Chenggang Mu, Tao Ding, Mohammad Shahidehpour, Shiqi Liu · 8 authors
Household-level distributed energy sources, such as rooftop photovoltaic, microturbines, and energy storage, become important behind-the-meter (BTM) resources. BTM resources can meet all or part of users’ demands. Establishing a peer-to-peer (P2P) energy trading network among these users will further promote the utilization of BTM resources. However, such a proposal faces the problem that cyber trading and physical dispatching are difficult to coordinate. Therefore, this paper proposes the architecture of the behind-the-meter peer-to-peer (BTM-P2P) energy trading system, including the cyber layer and physical layer. To ensure that users strictly execute the cyber trading results in the physical layer, a trading mechanism considering credit is designed, and the user’s credit has an impact on the bidding priority, which in turn urges the user to strictly execute in subsequent tradings. Then, a light blockchain suitable for energy trading is developed, ensuring that both the trading results and the actual dispatching results are not tampered with. Database technology is inserted in the light blockchain to improve efficiency. Finally, a BTM-P2P cyber-physical testbed coupling physical dispatching with cyber trading is built, providing technical support for the implementation of BTM-P2P.
The ability for residents to actively trade and generate energy on the demand side is made possible by distributed renewable energy and two-way communication infrastructures. Information exchange is compromised by eavesdropping, lack of dependability, and loss of privacy under the conventional centralized power management model. This article suggests a distributed energy trading system for residential communities that is efficient and protects privacy, powered by a novel smart contract. For the demand side to engage in peer-to-peer energy trading on the real-time market, an effective smart-contract-based bidding mechanism is presented. To ensure that the information exchange is safe, seamless, and traceable using a decentralized system, the full electricity transaction is performed in the smart contract. Results from simulation studies show that the proposed system is both stable and scalable. It could also help to guarantee the security of energy transactions and reduce customers’ costs. As a result, our proposed smart-contract-based trading system is applied to microgrids formed by distributed renewable energy sources, which is proven to reduce the load consumption of residents among communities as well as obtain more significant economic benefits compared to the centralized trading mechanism.
Anu G Kumar, M R Sindhu, Vivek Mohan, Rekha Viswanathan · 5 authors
Rooftop solar PV in India has seen good progress in the Commercial and industrial sectors, but the progress in the domestic sector is relatively slow due to the high initial installation cost. Thus, there arises the need for good market models for Rooftop Solar (RTS) implementation. This paper conducts a comparative study of workable RTS market models by employing the discounted cash flow method, as per the recent regulatory guidelines. Market models are formulated and tested for a typical residential high-rise apartment complex in India comprising 15 storied buildings with a combined maximum demand of 180kVA. The results suggest that the centralized community RTS model of 80kWp capacity with upfront financing is suitable when compared to the decentralized individual model, as it has the lowest levelized cost of 3.39 ₹/kWh and a payback period of 5.5 years. With the federal subsidy, the prosumer levelized cost reduces to 2.06 ₹/kWh with a payback period of 3.3 years. Thus grid parity is achieved for all tariff tier rates. With adaptive staggering strategy, this scheme is validated to be more attractive for the urban residential microgrids, as the solar installation of 80kWp and its cost can be staggered and even reduced over the planning period. Hence capital installation and operation costs can be distributed over the stipulated time interval. The study result gives RTS stakeholders insight into selecting the most cost-effective market model to suit their requirements. Financial analysis of the proposed models provides input to the customers, developers, and policymakers to assess the financial merit of adopting the suitable business model for RTS development. The proposed analysis can be replicated for high-rise residential buildings, especially in cities with high electricity tariffs. With time, a decrease in solar PV installation price and an increase in grid price are expected; hence, the overall investment cost gets reduced and staggered.
Xin Zhou, Bin Wang, Qinglai Guo, Hongbin Sun · 6 authors
The increasing integration of distributed energy resources has led to a network-constrained peer-to-peer (NCP2P) energy trading. Compared with conventional peer-to-peer trading without network constraints, NCP2P trading encounters challenges in protecting bidirectional privacy of both the prosumers and the grid operator when implementing market clearing and dispute resolution mechanisms. To deal with them, we apply a novel cryptographic technology called secure multiparty computation (SMPC). Firstly, a secure quadratic programming (QP) algorithm based on SMPC is designed to compute the NCP2P market clearing results with bidirectional privacy. Secondly, we propose dispute resolution mechanisms that employ blockchain to verify the correctness of claimed trading results of the two trading prosumers, and reconstruct the true trading bill based on Karush-Kuhn-Tucker conditions using SMPC when both prosumers claim wrong trading results. Finally, we design a bidirectional privacy-preserving NCP2P energy trading framework based on SMPC and blockchain. The case analysis shows that our proposed trading framework using the secure QP algorithm achieves optimal trading results, bidirectional privacy and low communication requirements for prosumers. The accuracy of the proposed dispute resolution mechanisms is also proven.
