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. Architectures 
1. Abstract of Cited Paper (BIB001):  This paper presents an architecture for a future electric power distribution system that is suitable for plug-and-play of distributed renewable energy and distributed energy storage devices. Motivated by the success of the (information) Internet, the architecture described in this paper was proposed by the NSF FREEDM Systems Center, Raleigh, NC, as a roadmap for a future automated and flexible electric power distribution system. In the envisioned “Energy Internet,” a system that enables flexible energy sharing is proposed for consumers in a residential distribution system. The key technologies required to achieve such a vision are presented in this paper as a result of the research partnership of the FREEDM Systems Center. 
2. Abstract of Cited Paper (BIB002):  This paper presents implementation of one of the Distributed Grid Intelligence (DGI) applications: Load Balancing, using the IEC61499 architecture. This enables system level design of distributed load balancing application with a direct pathway to deployment to hardware. The use of IEC 61499 improves scalability, re-configurability and maintainability of automation software. The application was deployed to commercial programmable automation devices and embedded controller (ARM based TS-7800). The application was verified using co-simulation approach: control and power system simulated using Matlab on PC networked with the number of distributed hardware running load balance algorithm. The use of IEC 61499 facilitates deployment of hardware independent function block model to the variety of compliant hardware.

Literature Review:
Automation architectures of future smart grids are being developed in a number of large-scale research programs worldwide. One significant research initiative is conducted by the center of Future Renewable Electric Energy Delivery and Management (FREEDM) funded by the National Science Foundation, USA. The FREEDM center envisions the backbone of the future grid to be a new power distribution infrastructure, allowing for integration of smart grid components in a "plugand-play" manner and enabling bidirectional flow of electricity BIB002 . This new energy delivery infrastructure is also denoted by "Energy Internet" or "Internet of Energy" BIB002 . This vision is akin to the (information) Internet. Fig. 5 illustrates the FREEDM vision. The core enabling technology is the SST BIB001 , which is a new generation power transformer using power electronics enabling bidirectional electricity flow and supports ac and dc buses for direct connection of components (e.g., DER and ESS). It is controlled by distributed grid intelligence (DGI), which consists of two types of nodes: intelligent energy management (IEM) and intelligent fault management (IFM). The first key feature of FREEDM is a plug-and-play interface, which enables components to seamlessly integrate with the rest of the grid. This interface includes an open and standard-based protocol, enabling interoperability and selfawareness of the devices. The second feature is an energy router or an IEM device. The IEM device is based on the SST concept. It manages the energy flow, provides power management, and has power-balancing capabilities. Furthermore, it manages connected DER, ESS, and flexible loads. The third feature is the DGI itself, formulated and implemented using open standards. To address the fundamental challenges in controlling large numbers of distributed devices and dynamic loads, new control theories and distributed agent-based algorithms are required and currently under development. The FREEDM center envisions that the major challenge will be implementing DGI applications in a distributed manner across multiple execution platforms (i.e., IEM and IFM). power-balancing DGI application on a network of ARM controllers BIB003 .