Marthe Fogstad Dynge, Ugur Halden, Gro Klæboe, Ümit Cali
Support schemes like the Feed-in-Tariff (FiT) have for many years been an important driver for the deployment of distributed energy resources, and the transition from consumerism to prosumerism. This democratization and decarbonization of the energy system has led to both challenges and opportunities for the system operators, paving the way for emerging concepts like local energy markets. The FiT approach has often been assumed as the lower economic bound for a prosumer's willingness to participate in such markets but is now being phased out in several countries. In this paper, a new pricing mechanism based on the Levelized Cost of Electricity is proposed, with the intention of securing profitability for the prosumers, as well as creating a transparent and fair price for all market participants. The mechanism is designed to function on a Distributed Ledger Technology-based platform and is further set up from a holistic perspective, defining the market framework as interactions in a Cyber-Physical-Social-System. Schemes based on both fixed and variable contracts with the wholesale supplier are analyzed and compared with both the conventional FiT and to its proposed replacement options. The results show a cost reduction for the consumers and a slight loss in revenue for the prosumers compared to the FiT scheme. Comparing it to the actual suggested replacements to the FiT, however, it is clear that the pricing mechanism proposed in this study provides a substantial increase of benefits for both prosumers and consumers.
The energy transition to renewable energy in a democratic way is directly connected to the development of energy communities and community microgrids. Los Molinos del Rio Aguas (LMRA), an ecological community in the south of Spain, offers a promising case study for an off-grid community-owned microgrid. In this paper, the interconnection of autonomous solar home systems is proposed with the addition of community assets in order to create an off-grid community microgrid that is financially beneficial for the community. Based on this scenario, a Local Energy Market (LEM) based on Distributed Ledger (DL) technologies is implemented in order to foster the energy exchange and contribute to the social welfare of the community. The results provide a win-win scenario for the community and provides an example of an off-grid community microgrid in combination with a LEM that takes into consideration the social aspect of the community.
Energy Internet (EI) is developing and booming rapidly with the increase of distributed energy resources, which is beneficial to address the severe condition of industrial energy. However, there are inevitable credit crises and utility optimization challenges in EI that need to be settled. In this article, we propose a blockchain-assisted software defined energy Internet (BSDEI), where a distributed energy market smart contract is designed to ensure transactions executed reliably and participants’ accounts dealt accurately. In order to jointly optimize the utilities of operators, retailers, and industrial prosumers in BSDEI, we formulate the whole trading process as a three-stage Stackelberg game, with the proof of existence and uniqueness for the Stackelberg equilibrium. Then, we design a hierarchical distributed policy gradient algorithm to solve the Stackelberg game under incomplete information. We implement a blockchain-based industrial energy trading system using a middleware platform. The smart contract is deployed on the consortium blockchain, providing website interfaces for participants to operate. Furthermore, we conduct experiments for analyzing economic benefits. Our system prototype demonstrates the feasibility of BSDEI and the algorithm exceeds about 18% in total mean reward than comparing algorithms.
Abstract In the time of Industry 4.0, with the requirements for reducing CO2 in the atmosphere and realizing a circular economy in all aspects of life, the implementation of electric vehicles and IoT control systems was observed. The advantages and positive effects of implementing electric vehicles in the mining industry are discussed in the article. To achieve a circular economy and meet the criteria for sustainable development, a conceptual model is proposed for tracking the quantities of useful raw materials used in power batteries, as one of the main components of electric vehicles. To implement reliable and unambiguous communication among the various participants, blockchain technology is used.
Liaqat Ali, M. Imran Azim, Jan Peters, Vivek Bhandari · 8 authors
This paper presents a collated case study on local energy market (LEM) in Australia, in which energy users take part frequently in peer-to-peer (P2P) energy trading among themselves considering the agile presence of energy retailers and distribution utilities. To do so, first, an overview is provided in regard to LEM architecture, trading model with energy retailers, and the blockchain structure. Then, a new P2P trading mechanism is proposed in the LEM that enables both energy users, i.e., sellers and buyers, to reap financial benefits compared to the existing business-as-usual (BAU) model — where local power is exported and imported via feed-in-tariff (FiT) and time-of-use (ToU) rates. The proposed LEM framework also exploits residential battery energy storage systems (RBESSs); and the community battery energy storage systems (CBESSs) to balance local supply and demand appropriately and contributes towards lowering exports/imports from/to power grids by means of bilateral P2P transactions while the inclusion of responsible energy retailers are assured. Moreover, the margins of both energy retailers and distribution utilities are kept unchanged or increased to some extent by the proposed trading model to incorporate them in the LEM framework effectively. Finally, diverse case studies are provided to validate the proposed LEM mechanism with various studied models and demonstrate the superior performance in contrast with the present-day BAU model.
