## 3 Demand-Side Resources in Active Distribution Systems
### Demand Response Systems Objectives and Deployment Barrier  
Depending on the aim of the specific DR implementation and design, there exist several objectives of DR systems, such as reducing total energy consumption to achieve greater profits for both the supplier and the consumer. Another important objective is to also reduce the total power generated due to the reduced energy consumption and changing the demand while considering the current supply to improve the overall reliability of the system. One of the vital objectives of DR systems is to mitigate distribution system overload through a distribution management system by monitoring the distributional services provided by the system and using real-time adjustments to increase system robustness [33]. There are a few hindrances to DR deployment. Firstly, there is the problem of technology-based barriers caused by a lack of protocols and standards. Secondly, the markets and regulatory frameworks hinder DR deployment due to market entry barriers and unequal treatment of participation. Another deployment barrier that also poses a hindrance is the privacy of information, which is mostly called consumer privacy [34]. Finally, uncertainty in demand and renewable energy generation for aggregators to predict ADR potential for the consumer is also an important deployment barrier faced by DRs [32]. Table 2 presents an overview and analysis of demand-side management implementation methods in the literature as regards the study area, algorithm used, achievements, and shortcomings. Figure 2: Automated Demand Response Operability layers [32]. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**References** & **Components/Strategies** & **Objective of StudyFeatures** & **Algorithm** & **Achievements** & **Shortcomings/Recommendations** \\ \hline \multirow{4}{*}{[35]} & Wind and energy storage system & Optimal operation of the market-based wind system & MPC & Achieved cost savings of 12.18\% and 6.3\% & Recommended that there should be an optimal selection of the prediction and for 1 st and and approaches. Also 13.39\% & control horizon of the MTC for future and 4.9\% savings in daily energy & works, and there is also need for data \\  & & & & & \\  & & & & & \\  & & & & & \\  & \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**References** & **Components/Strategies** & **Objective of StadyFeatures** & **Algorithm** & **Achievements** & **Shortcomings/Recommendations** \\ \hline
[46, 47] & Strategic conversation &
\begin{tabular}{c} Utility-based DB program for \\ customers to change usage \\ patterns for incentives \\ \end{tabular} & A strategy for the efficient use of energy. & Customers’ states affect demand forecasts, \\  & & & & \\ \hline
[48] & Flexible Load Scheduling &
\begin{tabular}{c} A strategy with incentives and no \\ definite shapes for deterioration \\ of the system’s reliability \\ \end{tabular} & Good in improving the DC system’s autonomy. & May not be feasible in systems of unified \\ \hline
[49] & Load Shifting & \
\begin{tabular}{c} Minimize energy purchase traiffs \\ and reduce individual energy \\ bills \\ \end{tabular} & LP &
\begin{tabular}{c} Efficient management of energy storage \\ system and EV state of charge is achieved. \\ \end{tabular} & Load and weather data are required, including energy tariffs at building \\ \hline
[50] & Direct Load Control &
\begin{tabular}{c} Minimization of the total energy \\ price paid by the consumer \\ \end{tabular} & MILP & Reduction in the power consumption of appliances. & Issues relating to controlling indoor \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._Communication Technologies Implementation for Control and Automation Capabilities in Active Distribution Networks  
The main foundation for the management of ADNs is the ability of several entities, such as operators of DGs, aggregators, distributed system operators, and transmission system operators, to interact with each other for delivering monitoring, control, and real-time exchange of energy consumption and power usage data.