Microgrid Technologies

The management system of energy (MSE) is the collection of different control approaches and different active, ongoing exercises along with hardware and software to mitigate the energy management objectives problems. It is a multiple functionary system. It is a system which distributes the generated power optimally and economically to the load with proper voltage regulation and frequency regulation of the micro-grid. So, we can get a smooth changeover between connected to grid manner and isolated manner of micro-grid systems, according to micro-grid components and real-time load conditions of operation. This system can be used to get high-quality power, sustainability, reliability and environmentally friendly power source.

Due to this, researchers started focusing extensively on MSE strategies for various micro-grids ranging from small home (small scale) to cities or towns (large scale) as shown in the different scales of MG of Figure 1.4.

Exploration has started on a study of the practicability of the parts of micro-grid, and it is modeled by scheduling the DGs, and forecasting the data of environmental conditions such as irradiance of sunray, speed of wind flow and water speed, forecast of energy demand and on availability optimization algorithms in the intention of cost-effective benefits with minimum impact on the atmosphere. Figure 1.5shows the central micro-grid arrangement and components related to the energy management system. It shows that the research is mainly focused on the resolution of different problems regarding the micro-grid by means of an energy management system.

Figure 1.4 Various ranges of MG.

Figure 1.5 Components of micro-grid.

This is a review of the different features of micro-grid and management of energy that are presented in various current topics, starting from various units of MG, synchronization of components to the recent optimization methodology with system limitations and objective functions for MSE.

Afterwards, the different configuration and components of micro-grid are deployed in Section 1.2.Here the different structures used in an energy management system with various distributed energy sources, various storage systems and different type of load or the consumer behavior are illustrated. Followed by Section 1.3, it depicts the MG–MSE and different modes of operation. Further, Section 1.4discusses about the recent techniques and algorithms used for optimization in energy management systems. Finally, Section 1.5concludes the different sections and further deliberates the strategy for further research in this area.

In recent years, a great number of researchers are discussing the issues in micro-grids. Nowadays, the verities of micro-grid structures have been presented in the literature. In micro-grid the different distributed generations are utilized because of its geographical characteristic, economic benefits, environmental condition and impact on the surrounding. In Ref. [5], there is a discussion on predictive MSE with its control strategies and communication of micro-grid to the independent utility grid. A 1.5 MW wind energy associated with the battery as a storage system is analyzed. In Ref. [6] a hybrid hydrokinetic system HKT battery is used in GC mode. The surplus power of HKT is utilized for charging a battery or trade to the grid. Whether the power will be sold to the main grid or not is determined by the charge condition of the battery and the principle of the utility grid network. The power requirement of the load is provided by the HKT. The excess power is utilized to charge the storage body. Then also, if there is an excess quantity of power, that can return back to the utility grid network. However, the utility grid supplies the load directly when the distributed generation system and the battery can’t entirely meet the load demand.

The universally used energy storage system is the battery. The battery system also has some limitations, as some charging and discharging current issues and unreliability according to the lifespan of the battery. So, techno-electronic indexes of micro-grid-based hybrid renewable energy resources are significantly increased by applying the distributed system of the generation with the storage system of energy [7]. Ref. [8] is a study of hybrid solar power as PV and diesel power in a distributed system supplying a load of a rural school in Ethiopia. The paper has compared the hybrid PV/Diesel distributed system with the storage system to the distributed generation system without storage as the net instantaneous rate of energy. Here a software named Homer is applied for analysis. The result was concluded that the hybrid distributed generation system with storage is having technical and economic advantages than that without storage. In Ref. [9] the authors proposed that the energy management system for hybrid micro-grid consist of photovoltaic and wind power as renewable energy sources (RES) and fuel cell (Hydrogen cell), ultracapacitor or battery as storage system of energy (SSE).

Nowadays the incorporation of an electric vehicle with micro-grid is viral because of its effect of low emission, inexpensive charging and decreased usage of conventional fuels. The electric car with MG can function in car-to-grid (C2G) mode or grid-to-car (G2C) mode. In Ref. [10] planned power management is proposed in the MG, including storage systems categorized into two types: regenerative fuel cell (RFC) and electric car (EV). That paper approaches with multi-goal optimization to minimize operational cost, line losses and maximise the value of energy stored in terms of RFC and EC. There are two functioning schemes planned for EC working in C2G mode to decrease the net running cost of the system. The combination of particle swarm skim of optimization as well as front and back sweep algorithm is used to solve complication, non-linear action and multidimensional property of the objective function. In Ref. [11] a large-scale electric vehicle charging station is proposed by the author, in which the required power is supplied by solar and wind power. Here both the PV and wind work with a unified MPPT technique. In Ref. [12] the author incorporated the plug-in charger of the electric vehicle in the distribution grid in both directions by using various converters. The bidirectional converters are coupled to the capacitor at the link with DC. The grid voltage may be regulated in the C2G configuration using the capacitor at the link with DC, which provides compensation for reactive power, which avoids the risk of voltage sag in the main. The mixed charging electrical car battery is used for peak load shaving and load levelling. Ref. [13] illustrates a real application of electric vehicle charging station along with a storage system of energy, which is a battery of Lithium polymer. Investigational research is done in Italy at the power and Sustainable Economic Development labs for innovative Technologies. The outcome shows the new performance of the ECs in the height of energy shaving action, as compared to the utility grid.

A resiliency-based Energy Management System of islanded operation of micro-grid is presented in Ref. [14]. Here the case studied is about micro-grid (MG) consisting of PV generation farms and WT generation farms both having storage system of energy (SSE) and distributed generation system. Based on the study, the researchers used 25 plug-in hybrid electric cars as adaptable load and supply to replicate the scheme of demand response in an optimal way, so the ECs in G2V manner are used as adaptable load, while in V2G manner is applicable as adjustable supply. Ref. [15] is a discussion on systematic energy management of a home with the smart system using PV panels as the source and plug-in EC (PEC) as storage of energy. It reduces payment for energy demand under using time tariff while supplying energy requirements to PEC and home load. A Lithium-ion battery is used in the PEC as storage and is controlled by DC–AC inverter, which allows the bidirectional flow of power. The plugs-in and plug-out of the PEC can be done once a day. The PEC mobility model is modeled by the Markov Chain model. The predictive models are used by the author to design solar power supply and home as load. The researchers proposed that the system may possibly be a significant cost savings system for the consumers. The proposed Management System of Energy manages the flow of power in between the PEC as storage, building or home as loads, and an array of PV panels and utility supply grid as supply.