9,620 research outputs found
A real-time pricing scheme for residential energy systems using a market maker
Voltage rise is an undesirable side-effect of solar photovoltaic (PV) generation, arising from the flow of surplus electrical power back into the grid when PV generation exceeds local demand. Customers deploying residential-scale battery storage are likely to further exacerbate voltage rise problems for electrical utilities unless the charge/discharge schedules of batteries are appropriately coordinated. In this paper, we present a real-time pricing mechanism for use in a network of distributed residential energy systems (RESs), each employing solar PV generation and battery storage. The pricing mechanism proposed in this paper is based on a Market Maker algorithm in which predicted power profiles and real-time pricing information is iteratively exchanged between a central entity and each of the RESs. The Market Maker formulation presented in this paper is shown via simulation studies to converge to a fixed price vector, thereby reducing the price volatility observed in an earlier formulation, while achieving the same reduction in power usage variability as a centralised model predictive control (MPC) scheme presented previously
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
Feasibility of Using Discriminate Pricing Schemes for Energy Trading in Smart Grid
This paper investigates the feasibility of using a discriminate pricing
scheme to offset the inconvenience that is experienced by an energy user (EU)
in trading its energy with an energy controller in smart grid. The main
objective is to encourage EUs with small distributed energy resources (DERs),
or with high sensitivity to their inconvenience, to take part in the energy
trading via providing incentive to them with relatively higher payment at the
same time as reducing the total cost to the energy controller. The proposed
scheme is modeled through a two-stage Stackelberg game that describes the
energy trading between a shared facility authority (SFA) and EUs in a smart
community. A suitable cost function is proposed for the SFA to leverage the
generation of discriminate pricing according to the inconvenience experienced
by each EU. It is shown that the game has a unique sub-game perfect equilibrium
(SPE), under the certain condition at which the SFA's total cost is minimized,
and that each EU receives its best utility according to its associated
inconvenience for the given price. A backward induction technique is used to
derive a closed form expression for the price function at SPE, and thus the
dependency of price on an EU's different decision parameters is explained for
the studied system. Numerical examples are provided to show the beneficial
properties of the proposed scheme.Comment: 7 pages, 4 figures, 3 tables, conference pape
Smart Grid Enabling Low Carbon Future Power Systems Towards Prosumers Era
In efforts to meet the targets of carbon emissions reduction in power systems, policy makers formulate measures for facilitating the integration of renewable energy sources and demand side carbon mitigation. Smart grid provides an opportunity for bidirectional communication among policy makers, generators and consumers. With the help of smart meters, increasing number of consumers is able to produce, store, and consume energy, giving them the new role of prosumers. This thesis aims to address how smart grid enables prosumers to be appropriately integrated into energy markets for decarbonising power systems.
This thesis firstly proposes a Stackelberg game-theoretic model for dynamic negotiation of policy measures and determining optimal power profiles of generators and consumers in day-ahead market. Simulation results show that the proposed model is capable of saving electricity bills, reducing carbon emissions, and increasing the penetration of renewable energy sources. Secondly, a data-driven prosumer-centric energy scheduling tool is developed by using learning approaches to reduce computational complexity from model-based optimisation. This scheduling tool exploits convolutional neural networks to extract prosumption patterns, and uses scenarios to analyse possible variations of uncertainties caused by the intermittency of renewable energy sources and flexible demand. Case studies confirm that the proposed scheduling tool can accurately predict optimal scheduling decisions under various system scales and uncertain scenarios. Thirdly, a blockchain-based peer-to-peer trading framework is designed to trade energy and carbon allowance. The bidding/selling prices of individual prosumers can directly incentivise the reshaping of prosumption behaviours. Case studies demonstrate the execution of smart contract on the Ethereum blockchain and testify that the proposed trading framework outperforms the centralised trading and aggregator-based trading in terms of regional energy balance and reducing carbon emissions caused by long-distance transmissions
Recent techniques used in home energy management systems: a review
Power systems are going through a transition period. Consumers want more active participation in electric system management, namely assuming the role of producers–consumers, prosumers in short. The prosumers’ energy production is heavily based on renewable energy sources, which, besides recognized environmental benefits, entails energy management challenges. For instance, energy consumption of appliances in a home can lead to misleading patterns. Another challenge is related to energy costs since inefficient systems or unbalanced energy control may represent economic loss to the prosumer. The so-called home energy management systems (HEMS) emerge as a solution. When well-designed HEMS allow prosumers to reach higher levels of energy management, this ensures optimal management of assets and appliances. This paper aims to present a comprehensive systematic review of the literature on optimization techniques recently used in the development of HEMS, also taking into account the key factors that can influence the development of HEMS at a technical and computational level. The systematic review covers the period 2018–2021. As a result of the review, the major developments in the field of HEMS in recent years are presented in an integrated manner. In addition, the techniques are divided into four broad categories: traditional techniques, model predictive control, heuristics and metaheuristics, and other techniques.info:eu-repo/semantics/publishedVersio
Blockchain electricity trading using tokenised power delivery contracts. ESRI Working Paper No. 649 December 2019
This paper proposes a new mechanism for forward selling renewable electricity generation. In this transactive
framework, a wind or solar farm may directly sell to consumers a claim on their future power output in the form of nonfungible
blockchain tokens. Using the flexibility of smart contract code, which executes irrevocably on a blockchain, the realised
generation levels will offset the token holders’ electricity consumption in near real-time. To elucidate the flexibility offered by
such smart contracts, two ways of structuring these power delivery instruments are considered: firstly, an exotic tranched
system, where more senior tokens holders enjoy priority claims on power, as compared against a simpler pro-rata scheme,
where the realised output of a generator is equally apportioned between token holders. A notional market simulation is
provided to explore whether, for instance, consumers could exploit the flatter power delivery profiles of more senior tranches to
better schedule their responsive demands
Proceedings of the Australian Summer Study on Energy Productivity
This collection includes the peer-reviewed papers presented during the 2016 Australian Summer Study on Energy Productivity
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