Peer-to-Peer Energy Trading in a Micro-grid Using Internet of Things and Blockchain

With advancements in renewable energy techno­logies, consumers are becoming prosumers, and renewable energy resources are being used in distributed networks. In an isolated distributed system, peer-to-peer (P2P) energy trading is one of the most promising energy management solutions. In this paper, we propose a P2P energy trading method for micro-grids using open resources and technology. The proposed setup comprises an Internet of Things (IoT) server to transfer energy amongst the peers without human intervention, and an Ethereum based private blockchain is suggested for money transfer in the form of cryptocurrency. The IoT server enables the peers to control and monitor self-produced energy. Arduino UNO, ACS 712 hall-effect current sensor, and a relay are the main components used in the hardware setup. The current sensor data is sent in real- time to Arduino for onward communication to the IoT server. A user-friendly interface has been developed on the server to perform various energy trading tasks. Peers have the choice to access the server remotely to perform energy trading tasks. The energy trading events can be shared amongst peers through e-mail notifications. For financial transactions, we utilized Ganache graphical user interface (GUI) a private Ethereum blockchain eliminating the need for financial institutions. The proposed peer-to-peer energy trading model has been successfully tested for energy trading between two peers. This paper provides details of the proposed hardware and software setup and explains how low-cost P2P energy trading can be achieved.

Decentralized P2P Electricity Trading Model for Thailand

Thailand’s power system has been facing an energy transition due to the increasing amount of Renewable Energy (RE) integration, prosumers with self-consumption, and digitalization-based business models in a Local Energy Market (LEM). This paper introduces a decentralized business model and a possible trading platform for electricity trading in Thailand’s Micro-Grid to deal with the power system transformation. This approach is Hybrid P2P, a market structure in which sellers and buyers negotiate on energy exchanging by themselves called Fully P2P trading or through the algorithm on the market platform called Community-based trading. A combination of Auction Mechanism (AM), Bill Sharing (BS), and Traditional Mechanism (TM) is the decentralized price mechanism proposed for the Community-based trading. The approach is validated through a test case in which, during the daytime, the energy import and export of the community are significantly reduced when 75 consumers and 25 PV rooftop prosumers participate in this decentralized trading model. Furthermore, a comparison analysis confirms that the decentralized business model outperforms a centralized approach on community and individual levels.

Optimisation and Management of Virtual Power Plants Energy Mix Trading Model

. In this study, a robust optimisation method (ROM) is proposed with aim to achieve optimal scheduling of virtual power plants (VPPs) in the day-ahead electricity markets where electricity prices are highly uncertain. Our VPP is a collection of various distributed energy resources (DERs), flexible loads, and energy storage systems that are coordinated and operated as a single entity. In this study, an offer and bid-based energy trading mechanism is proposed where participating members in the VPP setting can sell or buy to/from the day-ahead electricity market to maximise social welfare (SW). SW is defined as the maximisation of end-users benefits and minimisation of energy costs. The optimisation problem is solved as a mixed-integer linear programming model taking the informed decisions at various levels of uncertainty of the market prices. The benefits of the proposed approach are consistency in solution accuracy and traceability due to less computational burden and this would be beneficial for the VPP operators. The robustness of the proposed mathematical model and method is confirmed in a case study approach using a distribution system with 18-buses. Simulation results illustrate that in the highest robustness scenario, profit is reduced marginally, however, the VPP showed robustness towards the day-ahead market (DAM) price uncertainty

PV Energy Communities—Challenges and Barriers from a Consumer Perspective: A Literature Review

Renewable energy sources, in particular those based on solar radiation, are growing rapidly and are planned to play an instrumental role in building power systems to reach the 2030 and 2050 energy and climate mitigation objectives. However, new actors have been introduced into the energy field, highlighting the importance of the role of citizens and communities in building such energy systems. To outline the significance of citizens in the development of solar energy communities and to describe the benefits of and barriers to their implementation so far, a comprehensive literature review has been carried out based on 64 thoroughly selected, reliable scientific publications (published within 2015–2021), revealing the latest trends, technologies and research in this field. The research focuses on four consumer interest areas: policy, economic, technical and social, covering the following subsections: policy, trading model, economic assessment, business model, energy management, demand response, modelling tools and consumer adoption. Within each subsection the conducted review seeks to answer the questions related to the further development and implementation of PV energy communities, considering consumer needs and revealing the possible solutions.

Composition of portfolios by pairs trading with volatility criteria in the Brazilian market,

ABSTRACT The objective of this study was to understand how the shares’ volatility affects the portfolios’ dynamics formed using the model of pairs trading in the Brazilian stock market. This article distinguished itself by bringing new evidence about the effects of volatility in the pairs trading model not covered by previous studies, expanding the sample size analyzed in the Brazilian stock market. The chosen theme’s relevance is that investors can use pairs trading or long-short models to build their portfolios. The use of cointegration concepts probabilistically contributes to portfolios’ formation weakly correlated to the market indexes with superior performance. This article impacts the area by contributing new evidence for better use of the model in the analysis of investments. From January 2016 to December 2018, the 90 most liquid assets of Bolsa, Brasil, Balcão (B3) were analyzed, totaling 5,927,400 possible pairs. The Augmented Dickey-Fuller test and subsequent backtesting of the pairs in the proposed period were used to evaluate the cointegration criteria. Statistical analysis was performed by parametric and non-parametric tests and Pearson and Spearman correlation analyses. The results found indicated that the formation of portfolios by pairs trading with dependent assets with the criterion of higher levels of volatility (20 periods) presented a superior performance. These findings can be justified by a better risk and return ratio for the portfolio, measured by the Sharpe Index of the returns obtained concerning the portfolio’s volatility, compared to a portfolio formation based on a random selection of the pairs. In addition, the results also showed a low correlation of returns concerning the market index. Therefore, the application of the statistical cointegration analysis methodology alone does not guarantee results that are different from the market average.