the most important concerns globally for reducing greenhouse gases. Data in recent status reports on clean and renewable energy sources have shown that renewable energy sources, specifically PV and Wind energy have been growing rapidly year by year. However, most renewable energy sources have an intermittent nature of energy production due to the dependency on weather conditions such as solar irradiance, temperature, water wave speed, wind speed, etc. This intermittent nature of renewable energy sources has caused some unacceptable levels of fluctuation and ripple in generated power which is not suitable for load requirements. Therefore, Energy Storage Systems (ESS) have been utilized to store surplus energy and return it to the bus when needed, thereby reducing power fluctuations and increasing stability and reliability. In this work employs control method Fuzzy Logic Control (FLC) models based on a common DC bus hybrid power system. Each hybrid system consists of a PV generator, a wind generator, fuel cell with EV loads.

INTRODUCTION:

Due to the rapid usage and pollution of fossil fuels, renewable energy sources (RESs) must be integrated into the power system to meet future demands. Solar energy, geothermal energy, ocean energy, wind energy, bioenergy, and other renewable energy sources have been installed in many places around the world, especially rural comment. Wind, tidal and solar energy are the most popular renewable energy sources. Rather than constructing transmission lines to deliver power from generators to loads, small-scale off-grid (microgrid) systems are built in isolated regions. A microgrid is a small system that runs mostly on solar and wind energy. Increased non-renewable energy supplies and energy storage have also increased in order to ensure a permanent and reliable power supply due to solar, tidal and wind power system instability, interruption, and high costs. When renewable energy sources are coupled with additional energy sources, hybrid renewable energy systems (HRESs) are developed. Consumer demand for energy is not uniformly spread throughout time, resulting in phasing issues between energy produced and energy used. The grid’s stability is determined by the balance of output and consumption. For renewable energy sources to become more prevalent, they must participate in these services, which will be aided by the use of electrical energy storage devices in conjunction with them. A storage solution is therefore essential for integrating renewable energies into our energy infrastructure. While it provides a technological solution for grid operators to ensure a real-time balance between production and consumption, it also allows for the most efficient use of renewable resources by avoiding loadshedding in the event of overproduction (Rizwan et al., 2021; Sun et al., 2020). With the addition of local renewable energy production coupled with decentralized storage, electrical network resilience is improved by allowing the islanding of the area served by this resource. In addition, a well-positioned energy storage system (ESS) enhances power quality by enhancing frequency and voltage control and reducing unpredictability by making a contribution to the transmitted current, which is especially essential if the energy is supplied within peak periods. A freestanding microgrid that combines renewable energy sources with energy storage technology. Wind, tidal, and photovoltaic (PV) energy sources should be combined to maximize the ESS’s capacity. When using ESS, supercapacitors and batteries are typically used to extend the life of the battery and provide a speedy response of the system to adjust for power fluctuations. As a result, supercapacitors are replaced by the AC grid when power plants and battery storage systems (BSS) are coupled. A microgrid can be divided into three types: DC, AC, or hybrid. DC microgrids provide a number of advantages to AC microgrids, including fewer control parameters, easier integration, and simpler construction. The AC type, on the other hand, necessitates more data, such as reactive power and frequency synchronization, making the control computing step more difficult. Aside from that, DC microgrids can operate in a variety of modes, including AC microgrid, stand-alone, and integrated with AC. Power electronics advances have enabled the DC microgrid to function at maximum efficiency). However, due to the stochastic nature of renewable energy sources, a supplementary energy management unit is required to ensure smooth operation and continuous power transmission to the loads. As a result of the significant differences between DC microgrid dynamics and AC microgrid dynamics, many of these energy management control methodologies cannot be applied to DC microgrids. In the usual DC microgrid architecture, the sources of energy and the load converters are actually interconnected, where the energy is delivered or consumed through the DC-link. In order for the DC microgrid to work efficiently and reliably, the DC-link voltage must be regulated. As a result, a number of control solutions have been proposed to solve the issue of DC-link. Recent developments and advancements in hybrid microgrids are discussed together with power generation control and planning. It is proposed in a new voltage control that combines fuzzy control with gain-scheduling techniques to accomplish both power sharing and energy management based on one energy storage unit with a dc/dc converter to maintain the dc-bus voltage under intentional islanding operation. A control technique based on fuzzy logic with decreased rules is proposed for smoothing the power of a microgrid. The case study aims to design an Energy Management System (EMS) to reduce the impact on the grid power when renewable energy sources are incorporated to pre-existing grid-connected household appliances. A dual proportional–integral controller which uses a combination of the feedback and feed-forward control loops of the distributed generators integrated to a dc microgrid, in islanded and grid connected modes of operation. These linear control schemes, on the other hand, are able to regulate the DC-link in a very short time. As a result, nonlinear controllers have been researched in the literature to solve this limitation. A new energy management control method is proposed for energy storage systems used in DC microgrids. The proposed control method is based on an adaptive droop control algorithm that maintains the dc-bus voltage in the desired range. For several energy storage systems in a microgrid, energy management-based optimum control is examined. An H∞ control approach is proposed for microgrid converters based on direct-voltage control and optimized dynamic power sharing to minimize internal microgrid formation disturbances and to effectively reject both voltage magnitude disturbances and power angle swings associated with mode transition and load disturbances. A resilient sliding mode method is proposed for the regulation of a boost converter supplying constant power to a buck converter to tackles the problem of the cascade connection of real converters. A backstepping strategy system that is adaptive in nature. A control technique-based on the Lyapunov theory is investigated. A novel assorted nonlinear stabilizer, which is integrated with an extended nonlinear disturbance observer and feedback linearization controller, is proposed for stabilizing the microgrid system. A hybrid sliding mode and backstepping strategy is analysed, however, the nonlinear control strategies that have been previously proposed have shown limits in terms of performance has been given to the multiple integrated ESS, as well as poor stability. Another problem is that many of these controllers rely on fixed gains, which are particularly subject to outside disturbances, parameter mistakes and it is time to wrap things up with a look at the energy. Without suitable grid-based incentives for intended contribution levels, the widespread use of renewable energy sources in an open energy market is doubtful.

PROBLEM STATEMENT:

In this paper, FLC method for determining the lowest incentives is presented that result in the desired amount of renewable energy source penetration in the energy supply chain and optimal power source allocation in the electric power grid. The controller determines the appropriate incentive based on power-flow, then employs a unique approach to solve a mixed power generation planning to reduce energy costs. A fuzzy based control method is proposed in this paper to solve the problems associated with traditional integer controls in hybrid energy management systems. In this paper, the new proposed intelligent control is intended to regulate the source side converters (SSCs) in order to capture the maximum energy from hybrid renewable energy sources (wind, FC and PV) while also improving power quality in the DC-microgrid. To keep the microgrid as cost-effective as possible, the renewable energy sources are prioritized. The suggested controller offers a steady output power and sustained service.