Andrei Ionita, René Chester Goduscheit, Hessellund Lauritsen, Per, Wolfgang Prinz · 6 authors
The wind energy sector is undergoing digitalization processes that span multi-tier supply chains of turbine components and wind farm maintenance, amongst others. In an industrial use case that includes Siemens Gamesa Renewable Energy, Vestas and APQP4Wind, the processes of producing, fastening, and servicing bolts in turbines are mapped to a digital model. The model follows the lifetime of turbine bolts from the manufacturing phase, to fastening in turbines and maintenance, until their replacement and recycling. The development of the digital model is iteratively addressed in a design science research approach, as the authors actively contribute to the project. Distributed ledgers (DLs) support the notary documentation of the bolts and turbines, from their registration phase to the assembly-, technical service verification- and recycling phases. The immutable and decentralized nature of DLs secures the data against tampering and prevents any changes taken unilaterally by engaging the service stakeholders and component providers in a blockchain consortium.
Zahra Foroozandeh, Sérgio Ramos, João Soares, Zita Vale
In this paper, a collective residential building is considered in which the following points are taken into consideration: (i) a flexibility value of Contract Power (CP) is considered for each consumer; (ii) it is assumed a single CP for the entire building; (iii) an energy resource manager entity is considered to manage the energy resources in the residential building, such as Electric Vehicles (EVs), Photovoltaic (PV) generation system, and the Battery Energy Storage System (BESS). Taking into consideration the previous assumptions, the major goal of this work is to minimize the electricity consumption costs of the residential building by using a Multi-Objective Mixed-Binary Linear Programming (MOMBLP) formulation. The objective function of the MOMBLP model minimizes the electricity cost consumption of each apartment. Then, a Goal Programming (GP) strategy is applied to find the most appropriate solutions for the proposed MOMBLP model. Finally, the performance of the suggested model is evaluated by comparing the obtained results from a Single-Objective Mixed-Binary Linear Programming (SOMBLP) approach in which the whole building consumption cost is minimized. The results show that using the GP strategy a reduction of 7.5% in the total annual energy consumption is verified in comparison with SOMBLP. Moreover, the GP approach leads to fair benefit among building consumers, by finding a solution with less distance from the desired level.
A Smart Community (SC) is an essential part of the Internet of Energy (IoE), which helps to integrate Electric Vehicles (EVs) and distributed renewable energy sources in a smart grid. As a result of the potential privacy and security challenges in the distributed energy system, it is becoming a great problem to optimally schedule EVs’ charging with different energy consumption patterns and perform reliable energy trading in the SC. In this paper, a blockchain‐based privacy‐preserving energy trading system for 5G‐deployed SC is proposed. The proposed system is divided into two components: EVs and residential prosumers. In this system, a reputation‐based distributed matching algorithm for EVs and a Reward‐based Starvation Free Energy Allocation Policy (RSFEAP) for residential homes are presented. A short‐term load forecasting model for EVs’ charging using multiple linear regression is proposed to plan and manage the intermittent charging behavior of EVs. In the proposed system, identity‐based encryption and homomorphic encryption techniques are integrated to protect the privacy of transactions and users, respectively. The performance of the proposed system for EVs’ component is evaluated using convergence duration, forecasting accuracy, and executional and transactional costs as performance metrics. For the residential prosumers’ component, the performance is evaluated using reward index, type of transactions, energy contributed, average convergence time, and the number of iterations as performance metrics. The simulation results for EVs’ charging forecasting gives an accuracy of 99.25%. For the EVs matching algorithm, the proposed privacy‐preserving algorithm converges faster than the bichromatic mutual nearest neighbor algorithm. For RSFEAP, the number of iterations for 50 prosumers is 8, which is smaller than the benchmark. Its convergence duration is also 10 times less than the benchmark scheme. Moreover, security and privacy analyses are presented. Finally, we carry out security vulnerability analysis of smart contracts to ensure that the proposed smart contracts are secure and bug‐free against the common vulnerabilities’ attacks. The results show that the smart contracts are secure against both internal and external attacks.
In this study, artificial intelligence, the Internet of things, and blockchain technology were combined to develop a vehicle-to-everything blockchain power trading and energy management platform with the objective of enabling multi-level power transactions for electric vehicle charging stations in or between commercial buildings. The proposed platform considers green power transactions across microgrids, bidirectional power and green power charging and discharging transactions in microgrids, demand response bidding, and vehicle-to-vehicle emergency rescue charging. This innovative architecture operates smart contracts and distributed ledgers independently; uses smart contracts to handle bidding, matching, and settlement of the power trading platform; and simultaneously employs the cloud and local distributed ledger nodes to chain the detailed real-time transaction information and power data on the ledger. In this manner, the security and fairness of data can be ensured; furthermore, a large amount of chaining information can be processed, and the chaining latency can be shortened. In addition, the communication protocols are integrated through the artificial intelligence of things. An energy management system (EMS) is proposed, which can perform optimal charging and discharging scheduling according to the power transaction matching results and then control charging piles and energy storage system devices. It can reduce the operating cost of microgrids in commercial buildings, increase the efficiency of green power utilization, and reduce power loss. In this system, power transactions are automatically and simultaneously executed in the EMS to achieve real-time supply and demand balance of regional microgrids.
