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Register a new userFlexibility Requirement when Tracking Renewable Power Fluctuation with Peer-to-Peer Energy Sharing
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Added by
Yue Chen
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Flexible load at the demand-side has been regarded as an effective measure to cope with volatile distributed renewable generations. To unlock the demand-side flexibility, this paper proposes a peer-to-peer energy sharing mechanism that facilitates energy exchange among users while preserving privacy. We prove the existence and partial uniqueness of the energy sharing market equilibrium and provide a centralized optimization to obtain the equilibrium. The centralized optimization is further linearized by a convex combination approach, turning into a multi-parametric linear program (MP-LP) with renewable output deviations being the parameters. The flexibility requirement of individual users is calculated based on this MP-LP. To be specific, an adaptive vertex generation algorithm is established to construct a piecewise linear estimator of the optimal total cost subject to a given error tolerance. Critical regions and optimal strategies are retrieved from the obtained approximate cost function to evaluate the flexibility requirement. The proposed algorithm does not rely on the exact characterization of optimal basis invariant sets and thus is not influenced by model degeneracy, a common difficulty faced by existing approaches. Case studies validate the theoretical results and show that the proposed method is scalable.
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Efforts to efficiently promote the participation of distributed energy resources in community microgrids require new approaches to energy markets and transactions in power systems. In this paper, we contribute to the promising approach of peer-to-peer (P2P) energy trading. We first formalize a centralized welfare maximization model of an economic dispatch with perfect information based on the value of consumption with zero marginal-cost energy. We characterize the optimal solution and corresponding price to serve as a reference for P2P approaches and show that the profit-maximizing strategy for individuals with storage in response to an optimal price is not unique. Second, we develop a novel P2P algorithm for negotiating energy trades based on iterative price and quantity offers that yields physically feasible and at least weakly Pareto-optimal outcomes. We prove that the P2P algorithm converges to the centralized solution in the case of two agents negotiating for a single period, demonstrate convergence for the multi-agent, multi-period case through a large set of random simulations, and analyze the effects of storage penetration on the solution.
The development of distributed generation technology is endowing consumers the ability to produce energy and transforming them into prosumers. This transformation shall improve energy efficiency and pave the way to a low-carbon future. However, it also exerts critical challenges on system operations, such as the wasted backups for volatile renewable generation and the difficulty to predict behavior of prosumers with conflicting interests and privacy concerns. An emerging business model to tackle these challenges is peer-to-peer energy sharing, whose concepts, structures, applications, models, and designs are thoroughly reviewed in this paper, with an outlook of future research to better realize its potentials.
In this letter we propose a generalized branch model to be used in DC optimal power flow (DCOPF) applications. Besides AC lines and transformers, the formulation allows for representing variable susceptance branches, phase shifting transformers, HVDC lines, zero impedance lines and open branches. The possibility to model branches with concurrently variable susceptance and controllable phase shift angles is also provided. The model is suited for use in DCOPF formulations aimed at the optimization of remedial actions so as to exploit power system flexibility; applications to small-, medium- and large-scale systems are presented to this purpose.
Scalability and security problems of the centralized architecture models in cyberphysical systems have great potential to be solved by novel blockchain based distributed models.A decentralized energy trading system takes advantage of various sources and effectively coordinates the energy to ensure optimal utilization of the available resources. It achieves that goal by managing physical, social and business infrastructures using technologies such as Internet of Things (IoT), cloud computing and network systems. Addressing the importance of blockchain-enabled energy trading in the context of cyberphysical systems, this article provides a thorough overview of the P2P energy trading and the utilization of blockchain to enhance the efficiency and the overall performance including the degree of decentralization, scalability and the security of the systems. Three blockchain based energy trading models have been proposed to overcome the technical challenges and market barriers for better adoption of this disruptive technology.
We consider a network of prosumers involved in peer-to-peer energy exchanges, with differentiation price preferences on the trades with their neighbors, and we analyze two market designs: (i) a centralized market, used as a benchmark, where a global market operator optimizes the flows (trades) between the nodes, local demand and flexibility activation to maximize the system overall social welfare; (ii) a distributed peer-to-peer market design where prosumers in local energy communities optimize selfishly their trades, demand, and flexibility activation. We first characterizethe solution of the peer-to-peer market as a Variational Equilibrium and prove that the set of Variational Equilibria coincides with the set of social welfare optimal solutions of market design (i). We give several results that help understanding the structure of the trades at an equilibriumor at the optimum. We characterize the impact of preferences on the network line congestion and renewable energy waste under both designs. We provide a reduced example for which we give the set of all possible generalized equilibria, which enables to give an approximation of the price ofanarchy. We provide a more realistic example which relies on the IEEE 14-bus network, for which we can simulate the trades under different preference prices. Our analysis shows in particular that the preferences have a large impact on the structure of the trades, but that one equilibrium(variational) is optimal.
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