You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Review of Architectures and Concepts for Intelligence in Future Electric Energy Systems 
Chapter Title:  A. DR Programs 
1. Abstract of Cited Paper (BIB001):  Demand response and dynamic pricing programs are expected to play increasing roles in the modern smart grid environment. While direct load control of end-use loads has existed for decades, price driven response programs are only beginning to be explored at the distribution level. These programs utilize a price signal as a means to control demand. Active markets allow customers to respond to fluctuations in wholesale electrical costs, but may not allow the utility to control demand. Transactive markets, utilizing distributed controllers and a centralized auction, can be used to create an interactive system which can limit demand at key times on a distribution system, decreasing congestion. With the current proliferation of computing and communication resources, the ability now exists to create transactive demand response programs at the residential level. With the combination of automated bidding and response strategies, coupled with education programs and customer response, emerging demand response programs have the ability to reduce utility demand and congestion in a more controlled manner. This paper will explore the effects of a residential double-auction market, utilizing transactive controllers, on the operation of an electric power distribution system. 
2. Abstract of Cited Paper (BIB002):  The smart grid is conceived of as an electric grid that can deliver electricity in a controlled, smart way from points of generation to active consumers. Demand response (DR), by promoting the interaction and responsiveness of the customers, may offer a broad range of potential benefits on system operation and expansion and on market efficiency. Moreover, by improving the reliability of the power system and, in the long term, lowering peak demand, DR reduces overall plant and capital cost investments and postpones the need for network upgrades. In this paper a survey of DR potentials and benefits in smart grids is presented. Innovative enabling technologies and systems, such as smart meters, energy controllers, communication systems, decisive to facilitate the coordination of efficiency and DR in a smart grid, are described and discussed with reference to real industrial case studies and research projects.

Literature Review:
Nowadays, mainly due to both new regulatory and policy frameworks and new technologies, a great share of the enduse electrical loads can be engaged in DR programs in a more controlled manner. Automated control systems operating on a continual basis are replacing traditional load control systems, and these new systems are now available for commercial, industrial, and individual residential customers. Often, residential DR should be aggregated in order to compete in the wholesale energy markets. While the direct control of the end-use electrical loads existed for decades, price-driven response programs, using a price signal as a means for demand control, are beginning to emerge and to be the subject of study at the distribution level. Combining the automation of the demand bids and the strategies to respond to the growing user empowerment with respect to its domestic consumption, DR programs are the ideal solution to reduce demand power and prevent grid congestions. Diverse time-differentiated pricing models have been proposed, such as real-time, day-ahead, time-of-use, or criticalpeak pricing BIB003 . The basic ideas are the same for all these models; first, it is required that retail prices reflect fluctuations in wholesale prices so that users pay for what they consume at the market price and that users themselves are free to decide whether or when to buy the energy they need. In addition, these models encourage users to shift high loads during offpeak hours in order to reduce the cost of electricity and to help reduce the peak-to-average ratio of demand BIB001 . The authors in BIB002 aimed at evaluating the potential impact that the implementation of DR methodologies and the dynamic pricing could have on the operation of the electricity infrastructure. They state that models at multiple levels of analysis are essential in order to simulate a DR program using both a distributed and centralized control. Considering that DR techniques are moving toward approaches based on a more and more interactive model of communication, active, interactive, and transactive electricity markets are proposed. In an active market, a price signal is sent from the central controller to the end-use customer so that he can respond to price variations. In an interactive market, the end-use customer can also send information back to a central controller so that the price signal can be changed. In a transactive market, interactive controllers are used, which are also able to automatically operate on behalf of the end-use electrical load.