A smart electric vehicle (EV) charging station energy management system (CSMS) based on blockchain technology, which aims to protect privacy of EV users, ensure fairness of power transactions, and meet charging demands for large numbers of EVs, is proposed in this study. EV charging pile is designed as a local blockchain distributed ledger node, which operates synchronously with blockchain system and blockchain distributed ledger in cloud server. This paper integrates CSMS through smart contracts, providing EV users that ability to conduct power transactions and perform optimal charging and discharging control in real-time. The distributed ledger is in charge of recording all the EV charging and discharging data to maintain fairness of power transactions, protects data from being maliciously tampered, and enables the EV user to monitor status of the EV participating in power transactions and dispatching. The intelligent CSMS consists of an artificial intelligence (AI) module, centralized optimal scheduling module, and decentralized optimal control module. The AI module is responsible for forecasting renewable energy generation and load consumption. There is a two-layer architecture consisting of centralized and decentralized optimal control modules; the upper layer performs optimal charging and discharging scheduling of the entire EV charging station at time 15-min time segments, the bottom layer performs distributed optimal scheduling control in each EV charging pile at 5 min time interval. Proposed system in this paper can deal with feeder congestion and real-time power supply and grid demand imbalance, which are caused by high numbers of EVs.
Electric Vehicles (EVs) have emerged as one of the most promising solutions for reducing carbon emissions in smart cities. However, due to the limited battery life of EVs and the scarcity of charging stations, EV drivers are not willing to travel long distances. Thus, blockchain-enabled energy trading (BET) has lately been used to securely share energy among EVs via wireless power transfer (WPT) technology. Blockchain is used to ensure the security and privacy of transactions between untrustworthy EVs in the WPT process. Nevertheless, previous works on BET have relied on existing consensus mechanisms built on the requirements of the cryptocurrency systems. These consensus mechanisms have faced significant challenges in maintaining high reliability, throughput, low latency, and network scalability in V2V energy trading that requires real-time services. To address these issues, we propose a new consensus mechanism that leverages the benefits of Practical Byzantine Fault Tolerance (PBFT) and Proof of Reputation (PoR) called PBFT-based PoR (PPoR). The energy trading process runs in a clustered vehicular network, where validator selection, block generation, and consensus processes are performed in each cluster. We adopt an incentive mechanism based on a Stackelberg game model to optimize the utility of sellers, buyers, and validator nodes, which motivates honest and cooperative nodes. The simulation results show that the proposed scheme reduces buyers’ costs by 21.1% while increasing the utility of sellers by 18%. Moreover, compared to benchmarks, the proposed scheme reduces the transaction processing delay and increases the throughput by more than 47.1% and 15.7%, respectively.
To further implement decentralized renewable energy resources, blockchain based peer-to-peer (P2P) energy trading is gaining attention and its architecture has been proposed with virtual demonstrations. In this paper, to further socially implement this concept, a blockchain based peer to peer energy trading system which could coordinate with energy control hardware was constructed, and a demonstration experiment was conducted. Previous work focused on virtually matching energy supply and demand via blockchain P2P energy markets, and our work pushes this forward by demonstrating the possibility of actual energy flow control. In this demonstration, Plug-in Hybrid Electrical Vehicles(PHEVs) and Home Energy Management Systems(HEMS) actually used in daily life were controlled in coordination with the blockchain system. In construction, the need of a multi-tagged continuous market was found and proposed. In the demonstration experiment, the proposed blockchain market and hardware control interface was proven capable of securing and stably transmitting energy within the P2P energy system. Also, by the implementation of multi-tagged energy markets, the number of transactions required to secure the required amount of electricity was reduced.
