Blockchain Papers

Saumendra Das, H. Swapnarekha, S. Vimal

No abstract is available for this record.

Stephan Groß, Stefan Lankes, Ferdinanda Ponci, Antonello Monti

No abstract is available for this record.

Yu‐Chung Tsao, Wen-Hsiang Chiu

No abstract is available for this record.

Partha Pratim Bhattacharjee, Chaitali Koley, Saibal Chatterjee

No abstract is available for this record.

Ehsan Heydarian-Forushani, Seifeddine Ben Elghali

This book provides a general overview of virtual power plants (VPP) as a key technology in future energy communities and active distribution and transmission networks for managing distributed energy resources, providing local and global services, and facilitating market participation of small-scale managing distributed energy resources and prosumers. The book also aims at describing some practical solutions, business models, and novel architectures for the implementation of VPPs in the real world. Each chapter of the book begins with the fundamental structure of the problem required for a rudimentary understanding of the methods described. It provides a clear picture for practical implementation of VPP through novel technologies such as blockchain, digital twin, and distributed ledger technology. The book will help the electrical and power engineers, undergraduate, graduate students, research scholars, and utility engineers to understand the emerging solutions regarding the VPP concept lucidly.

Liaqat Ali, M. Imran Azim, Jan Peters, Vivek Bhandari · 8 authors

This paper presents the application of a community battery energy storage system (CBESS)-integrated microgrid (MG) in a blockchain-enabled local energy market (LEM). The proposed LEM balances the community energy requirement while facilitating frequent peer-to-peer (P2P) energy transactions between several energy users in the presence of both energy supplier and energy operator. The architecture is formulated by taking a number of local market and network constraints, that include residential battery energy storage system (RBESS) constraints; CBESS constraints; P2P traded price constraints; P2P traded power constraints; margin constraints of the stakeholders; power grid export and import constraints; and network energy balance constraints, so as to not only incentivise energy users but also reduce import/export from/to power grid while keeping the margins of energy supplier and energy operator unaffected. Different types of transactions data including energy users’ P2P pricing bids and P2P traded energy volume are also stored in the blockchain database. Further, the developed LEM framework is also validated through a case study executed on an actual Australian power grid network, comprising 260 residential energy users; two energy suppliers; an energy operator; and a CBESS, and the performance of the proposed P2P trading-based LEM strategy is compared with the existing business-as-usual (BAU) that directs energy users to buy/sell energy at the time-of-use (ToU)/ feed-in-tariff (FiT) rate. The extensive and comparative simulation results confirm the superior performance of the proposed LEM mechanism in terms of minimising energy users’ electricity bill; lowering power grid import and export; and retaining margins of energy suppliers and the energy operator; and thus, emphasise its application suitability in the current electricity market.

Fazel Mohammadi, Mehrdad Saif

Blockchain is a distributed decentralized peer-to-peer network, which is used for sharing data across a large number of entities in a trusted and secure way. Blockchain utilizes different mechanisms, such as hash functions, consensus algorithms, etc., for data verification and validation. In modern power systems, blockchain technology is used for balancing supply and demand, contributing to the demand-side management programs, and mainly, transitioning consumers to prosumers to trade electricity and reduce operational costs. This article aims at providing an in-depth discussion on energy transition and digitalization in power systems and investigating the role of blockchain technology in modern power systems. In addition, opportunities, challenges, and limitations of blockchain technology in modern power systems are discussed.

Nitima Malsa, Tushar Srivastave, Utkarsh Sahni, Suraj Garg · 6 authors

No abstract is available for this record.

Matthias Hofmann, Karen Byskov Lindberg

Price-responsive demand and dynamic electricity price contracts can play a vital role in balancing renewable energy production and alleviating energy shortages such as those experienced in the European energy crisis. This study focuses on the implicit demand flexibility of residential consumers during extraordinarily high electricity prices in winter 2021/22 in Norway where most households have electric heating and spot price contracts. An econometric model is developed that compares the demand with pre-crisis levels, adjusts for factors influencing electricity consumption, such as outdoor temperature, and utilises a comprehensive dataset including hourly electricity demand data. The results reveal a quick response since the price signal was passed immediately to the customers and substantial energy savings of 11.4 % during winter. While the average household showed no significant short-term price response to daily or hourly price variations, several subgroups did. Particularly, households actively monitoring hourly prices via real-time information channels and those with automatic smart charging of electric cars showed higher load reductions in peak price hours and load shifting to low-price hours. Thus, the study concludes that households are able to respond to variable hourly electricity prices and suggests the promotion of spot price contracts to incentivise residential demand response.

