788 research outputs found

    Towards transactive energy systems: An analysis on current trends

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    This paper presents a comprehensive analysis on the latest advances in transactive energy systems. The main contribution of this work is centered on the definition of transactive energy concepts and how such systems can be implemented in the smart grid paradigm. The analyzed works have been categorized into three lines of research: (i) transactive network management; (ii) transactive control; and (iii) peer-to-peer markets. It has been found that most of the current approaches for transactive energy are available as a model, lacking the real implementation to have a complete validation. For that purpose, both scientific and practical aspects of transactive energy should be studied in parallel, implementing adequate simulation platforms and tools to scrutiny the results.This work has received funding from the European Union's Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No. 771066) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2019.info:eu-repo/semantics/publishedVersio

    On an Information and Control Architecture for Future Electric Energy Systems

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    This paper presents considerations towards an information and control architecture for future electric energy systems driven by massive changes resulting from the societal goals of decarbonization and electrification. This paper describes the new requirements and challenges of an extended information and control architecture that need to be addressed for continued reliable delivery of electricity. It identifies several new actionable information and control loops, along with their spatial and temporal scales of operation, which can together meet the needs of future grids and enable deep decarbonization of the electricity sector. The present architecture of electric power grids designed in a different era is thereby extensible to allow the incorporation of increased renewables and other emerging electric loads.Comment: This paper is accepted, to appear in the Proceedings of the IEE

    Joint Chance-constrained Game for Coordinating Microgrids in Energy and Reserve Markets: A Bayesian Optimization Approach

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    Microgrids incorporate distributed energy resources (DERs) and flexible loads, which can provide energy and reserve services for the main grid. However, due to uncertain renewable generations such as solar power, microgrids might under-deliver reserve services and breach day-ahead contracts in real-time. If multiple microgrids breach their reserve contracts simultaneously, this could lead to a severe grid contingency. This paper designs a distributionally robust joint chance-constrained (DRJCC) game-theoretical framework considering uncertain real-time reserve provisions and the value of lost load (VoLL). Leveraging historical error samples, the reserve bidding strategy of each microgrid is formulated into a two-stage Wasserstein-metrics distribution robust optimization (DRO) model. A JCC is employed to regulate the under-delivered reserve capacity of all microgrids in a non-cooperative game. Considering the unknown correlation among players, a novel Bayesian optimization method approximates the optimal individual violation rates of microgrids and market equilibrium. The proposed game framework with the optimal rates is simulated with up to 14 players in a 30-bus network. Case studies are conducted using the California power market data. The proposed Bayesian method can effectively regulate the joint violation rate of the under-delivered reserve and secure the profit of microgrids in the reserve market.Comment: Received and Revised in 2023; IEEE Journa

    A robust energy and reserve dispatch model for prosumer microgrids incorporating demand response aggregators

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    Abstract: The uncertainty introduced by intermittent renewable energy generation and prosumer energy imports makes operational planning of renewable energy‐assisted prosumer microgrids challenging. This is due to the difficulty in obtaining accurate forecasts of energy expected from these renewable energy sources and prosumers. Operators of such microgrids therefore require additional grid‐balancing tools to maintain power supply and demand balance during grid operation. In this paper, the impact of demand response aggregators (DRA’s) in a prosumer microgrid is investigated. This is achieved by developing and solving a deterministic mathematical formulation for the operational planning of the grid. Also, taking a cue from CAISO’s proposed tariff revision which allows the state‐of‐charge of non‐generator resources (like storage units) to be submitted as a bid parameter in the day‐ahead market and permits scheduling coordinators of these resources to self‐manage their energy limits and state‐of‐charge, the proposed formulation permits prosumers to submit battery energy content as a bid parameter and self‐manage their battery energy limits. Furthermore, a robust counterpart of the model is developed. Both formulations are constrained mixed integer optimization problems which are solved using the CPLEX solver in Advanced Interactive Multidimensional Modelling System (AIMMS) environment. Results obtained from tests carried out on a hypothetical prosumer microgrid show that the operating cost of the microgrid reduces in the presence of DRA’s. In addition, the storage facility owner may benefit from self‐managing its energy limits, but this may cut the amount of grid‐balancing resource available to the microgrid operator, thereby increasing the operating cost of the microgrid

    Consensus-based approach to peer-to-peer electricity markets with product differentiation

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    With the sustained deployment of distributed generation capacities and the more proactive role of consumers, power systems and their operation are drifting away from a conventional top-down hierarchical structure. Electricity market structures, however, have not yet embraced that evolution. Respecting the high-dimensional, distributed and dynamic nature of modern power systems would translate to designing peer-to-peer markets or, at least, to using such an underlying decentralized structure to enable a bottom-up approach to future electricity markets. A peer-to-peer market structure based on a Multi-Bilateral Economic Dispatch (MBED) formulation is introduced, allowing for multi-bilateral trading with product differentiation, for instance based on consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is described to solve the MBED in fully decentralized manner. A set of realistic case studies and their analysis allow us showing that such peer-to-peer market structures can effectively yield market outcomes that are different from centralized market structures and optimal in terms of respecting consumers preferences while maximizing social welfare. Additionally, the RCI solving approach allows for a fully decentralized market clearing which converges with a negligible optimality gap, with a limited amount of information being shared.Comment: Accepted for publication in IEEE Transactions on Power System

    Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

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    Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac
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