788 research outputs found
Towards transactive energy systems: An analysis on current trends
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
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
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
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
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
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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