He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi

No abstract is available for this record.

Juan Ignacio Ibañez, Alexander Freier

No abstract is available for this record.

Pavan Ramchandra Padghan, S. Arul Daniel, P. Raja

No abstract is available for this record.

Hass McCook

No abstract is available for this record.

Juan Ignacio Ibañez, Alexander Freier

For more than a decade, Bitcoin has gained as much adoption as it has received criticism. Fundamentally, Bitcoin is under fire for the high carbon footprint that results from the energy-intensive proof-of-work (PoW) consensus algorithm. There is a trend however for Bitcoin mining to adopt a trajectory toward achieving carbon-negative status, notably due to the adoption of methane-based mining and mining-based flexible load response (FLR) to complement variable renewable energy (VRE) generation. Miners and electricity sellers may increase their profitability not only by taking advantage of excess energy, but also by selling green tokens to buyers interested in greening their portfolios. Nevertheless, a proper ''green Bitcoin'' accounting system requires a standard framework for the accreditation of sustainable bitcoin holdings. The proper way to build such a framework remains contested. In this paper, we survey the different sustainable Bitcoin accounting systems. Analyzing the various alternatives, we suggest a path forward.

Rui Cheng

Traditional power systems always rely on the fossil-fuel based power, the power is determined and dispatched in the centralized decision-making process. However, recent years have seen the increasing proliferation of distributed energy resources (DERs), communication, computing, and information devices in power systems, becoming next-generation autonomous power systems. On the one hand, the high penetration of DERs can provide a variety of benefits to next-generation autonomous power systems. For example, DERs can respond rapidly to near-term generation or reliability-related requirements, further improving their ability to enhance power system reliability and reduce costs. On the other hand, DERs have led to significant uncertainty and intermittency in power system controls and operations, especially for power system economic dispatch and voltage regulation problems. It becomes increasingly urgent to explore how to utilize DERs to improve power system efficiency, reliability, and resilience while mitigating the negative impacts of DERs on power systems. Traditional power system decision-making is the centrally-managed formulation and solution of system-wide optimizations. It always entails large amounts of computation time and information coming from customers, leading to customer privacy and scalability problems. Particularly, the capacity of each DER is always small, but the number of DERs in power systems is massive. Given such distribution characteristics of DERs, it might be impractical to apply traditional power system decision-making to autonomous power systems. To figure out this dilemma caused by DERs, it calls for new and innovative decision-making strategies to adapt to new characteristics of autonomous power systems: (1) The capacity of DERs is usually small, but the number of DERs is very massive. In addition, DERs are distributed across power systems. Coordinating massive DERs at different network locations is a big scalability challenge. (2) The uncertain and intermittent nature of DERs makes the operations of autonomous power systems more complicated, leading to different environmental change rates. Different environmental change rates might require different decision-making strategies. Offline decision-making strategies are suitable for slow environmental change rates since there is enough time for the algorithm convergence. In contrast, fast environmental change rates require online decision-making strategies to adjust the decision variables in real time. (3) The increasing deployment of communication, computing, and information devices, along with increasing data, will bring many opportunities and changes to autonomous power system decision-making. It has attracted increasing attention worldwide utilizing these devices and data to make better decisions for autonomous power systems. To this end, this work aims to propose scalable offline and online decision-making for next-generation power systems, utilizing DERs to enhance power system efficiency, reliability, and resilience. In particular, we focus on developing and designing offline and online decision-making to resolve a series of power system problems, including energy management, voltage regulation, and power flow problems. Chapters 2-3 mainly focus on the scalable offline power system decision-making, and Chapters 4-5 mainly focus on the scalable online power system decision-making. Chapter 2 develops a consensus-based transactive energy design managed by an Independent Distribution System Operator (IDSO) for an unbalanced distribution network. The network is populated by welfare-maximizing customers with price-sensitive and fixed loads who make multiple successive power decisions during each Operating Period (OP). The IDSO and customers engage in a negotiation process in advance of each OP to determine retail prices for OP that align customer power decisions with network constraints in a manner that preserves customer privacy. Convergence and