P2P market coordination methodologies with distribution grid management

Faria, António Sérgio; Soares, Tiago; Orlandini, Tommaso; Oliveira, Catarina; Sousa, Tiago; Matos, Manuel

doi:10.1016/j.segan.2023.101075

Cited by 7 publications

(2 citation statements)

References 26 publications

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“…Without these incentives, there may be little motivation for participants to move away from existing BAU contracts and engage with the LEM [5]. Another aspect is the assured advantage of managing the power grid by repeatedly coordinating with the LEM [6]. Additionally, it is necessary to determine the economic advantages of various other distribution utilities, such as energy retailers, network operators, and market operators, to introduce the LEM in practice [7].…”

Section: Introductionmentioning

confidence: 99%

Integrating Forecasting Service and Gen2 Blockchain Into a Local Energy Trading Platform to Promote Sustainability Goals

Ali,

Azim,

Ojha

et al. 2024

IEEE Access

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Peer-to-peer (P2P) trading in a local energy market (LEM) offers various participants the opportunity to negotiate and strike energy deals among themselves using a distributed ledger technology called blockchain. In this paper, a new local model is presented using a layer-2 scalability solution for secondgeneration (Gen2) blockchain technology to enable P2P trading among four types of participants: consumers, prosumers with solar photovoltaic (PV) systems, prosumers with solar PV systems and battery energy storage systems (BESSs), and electric vehicles (EVs). The proposed LEM trading platform involves several critical steps, including the creation of typical forecasting profiles for load consumption, solar generation, and battery state-of-charge (SOC) through a forecasting solution. Next, the LEM participants place their pricing bids using a trading agent service, and the trading engine collects the profiles data and bid prices, which performs matchmaking in a forward-facing market. The output of the trading engine consists of dispatch signals for prices and energy values that are sent to each participant to execute actual trading. Furthermore, the trading engines store the accepted and past bidding data and energy values of P2P trades for each participant in blockchain technology, which can be retrieved and displayed on the LEM user interface screens of participants and administrators using their blockchain addresses at any time during the trading process. This study focuses on simulating proposed LEM models, incorporating functional limitations and market rules. These rules aim to reduce energy costs, enhance margins for utilities and retailers, and mitigate grid congestion through BESSs, resulting in reduced operational and capital expenditure. LEM outcomes are analysed and compared with a Business-as-usual (BAU) model. Participants' energy trading behaviour, costrevenue dynamics, grid impact, and blockchain implementation costs are explored. The study highlights LEM benefits in terms of reduced CO2 emissions by 984 kg CO2, increased self-sufficiency by 2.2%, and improved financial benefits of all participants by 21.6%. The use of modern blockchain technology guarantees secure data storage and rapid, cost-effective energy trading, thereby making the proposed LEM platform a viable solution in the distribution market.INDEX TERMS Blockchain technology, forecasting service, LEM, P2P energy trading, smart contracts.

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Section: Introductionmentioning

confidence: 99%

Integrating Forecasting Service and Gen2 Blockchain Into a Local Energy Trading Platform to Promote Sustainability Goals

Ali,

Azim,

Ojha

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…To achieve this goal, they provide incentives for renewable energy integration and uptake of energy efficiency technologies [4]. P2P energy trading technologies can help achieve such goals by enhancing the adoption of renewable energy technologies and reducing carbon emissions [5][6][7]. The existing energy market mechanisms often fail to manage the new challenges arising with changes in the energy mix.…”

Section: Introductionmentioning

confidence: 99%

A Review of Peer-to-Peer Energy Trading Markets: Enabling Models and Technologies

Islam

2024

Energies

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This paper presents a detailed review of the existing literature on peer-to-peer (P2P) energy trading considering market architectures, trading strategies, and enabling technologies. P2P energy trading enables individual users in the electricity network to act as sellers or buyers and trade energy among each other. To facilitate the discussion on different aspects of P2P energy trading, this paper focuses on P2P market mechanisms, relevant bidding strategies, and auction models. In addition, to solve the energy management problems associated with P2P energy trading, this paper investigates widely used solution methods such as game-theoretic models, mathematical optimisation, as well as more recent machine learning techniques and evaluates them in a critical manner. The outcomes of this investigation along with the identification of the challenges and limitations will allow researchers to find suitable P2P energy trading mechanisms based on different market contexts. Moreover, the discussions on potential future research directions are expected to improve the effectiveness of P2P energy trading technologies.

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Hybrid local energy markets: Incorporating utility function-based peer risk attributes, renewable energy integration, and grid constraints analysis

Moradi,

Farzaneh

2024

Energy Conversion and Management: X

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P2P market coordination methodologies with distribution grid management

Cited by 7 publications

References 26 publications

Integrating Forecasting Service and Gen2 Blockchain Into a Local Energy Trading Platform to Promote Sustainability Goals

Integrating Forecasting Service and Gen2 Blockchain Into a Local Energy Trading Platform to Promote Sustainability Goals

A Review of Peer-to-Peer Energy Trading Markets: Enabling Models and Technologies

Hybrid local energy markets: Incorporating utility function-based peer risk attributes, renewable energy integration, and grid constraints analysis

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