Piyush Kumar Yadav, Rajnish Bhasker, Albert Alexander Stonier, Geno Peter · 6 authors
Abstract Many progressed information scientific strategies, particularly Artificial Intelligence (AI) and profound learning methods, have been proposed and tracked down wide applications in our general public. This proposition creates information driven arrangements by utilizing the most recent profound learning and AI innovation, including outfit learning, meta‐learning and move learning, for energy the executives framework issues. Genuine world datasets are tried on proposed models contrasted and best in class plans, which exhibit the predominant presentation of the proposed model. In this proposition, the engineering of the Smart Grid testbed is additionally planned and created by using ML calculations and true remote correspondence frameworks to such an extent that constant plan necessities of Smart Grid testbed is met by this reconfigurable system with stacking of full convention in medium access control (MAC) and physical layers (PHY). The proposed engineering has the reconfiguration property in view of the organization of remote correspondence and trend setting innovations of Information and communication technologies (ICT) which incorporates Artificial Intelligence (AI) calculation. The fundamental plan objectives of the Smart Grid testbed is to make it simple to construct, reconfigure and scale to address the framework level prerequisites and to address the ongoing necessities.
Digitalization will play a vital role in the achievement of successful transitions towards more flexible, reliable and sustainable energy systems. The progressive availability of data from meters and sensors deployed across end-users and energy supply-chains constitute a first step towards this direction. Leveraging on such cross-sectorial trend, business developers find in decentralized ledger technologies (DLTs) – such as the blockchain – opportunities for value creation across a broad range of participants in energy systems. Peer-to-peer energy trading platforms interconnect legacy and novel participants leveraging renewable and storage capacity (small and utility-scale) with grid operators and within local microgrids or markets. In this way, near real time (bi-directional) exchanges can be secured and validated via tokenization and smart contracting. The proposed configurations enable governance arrangements between legacy and novel participants at the platform and sectorial level. This paper focuses on investigating the decentralized governance characteristics proposed by peer-to-peer energy trading platforms and briefly discusses their implications on legacy systems from a broad ‘relational’ (i.e. actor network, sociotechnical transitions) and ‘normative’ (i.e. energy justice) set of theories. The paper draws upon prior surveys and publicly available whitepapers from business initiatives (start-ups). For the purposes of this study, whitepapers constitute official written texts and potential sources of information for the study of emergent ways of governance and collective action leveraging this technology. Results from ground theory method (qualitative) leveraging an inductive content analysis approach, built four (4) main categories that explain: (1) the digital features of these platforms, (2) the participants and incentives involved (3) the purposes and benefits of the solutions and, (4) the governance dynamics arising from trading tokenized energy via smart contracting. Results reveal complex multi-level socio-technical interrelations at different layers and points towards opportunities for private and community-based solutions, end-user empowerment, democratic energy systems and polycentric governance while considering fractal planning in policy design.
The concern for privacy and scalability has motivated a paradigm shift to decentralized energy management methods in microgrids. The absence of a central authority brings significant challenges to promote trusted collaboration and avoid collusion. To address these issues, this paper proposes a blockchain-empowered microgrid energy management framework, which adopts a novel consensus-based algorithm with a collusion prevention mechanism. Aiming at social welfare maximization, the energy management problem is formulated into a convex and decomposable form, which can be solved in a decentralized manner. To prevent the collusion between malicious agents, we propose a random information transmission mechanism empowered by the blockchain smart contract to replace the time-invariant communication topology. The consensus-based algorithm is extended to obtain the optimal solution of the energy management problem on the random and time-varying communication topology. We theoretically proved that the proposed algorithm converges to the global optimal solution with a probability of 1, without violating the physical constraints of individual agents. The effectiveness of the proposed method was validated by multiple experiments, both within the simulation environment and on a hardware system.
