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Register a new userDecentralized Provision of Renewable Predictions within a Virtual Power Plant
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The mushrooming of distributed energy resources turns end-users from passive price-takers to active market participants. To manage those massive proactive end-users efficiently, virtual power plant (VPP) as an innovative concept emerges. It can provide some necessary information to help consumers improve their profits and trade with the electricity market on behalf of them. One important information that is desired by the consumers is the prediction of renewable outputs inside this VPP. Presently, most VPPs run in a centralized manner, which means the VPP predicts the outputs of all the renewable sources it manages and provides the predictions to every consumer who buys this information. We prove that by providing predictions, the social total surplus can be improved. However, when more consumers and renewables participate in the market, this centralized scheme needs extensive data communication and may jeopardize the privacy of individual stakeholders. In this paper, we propose a decentralized prediction provision algorithm in which consumers from each subregion only buy local predictions and exchange information with the VPP. Convergence is proved under a mild condition, and the demand gap between centralized and decentralized schemes is proved to have zero expectation and bounded variance. Illustrative examples show that the variance of this gap decreases with more consumers and higher uncertainty, and validate the proposed algorithm numerically.
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The prevalence of distributed generation drives the emergence of the Virtual Power Plant (VPP) paradigm. A VPP aggregates distributed energy resources while operating as a conventional power plant. In recent years, several renewable energy sources have been installed in the commercial/industrial/residential building sector and they lend themselves for possible aggregation within the VPP operations. At present, building-side energy resources are usually managed by building energy management systems (BEMSs) with autonomous objectives and policies, and they are usually not setup to be directly controlled for the implementation of a VPP energy management system. This article presents a Building VPP (BVPP) architecture that aggregates building-side energy resources through the communication between the VPP energy management system and autonomous BEMSs. The implementation technologies, key components, and operation modes of BVPPs are discussed. Case studies are reported to demonstrate the effectiveness of BVPP in different operational conditions.
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