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The introduction of Smart Grid resulted in the development of various applications that are built upon the concept of bi-directional flow of electricity and data. One of the Smart Grids pillars is the Distributed Generation (DG) technologies, where customers turn to be prosumers with power generation capability. Another pillar is the Demand Side Management (DSM), which helps control the energy consumption by changing the power usage slots among other peers. DG and DSM have facilitated the sharing of excess power by customers to the grid, and then to their peers through the grid as a trading agent. Although the concept of integrating Peer-to-Peer energy trading with DSM has been explored by scholars and relatively established trading frameworks, there are very limited research performed in respect to the UAE market in terms of its acceptance and readiness towards this energy trading market. This research aims to explore the perception of Peer-to-Peer electricity trading within the Power Distribution Network in the United Arab Emirates. The study will review the Smart Grid network in the UAE and will obtain insights on people's perception of the transition from classical electricity network to Smart Grid. It will also look into peoples' perception regarding the transition from being electricity consumers to being electricity producers that trade among peers through semi-structured interviews. This will enhance the understanding of the energy trading market between self-generated power producers connected to a network grid, where the consumer will be utilizing the excess power available in the form of electricity trading, by importing and exporting power, without adding any additional power to the grid. The outcome of the study will provide an insight on the UAE electricity market by designing an electricity trading model that is built upon the following vital factors: power quality, supply reliability, type of integration, peers, and trading time. Furthermore, the study will provide a foundation base to the utilities, as well as individuals, when dealing with the changes in the electricity market structure. [ABSTRACT FROM AUTHOR]

With smart grid, the power supply will shift from the 1∶N tree structure with centralized power plants to the M∶N structure with various kinds of distributed energy resources based on renewable energy, batteries, and so on. Deregulation of the electricity market will yield a truly competitive market, where anyone can become a power seller or buyer, which will necessitate a real-time multiseller–multibuyer power trading system. However, it is difficult to realize such a system without centralized control, because of the additional trade complexity created by a large number of sellers, including ordinary homes. In this paper, the authors propose a novel distributed power cooperation algorithm that maximizes each home’s welfare based on local information. The proposed algorithm enables each home to calculate the same electricity market price from only local household information, to trade, and to maximize all members’ satisfaction in smart grid by balancing consumption against supply. The authors formulate a distributed optimization problem and logically prove that the authors’ algorithm can obtain the same optimal user welfare as the global optimal approach but within a much shorter time. [ABSTRACT FROM AUTHOR]

Local energy production and distributed energy storage facilities will take a prominent position in the future smart grid along with the challenge of sustainability. To cope with that, smart grid simulation platforms are needed in order to analyze the problems of two-way data and energy flow. The Power Trading Agent Competition (Power TAC) provides an open source, smart grid simulation platform to enable various smart grid studies from the perspective of sustainability. In this paper, we present AgentUDE, which competed in the Power TAC 2014 and 2015 Final games as a broker agent. Here, we create and formalize information system artefacts for the electricity trading problem in a continuous and competitive environment. The main trading problem is partitioned to smaller problems to reduce the complexity. Therefore, wholesale and retail electricity market activities are individually discussed for AgentUDE14. In 2015 competition, we added a capacity control capability to AgentUDE14, which was introduced as AgentUDE15. We show that AgentUDE is a successful broker agent in many metrics, analyzing its performance in controlled experiments and international tournaments. We have also reviewed the tournament data from the winner agent's point of view [ABSTRACT FROM AUTHOR]

In this paper, we propose an autonomous microgrid operation using a multiagent approach. The proposed multiagent system consists of seven types of agent: a single microgrid controller agent (MGC), several load agents (LAGs), several gas-turbine (gas-engine) agents (GAGs), several photovoltaic generation agents (PVAGs), several wind-turbine generation agents (WTAGs), several battery agents (BAGs), and a single grid agent (GridAG). In a microgrid, LAGs act as consumers or buyers, GAGs, PVAGs, and WTAGs act as producers or sellers, and BAGs act as prosumers or sellers/buyers. In order to verify the performance of the proposed system, it is applied to a simple model system with different electrical power prices. From the simulation results, it can be seen that the proposed multiagent system can perform microgrid operations efficiently. [ABSTRACT FROM AUTHOR]