## 3 Evolution of Smart Grids  
With the rapid growth and urbanization in various parts of the world in the 21 st century, the demand for electrical energy is also increasing, which can no longer be met by traditional power grids. Therefore, it is important to upgrade the existing power grids. The same technology is used by utilities in different parts of the world, even if they are located in different regions. The political, economic, and geographic conditions of each country affect the creation of power grids. Despite these differences, the basic characteristics of the power grid remain the same. The power industry operates with a strong distinction between generation, transmission, and distribution subsystems. At each stage, different levels of automation and transformation have emerged as the smart grid has evolved. The conventional utility grid is a hierarchical structure in which electricity is distributed to customers at the lower level, and power generation is provided by the power plant at the upper level, as shown in Figure 1. In the current power grid, the generation plants or sources do not have real-time data on the endpoints or user parameters, and the mechanism is a one-way power flow. In addition, the reliability of the system is deteriorating due to the huge increase in electricity demand and the comparatively low investment in electricity infrastructure. As the safety margin is exhausted, any disturbances or anomalies in the distribution networks and the sudden increase in electricity demand would lead to failures of system equipment, resulting in catastrophic power outages. To facilitate troubleshooting and maintenance of expensive power plants, many utilities have implemented various levels of monitoring and control functions. SCADA is a common example of where the new power system is most commonly used. Nearly 90 percent of all faults and power outages recorded by the authors in [22] originate in the distribution system, where the smart grid would come in. Additionally, the failure of utilities to produce electricity to meet energy \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Parameters** & **Conventional Grid** & **Smart Grid** \\ \hline Communications & One-way & Two-way [5] \\ \hline Power generation & Centralized generation & Decentralized/distributed generation [6; 7] \\ \hline Control methods & Manual control & Automatic control and recovery [10; 11; 12] \\ \hline Monitoring system & Manual monitoring & Automatic monitoring [13; 14] \\ \hline Sensors required for monitoring and control & No/fewer sensors & Large numbers of sensors for monitoring and control [15; 16; 17] \\ \hline Response to emergencies & Slow response & Fast response \\ \hline Choices to customer & Limited choices & Vast choices \\ \hline Network type & Radial & Dispersed/distributed [18; 19] \\ \hline Security/privacy concerns & Less security and privacy concerns & Prone to security and privacy issues \\ \hline Data involved & Less data & A huge volume of data is involved [20] \\ \hline Storage system & No storage is used & A storage system is used [21] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The conventional utility grid vs. smart grid. demand and higher fossil fuel prices have increased the need to upgrade distribution grids by implementing new technologies to protect sales and demand-side management (DSM). Most utilities are investing in distribution grid metering systems. As can be seen in Figure 2, recent investments in distribution system infrastructure have been concentrated on the metering side of the system. One example is the introduction of the automatic meter reading (AMR) system. With the introduction of AMR systems to the distribution grid, utilities can remotely read the records, alerts, and status of energy consumption.