Transactive energy is a novel approach for energy management and trading, which can be used in microgrids to facilitate the integration of distributed energy resources (DERs) in existing networks. The key feature in transactive energy is using market-based solutions for energy management. Hence, an appropriate transactive energy market (TEM) framework should be designed to enable and incentivize DER owners to participate in different markets. The efficient implementation of TEM for microgrid energy management encompasses the application of a variety of design principles. In this rapidly developing area, this paper presents a complete proposal of the TEM as a framework for the design, implementation, and deployment of transactive energy solutions for energy management in microgrids. In particular, we outline the requirements to design an effective market mechanism for the TEM. The applicability of this perspective is demonstrated through the introduction of the Monash Microgrid as a real-world implementation of a TEM solution, where a complete hardware and software foundation is presented as a platform to deploy a market-based solution for microgrid energy management. This is further illustrated through an example scenario, where the application of TEM is discussed to demonstrate the impact of considered design choices on achieving desired objectives.
The home energy management problem has many different facets, including economic viability, data uncertainty and quality of strategy employed. The existing literature in this area focuses on individual aspects of this problem without a detailed, holistic analysis of the results with regards to practicality in implementation. In this paper, we fill this gap by performing a comprehensive comparison of seven different energy management strategies, each with different levels of practicality, sophistication and computational requirements. We analyse the results in the context of these three characteristics, and also critique the modelling assumptions made by each strategy. Our analysis finds that using a more sophisticated energy management strategy may not necessarily improve the performance and economic viability of the PV-battery system due to the effects of modeling assumptions, such as the treatment of uncertainties in the input data and battery degradation effects.
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