optimality properties of this proposed design are established for an analytically formulated illustration: an unbalanced radial distribution network, populated by households, that is electrically connected to a relatively large regional transmission organization/independent system operator-managed transmission network. Chapter 3 aims to mitigate the voltage deviations and reduce the cost of supplying reactive power in distribution networks by optimally setting the reactive power of DERs. It proposes two types of Volt/VAr Control (VVC) strategies, including the hierarchical and decentralized VVC, based on a novel fast alternating direction method of multipliers (ADMM). For the fast ADMM-based hierarchical VVC strategy, it requires a central agent to iteratively communicate with local bus agents, but both the central agent and local bus agents can update variables in a closed form without solving sub-optimization problems. In contrast, the fast ADMM-based decentralized VVC strategy only requires the minimal information exchange between neighboring buses, but solving sub-optimization problems is necessary for local bus agents. Chapter 4 proposes an automatic self-adaptive local voltage control (ASALVC) by locally controlling VAr outputs of DERs. In this ASALVC strategy, each bus agent can locally and dynamically adjust its voltage droop function in accordance with time-varying system changes. The voltage droop function is associated with the bus-specific time-varying slope and intercept, which can be locally updated, merely based on local voltage measurements, without requiring communications. Stability, convergence and optimality properties of this local voltage control are analytically established. Numerical test cases are performed to validate and demonstrate the effectiveness and superiority of ASALVC. Chapter 5 proposes an online feedback-based linearized power flow model for unbalanced distribution networks with both wye-connected and delta-connected loads. The online feedback-based linearized model is grounded on the first-order Taylor expansion of the branch flow model, and updates the model parameters via online feedback by leveraging the instantaneous measurements of voltages and load consumption. Exploiting the connection structure of unbalanced radial distribution networks, we also provide a unified matrix-vector compact form of the model. Chapter 6 proposes an online voltage control strategy of DERs, based on the projected Newton method (PNM), for unbalanced distribution networks. The optimal VVC problem is formulated as an optimization program with the goal of maintaining the voltage profile across the network by coordinating the VAr outputs of DERs. To overcome the slow convergence rate of conventional gradient-based methods, a PNM-based VVC solution algorithm is developed to solve this problem. It utilizes a non-diagonal symmetric positive definite matrix, developed from the Hessian matrix of the objective, to scale the gradient, and thus a fast convergence performance can be expected in this Newton-like algorithm. Moreover, taking advantage of the instantaneous feedback of voltage measurements, the online implementation of the PNM-based voltage control is further designed to deal with fast system variations.

Nishkar R. Naraindath, Ramesh C. Bansal, Raj Naidoo

No abstract is available for this record.

Mehran Hajiaghapour‐Moghimi, Ehsan Hajipour, Kamyar Azimi Hosseini, Mehdi Tavakkoli · 7 authors

In recent decades, there has been a growing global focus on solar power as a renewable energy source (RES) to supply local energy demands and reduce greenhouse gas emissions. Rooftop solar photovoltaic (PV) system provides a small-scale utilization of solar energy on the roofs of apartment buildings. Investment in this system and its profitability depends on several factors, including geographic conditions, electricity price, and local load profiles. However, in Finland, the maritime and continental climates and electrically heated residential buildings present unique challenges to the investment and utilization of rooftop PV systems. Common solutions to incentivize the investment of grid-connected PV in apartments are battery energy storage systems (BESSs), demand side management (DSM), and power-to-x (P2X) approaches. Nevertheless, the value of these solutions is limited in Finland due to the seasonal variation of solar PV generation and customers’ energy consumption. This paper presents a novel and practical control and hedging mechanism to encourage investments in rooftop solar PV-BESS systems by investing in cryptocurrency mining devices (CMDs) as dispatchable and flexible loads, which facilitate the use of excess renewable energy for producing cryptocurrency, such as bitcoin (BTC). This mechanism can optimally switch the output of excessive renewable energy between exporting to the main grid and mining cryptocurrency. The proposed mechanism is studied using a dataset obtained from a residential apartment building in Helsinki, Finland, and its effectiveness is demonstrated through several practical scenarios. The results of a case study employed in this work demonstrate that the proposed hedging mechanism can provide sufficient encouragement for investors to invest in a PV system, with a return on investment equal to 57.7%. This mechanism also reduces the annual cost of residential apartments by 68.1%.