Demand flexibility plays a pivotal role in modern power systems with high penetration of variable energy resources. In recent years, one of the fastest-growing flexible energy demands has been proof-of-work-based cryptocurrency mining facilities. Due to their competitive ramping capabilities and demonstrated flexibility, such fast-responding loads are capable of participating in frequency regulation services for the grid while simultaneously increasing their own operational revenue. In this paper, we investigate the physical and economic viability of employing cryptocurrency mining facilities to provide frequency regulation in large power systems. We quantify mining facilities' operational profit, and propose a decision-making framework to explore their optimal participation strategy and account for the most influential factors. We employ real-world ERCOT ancillary services data in our case study to investigate the conditions under which provision of frequency regulation in the Texas grid is profitable. We also perform transient level simulations using a synthetic Texas grid to demonstrate the competitiveness of mining facilities at frequency regulation provision.
- With the ever-increasing integration of distributed generation in the distribution system and the deregulation of power industry, some new-type entities emerge and could play both roles as producers and consumers of electricity, i.e. the so-called prosumers. The occurrence of prosumers promotes local electricity energy utilization and enhances the accommodation capability for small-capacity intermittent renewable energy-based generation units through peer-to-peer (P2P) transactions. In this context, an event driven P2P electric energy trading mechanism based on the blockchain platform is proposed. Firstly, an event driven electricity trading mechanism is established based on the smart contract in blockchain technology. Secondly, the market clearing model is established, and a distributed algorithm is used for market clearing and settlement. Finally, an energy trading platform is built through the Ganache client in the Ethereum network. Case studies and numerical analysis demonstrate that the proposed trading mechanism is feasible and effective.
Smart grid is considered as next generation power system which performs automated control and monitoring operations to make it self-resilience. Advanced Metering Infrastructure is an essential part of smart grid which enables two-way communication thereby providing real-time communication link between consumer and grid operators. Emergence of Distributed Energy Resources (DERs) at end user make AMI's operation more challenging. Smart Meters (SMs) are key components in AMI that sends Power Consumption Data (PCD) of home appliances to Distributed System Operator (DSO). PCD received at DSO can be used for real time pricing applications, real time energy consumption, automatic diagnostic, daily energy metering and tasks such as billing, monitoring, planning and predicting of energy usage. In the context of selling of excess energy generated at DER's to the grid, SMs participates in Demand Response (DR) applications to perform energy trading. Revealing PCD of a home leads to privacy breach, hence it is necessary to achieve secure communication between SM and DSO. At the same time, it is essential to make energy trading transparent. To address this issue, this paper proposes a cloud based private blockchain framework to accomplish secure communication between SM and DSO without compromising privacy. Furthermore, trust between SM and DSO is achieved through smart contracts. Performance evaluation of the proposed blockchain shows its applicability to the said environment.
Decentralized energy management can preserve the privacy of individual energy systems while mitigating computational and communication burdens. However, most decentralized energy management methods are partially decentralized and cannot ensure information exchange security. Therefore, this paper provides a secure fully decentralized energy management by using blockchain. First, a fully decentralized energy management framework using the optimality condition decomposition (OCD) is provided, in which individual energy system operators only exchange the boundary information with their peers rather than submitting proprietary information to a centralized system operator. Then, an asynchronous mechanism is proposed for updating the information exchange in OCD, enabling the proposed decentralized management to work under potential communication latency or interruption. Furthermore, the blockchain-based framework with state machine replication (SMR) based consensus algorithm is provided to safeguard the information exchange among individual energy systems in a secure and tamper-proof manner. The proposed decentralized energy management is tested on a multi-energy system with seven subsystems and a real-world multi-energy system in North China. The numerical results demonstrate the effectiveness of the proposed method in privacy protection and data security enhancement. The proposed method can prevent the cost increase caused by cheating activities, which in some subsystems can reach 17.6%. Additionally, the proposed fully decentralized method outperforms the partially decentralized method by 37.7% in reducing computation time. Also demonstrated are the computational precision, scalability and adaptability of the proposed method.1
Vikas Goel, Ashutosh Sharma, Raju Ranjan, Amit Kumar Sharma
As a new form of technology, blockchain has much to offer. The technology has a wide range of potential uses and advancements, depending on the field of application. However, further study is required to realise the potential of advanced technologies like Blockchain and smart contracts. There is a lot of potential for investigation because the technology is so new. This research looked at the origins of the Blockchain and analysed several different blockchain solutions. Ethereum was discovered to be the most often used platform for constructing distributed apps after being compared to other platforms. Therefore, a distributed smart energy microgrid application will be built on the Ethereum platform. There is a coin, or token, exclusive to each blockchain platform. Bitcoin's relationship to other cryptocurrencies was measured using the Karl Pearson correlation coefficient. The research concludes that ether's price is most sensitive to changes in the price of bitcoin. On a preferred Ethereum network, a distributed application for managing smart microgrids has been built. The smart contract constitutes the heart of this programme. As a result, we also take care of the smart contract's layout, coding, and optimization. In comparison to the original, less GAS is consumed by this smart contract. The entire distributed app has been built and thoroughly tested. Smart Energy Microgrid Distributed Application framework results demonstrate that the application functioned as expected.
