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Register a new userDesign of auction-based approach for market clearing in peer-to-peer market platform
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Added by
Mohsen Khorasany
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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This paper designs a market platform for Peer-to-Peer (P2P) energy trading in Transactive Energy (TE) systems, where prosumers and consumers actively participate in the market as seller or buyer to trade energy. An auction-based approach is used for market clearing in the proposed platform and a review of different types of auction is performed. The appropriate auction approach for market clearing in the proposed platform is designed. The proposed auction mechanism is implemented in three steps namely determination, allocation and payment. This paper identifies important P2P market clearing performance indices, which are used to compare and contrast the designed auction with different types of auction mechanisms. Comparative studies demonstrate the efficacy of the proposed auction mechanism for market clearing in the P2P platform.
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This paper proposes a market clearing mechanism for energy trading in a local transactive market, where each player can participate in the market as seller or buyer and tries to maximize its welfare individually. Market players send their demand and supply to a local data center, where clearing price is determined to balance demand and supply. The topology of the grid and associated network constraints are considered to compute a price signal in the data center to keep the system secure by applying this signal to the corresponding players. The proposed approach needs only the demanded/supplied power by each player to reach global optimum which means that utility and cost function parameters would remain private. Also, this approach uses distributed method by applying local market clearing price as coordination information and direct load flow (DLF) for power flow calculation saving computation resources and making it suitable for online and automatic operation for a market with a large number of players. The proposed method is tested on a market with 50 players and simulation results show that the convergence is guaranteed and the proposed distributed method can reach the same result as conventional centralized approach.
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.
Blockchain is increasingly being used as a distributed, anonymous, trustless framework for energy trading in smart grids. However, most of the existing solutions suffer from reliance on Trusted Third Parties (TTP), lack of privacy, and traffic and processing overheads. In our previous work, we have proposed a Secure Private Blockchain-based framework (SPB) for energy trading to address the aforementioned challenges. In this paper, we present a proof-on-concept implementation of SPB on the Ethereum private network to demonstrates SPBs applicability for energy trading. We benchmark SPBs performance against the relevant state-of-the-art. The implementation results demonstrate that SPB incurs lower overheads and monetary cost for end users to trade energy compared to existing solutions.
A multiagent based model for a system of cooperative agents aiming at growth is proposed. This is based on a set of generalized Verhulst-Lotka-Volterra differential equations. In this study, strong cooperation is allowed among agents having similar sizes, and weak cooperation if agent have markedly different sizes, thus establishing a peer-to-peer modulated interaction scheme. A rigorous analysis of the stable configurations is presented first examining the fixed points of the system, next determining their stability as a function of the model parameters. It is found that the agents are self-organizing into clusters. Furthermore, it is demonstrated that, depending on parameter values, multiple stable configurations can coexist. It occurs that only one of them always emerges with probability close to one, because its associated attractor dominates over the rest. This is shown through numerical integrations and simulations,after analytic developments. In contrast to the competitive case, agents are able to increase their capacity beyond the no-interaction case limit. In other words, when some collaborative partnership among a relatively small number of partners takes place, all agents act in good faith prioritizing the common good, whence receiving a mutual benefit allowing them to surpass their capacity.
We propose measurement integrity, a property related to ex post reward fairness, as a novel desideratum for peer prediction mechanisms in many applications, including peer assessment. We operationalize this notion to evaluate the measurement integrity of different mechanisms in computational experiments. Our evaluations simulate the application of peer prediction mechanisms to peer assessment---a setting in which realistic models have been validated on real data and in which ex post fairness concerns are quite salient. We find that peer prediction mechanisms, as proposed in the literature, largely fail to demonstrate measurement integrity in our experiments. However, we also find that certain mechanisms can be supplemented with realistic parametric statistical models to improve their measurement integrity. In the same setting, we also evaluate an empirical notion of robustness against strategic behavior to complement the theoretical analyses of robustness against strategic behavior that have been the main focus of the peer prediction literature. In this dimension of analysis, we again find that supplementing certain mechanisms with parametric statistical models can improve their empirical performance. Even so, though, we find that theoretical guarantees of robustness against strategic behavior are somewhat noisy predictors of empirical robustness. As a whole, our empirical methodology for quantifying desirable mechanism properties facilitates a more nuanced comparison between mechanisms than theoretical analysis alone. Ultimately, we find there is a trade-off between our two dimensions of analysis. The best performing mechanisms for measurement integrity are highly susceptible to strategic behavior. On the other hand, certain parametric peer prediction mechanisms are robust against all the strategic manipulations we consider while still achieving reasonable measurement integrity.
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