Salma Elgabri, Mohamed Sameh Hassanein

The purpose of this article is to propose a framework for controlling light level consumption in smart city buildings and preventing power meter reading fraud. The framework utilizes IoT sensors, decentralized smart agents, and a smart contract on a backchain platform. This method enables the monitoring of light system consumption by focusing on communication integrity and identity for IoT sensors. The framework improves the work of light systems based on operational voltage, which varies with respect to light intensity values sensed via IoT sensors. The decentralized smart agents send consumption and real-time behavior data from the IoT sensors either through the default assigned agent or any available nearby agent. The smart contract securely transacts the consumption and behavior data of the smart agents using a Proof-of-Stake algorithm to support untampering of electric consumption. The results of the case study show that the proposed framework can improve light level consumption by 76%. The framework is evaluated through characteristics such as communication overhead, energy optimization, high availability, and real-time monitoring. The research results contribute to the development and improvement of energy conservation in smart cities. The proposed framework can also be applied to other applications in smart cities, such as facility management solutions. The novelty of the paper lies in the use of a blockchain-based framework to control light level consumption and prevent power meter readings fraud, providing a secure and tamper-proof way to collect and transmit consumption data, thus improving energy efficiency in smart city and ensuring accurate billing for consumers. Keywords: IoT Sensors, Blockchain, Energy Management, Smart Agents DOI： https://doi.org/10.35741/issn.0258-2724.58.4.46

Muhammad Hasan Danish Khan, Junaid Imtiaz, Muhammad Najam-ul-Islam

Energy markets are being transformed rapidly all over the world due to an increased integration of renewable energy sources. Blockchain technology is emerging as a prime contender, as it can provide a secure and efficient transactional platform for such markets. In a typical microgrid energy market, the consumers and prosumers belonging to the microgrid have the ability to trade energy in a peer-to-peer fashion. However, the existing energy markets suffer from multiple issues security and privacy issues. To handle the aforementioned issues, this research work proposes a blockchain based secure Decentralized Transaction System (DTS) for energy trading in microgrids. The proposed system comprises of a secure market model that facilitates energy trade between energy users. A simplistic energy exchange mechanism has been formulated that ensures data integrity and privacy of the participating energy users. A prosumer centric consensus mechanism has been employed to incentivize the prosumers and ensure the availability of energy in the microgrid at all times. An efficient and dynamic pricing mechanism has been used to reduce the supply and demand disparity. A comprehensive trust model based on commitments has been adopted for ensuring the reliability of the participating energy user. Additionally, a hardware based access control mechanism has been utilized to make the proposed DTS a physical and cyber secure system. Other than this, a framework of smart contracts has been deployed to provide a comprehensive solution that ensures privacy, security, anonymity, auditability and confidentiality of the generated energy information. To demonstrate its practicality, the system has been implemented on Ethereum platform. The proposed DTS is validated using realistic data with the Ethereum Virtual Machine (EVM) environment of Goerli Test Network.

Nic Carter, Shaun Connell, B. G. Jones, Dennis Porter · 5 authors

No abstract is available for this record.

Moinak Maiti, Darko Vuković, Michael Frömmel

No abstract is available for this record.