Leonardo Weber Stringini, Héricles Eduardo Oliveira Farias, Camilo Alberto Sepúlveda Rangel, Luciane Neves Canha · 6 authors
This paper presents a methodology for optimal energy management of battery energy storage systems for aggregators use in distribution systems considering photovoltaic generation, demand contracts, and lifetime degradation. The methodology sets the optimum operation of the battery, define a trade-off between profit/lifetime of the battery dispatch and reduce the aggregator tariff bill. The dispatch optimization is carried out on a 48h forecasting model, where the best strategy is the one that guarantees a good operation for the day n+1 and day n+2. A nonlinear optimization approach sets battery dispatch, under operational constraints given by the Distribution System Operator contract and the battery state of charge constraint. Three types of battery chemistry are used, the lead acid, lithium ion and vanadium redox. Also, for each battery type the best methodology strategy is defined. Regarding the methodology, a neural network is used for forecasting of demand values, PV generation and tariff prices. Battery degradation cost is controlled in daily operation based on cycles and cost. Moreover, for total lifetime estimation, the Rainflow Counting technique is used through the depth of discharge. The results define an operation for the battery that allows economic profit, without compromising the lifetime.
Profound changes driven by decarbonization, decentralization, and digitalization are disrupting the energy industry, bringing new challenges to its key stakeholders. In the attempt to address the climate change issue, increasing penetration of renewables and mobility electrification augment the complexity of the electric grid, thus calling for new management approaches to govern energy exchanges while ensuring reliable and secure operations. The emerging blockchain technology is regarded as one of the most promising solutions to respond to the matter in a decentralized, efficient, fast, and secure way. In this work, we propose an Ethereum-based charging management framework for electric vehicles (EVs), tightly interlinked with physical and software infrastructure and implemented in a real-world demonstration site. With a specifically designed solidity-based smart contract governing the charging process, the proposed framework enables secure and reliable accounting of energy exchanges in a network of trustless peers, thus facilitating the EVs’ deployment and encouraging the adoption of blockchain technology for everyday tasks such as EV charging through private and semi-private charging infrastructure. The results of a multi-actor implementation case study in Switzerland demonstrate the feasibility of the proposed blockchain framework and highlight its potential to reduce costs in a typical EV charging business model. Moreover, the study shows that the suggested framework can speed up the charging and billing processes for EV users, simplify the access to energy markets for charging station owners, and facilitate the interaction between the two through specifically designed mobile and web applications. The implementation presented in this paper can be used as a guideline for future blockchain applications for EV charging and other smart grid projects.
The era of Electric Vehicles (EVs) has influenced the very make and manufacture of vehicles resulting in low pollution and advanced battery life. On the other hand, the internet of things has also expanded allowing a number of devices to stay connected using the internet. Massive drawbacks faced by EVs today are the limitation in battery swapping and charging stations and limitation in the range of batteries used. This proposed paper aims to efficiently manage the best battery system apart from building the essential infrastructure. In some cases battery swapping option is also provided through other EV drivers or at registered stations. Hence a complete database of the EV network is required so that it is possible to swap and charge batteries successfully. An EV management using two blockchains as a data layer and network of the application is implemented in this work. The first step involves the development of a blockchain framework using Ethereum and the next step entails a direct acyclic graph. When integrated, these two methodologies prove to be an efficient platform that offers a viable solution for battery management in Electric Vehicles.
Mishaal Ahmed, Muhammad Shoaib Farooq, Muhammad Ibrar–ul–Haque, Manzar Ahmed · 6 authors
The massive increase in environmental pollution due to industrial growth in recent years has made researchers study the concept of clean energy and find cheap and green alternative energy resources. Green Energy means renewable and zeroes hazardous gas emissions that pollute the atmosphere to produce energy such as CO2. The main sources of Green Energy are Wind, Hydro and Solar. The integration of these clean energy resources with the emerging Microgrid technology made researchers expect that it will reduce the main grid's burden and help reduce carbon emissions. However, their integration makes the energy control system more complex. To provide clean and pollution-free energy to end users/buyers, it must be free and saved from cyber theft. Therefore, this paper proposed a Blockchain Technique to resolve above discussed issues. The green energy model used for analysis in our system fulfills the green energy rules.
Mikhak Samadi, Henry Schriemer, Sushmita Ruj, Melike Erol‐Kantarci
The high impact of demand reduction on the energy grid management and the importance of reducing loss of distributed energy resources (DERs), in addition to the necessity of a secure distributed data storing system motivate us to propose an energy blockchain solution. This paper presents a demand response (DR) solution utilizing energy blockchain to reduce demand, save the extra DERs, and efficiently incorporate customers block mining ability. In this work, a real dataset of customer demand profiles and PV generation in the Ottawa region is used to deploy a DR Stackelberg game between a control agent (CA) and local customers to negotiate demand reduction by integrating the block mining method as DERs saving. This article presents a novel and well-suited consensus algorithm, Proof of Energy Saving (PoES), that is used to incentivize the customers to reduce their demand, discharge their electric vehicle (EV) and maximize their chance for block mining to earn monetary rewards and DER savings. This results in lower peak demand, customer bill reduction, and transforms energy savings into monetary resources. Furthermore, the results show that our proposed consensus algorithm is robust and secure against malicious actions of users.