Naielly Lopes Marques, Leonardo Lima Gomes, Luiz Eduardo Teixeira Brandão

ABSTRACT This article proposes an investment model for a renewable energy generator that allows it to earn the right to issue Renewable Energy Certificates (RECs) and sell them through quarterly sales auctions promoted by the blockchain. Blockchain technology can further promote the RECs market, as it enables tokenization and distribution of certificates. We did not find articles in the literature that analyze the decision to invest in decentralized autonomous organizations (DAOs) that have rules for issuing and trading RECs specified in smart contracts, which are executed and validated by the blockchain. This article contributes to the literature on blockchain technology applications in the renewable energy market by proposing issuing and selling RECs tokens through a DAO. The relevance of this research is that it shows that simple real option pricing methods can help decision-makers evaluate investment opportunities under uncertainty and flexibility. The tokenization and distribution of RECs via blockchain can promote transaction agility, reduce or eliminate bureaucracy in the means of payment, and increase the security and transparency of transactions. We propose a model for issuing and selling RECs in smart contracts. We assume that the generator has the flexibility to invest now or in one year to enter the platform, considering the energy generated in one year by a single typical 4MW wind turbine. Our model assumes that the price of the REC token follows an inverse demand function subject to stochastic shocks. The results contribute to the understanding of the performance dynamics of digital products under uncertainty and flexibility and show that distributed ledger technology (DLT) may be a viable alternative for renewable energy incentives.

Liana Toderean, Viorica Rozina Chifu, Tudor Cioara, Ionuț Anghel · 5 authors

The household prosumers’ decentralized cooperation and aggregation in energy communities are essential to increase renewable energy penetration and to ensure a successful energy transition. Despite their potential, the prosumers are not motivated to participate in local energy value chains due to the lack of trust and decentralized cooperation models for meeting community welfare and sustainability preferences, most innovation efforts being focused on financial incentives that are anyway very low. In this paper, we propose a solution for prosumers’ decentralized coordination in self-sufficient energy communities using cooperative games on top of a blockchain overlay that considers their complementary energy features and flexibility mobilization. The proposed model for community-level local energy balance fits well in circumstances in which there is a strong motivation in the community to prioritize sustainability and environmental concerns and reduce dependence on external energy. We define a governance model to support the decentralized self-organization of prosumers in coalitions for balancing the renewable generation and demand while considering via tokenization factors that go beyond purely economic motivations and foster cooperation and collaboration among the prosumers in the community. Self-enforcing contracts are used to implement the cooperative game model enabling the decentralized management of prosumers’ coalitions for optimized tokens-based payoff distribution towards self-sufficiency. The evaluation results show our solution’s effectiveness in facilitating the prosumers cooperation in self-sufficient coalitions achieving a minimal difference between the energy consumption and production in the community of approximately 0.01%, with a low transactional time overhead.

Godwin C. Okwuibe, Thomas Brenner, Peter Tzscheutschler, Thomas Hamacher

Local energy markets (LEMs) provide opportunity to handle the challenges arising from the lower grid level while using the traditional top-down approach to manage distributed generated renewable energy resources. Blockchain based local energy markets (LEMs) have been introduced in recent years as a way to enable local consumers/prosumers to trade their energy locally in a distributed and highly secured manner in an LEM. However, there are still some challenges regarding the main factors that can drive local consumers/prosumers to participate in a blockchain based LEM, optimal community size and prosumer to consumer ratio for an efficient LEM. Also, there is still no information on how the quantifying factors for participation on a blockchain based LEM can affect the performance of an LEM. This paper presents a survey and simulation based analysis of quantifying factors for participation in a blockchain based LEM. The survey was distributed among local consumers/prosumers and a total of 261 responses were received from the responders. The results from the responders were analyzed using a Python code based statistical analysis model. The simulation based analysis was conducted using a community based LEM model and evaluated using data received from a combination of German household profiles and standard load profiles. The survey results showed that the major drive for local consumers/prosumers to participate on blockchain based LEM is their willingness to support renewable energy integration, transparency and trust offered by a blockchain network. On the other hand, the simulation based analysis showed that small and medium communities with prosumers to consumer ratios between 0.3 to 0.5 create more economic and technical benefits for local consumers/prosumers compared to large communities. The community based simulation results were modelled together with the survey results to determine how the individual quantifying factors for participating in a blockchain based LEM can affect the performance of an LEM.