Blockchain technology creates a distributed ledger of transactions through interconnected blocks which are decentralized, transparent, immutable, and automated. The use of blockchain solutions and applications is growing rapidly which include finance, supply chain management, digital identity, energy, healthcare, and real estate. Due to the rapid economic recovery, global weather variations, maintenance delays caused by the pandemic, and earlier decisions by oil and gas companies to cut investments, energy costs have increased since 2021. Through limiting consumer prices and compensating energy providers for the shortfall, governments are aiming to lessen the impact of increase energy prices on citizens and businesses. The utilization of energy using Blockchain technology, where peer-topeer (P2P) energy trading on local and global energy markets could be enabled, can be an enabler to resolve energy shortage and increasing prices. Currently, National Information Security Standards and International Information Security Standards lack a framework to manage and govern information security controls for P2P energy trading using Blockchain technology. This paper proposes information security controls to complement existing Standards that will enable proper governance of P2P energy trading and discusses associated risks.
Seyed Amir Alavi, Mehrnaz Javadipour, Ardavan Rahimian, Kamyar Mehran
Abstract The privacy of electricity consumers has become one of the most critical subjects in designing smart meters and their proliferation. In this work, a multilayer architecture has been proposed for anonymous data collection from smart meters, which provides: (1) The anonymity of information for third‐party data consumers; (2) Secure communication to utility provider network for billing purposes; (3) Online control of data sharing for end‐users; (4) Low communication costs based on available Internet of things (IoT) communication protocols. The core elements of this architecture are, first, the digital twin equivalent of the cyber‐physical system and, second, the Tangle distributed ledger network with IOTA cryptocurrency. In this architecture, digital twin models are updated in real‐time by information received from trusted nodes of the Tangle distributed network anonymously. A small‐scale laboratory prototype based on this architecture has been developed using the dSPACE SCALEXIO real‐time simulator and open‐source software tools to prove the feasibility of the proposed solution. The numerical results confirm that after a few seconds of anomaly detection, the microgrid was fully stabilized around its operating point with less than 5% deviation during the transition time.
P Nirmal Kumar, Blessy Sharon Gem Johnson Selvakumar, R Viji, K. Rajkumar · 6 authors
Among the most effective methods Exchanging Energy Management Smart Grid (SG) enhances user involvement in energy production and it creates decentralized power sector systems with peer-to-peer technique (P2P). In Peer to peer, prosumers produce electricity on-site using Sustainable Energy sources. Next it is traded with customers in the surrounding area. Peer-to-peer makes it easier for people to interchange energy in the Transactive Energy Management system's regional micro-energy markets. This study suggests a block chain-based Decentralized and apparent Peer-to-peer Energy Trading (DA-P2PET) to solve the identified issues. Its target is to decrease grid energy generation and raising the gain for both consumer and prosumer by flexible price system. The DA-P2PET system conducts peer-to-peer energy trading using Smart Contracts built on the Ethereum block chain and the Interplanetary File System (IP. In the suggested DA-P2PET system, the Ethereum SCs are created to carry out P2P in real time. In comparison to existing methods, the DA-P2PET scheme is rated based on numerous criteria including profit creation, data transfer speed, networking access
Younes Zahraoui, Tarmo Korõtko, Argo Rosin, Hannes Agabus
Electricity generation using distributed renewable energy systems is becoming increasingly common due to the significant increase in energy demand and the high operation of conventional power systems with fossil fuels. The introduction of distributed renewable energy systems in the electric grid is crucial for delivering future zero-emissions energy systems and is cost-effective for promoting and facilitating large-scale generation for prosumers. However, these deployments are forcing changes in traditional energy markets, with growing attention given to transactive energy networks that enable energy trading between prosumers and consumers for more significant benefits in the cluster mode. This change raises operational and market challenges. In recent years, extensive research has been conducted on developing different local energy market models that enable energy trading and provide the opportunity to minimize the operational costs of the distributed energy resources by promoting localized market management. Local energy markets provide a stepping stone toward fully transactive energy systems that bring adequate flexibility by reducing users’ demand and reflecting the energy price in the grid. Designing a stable regulatory framework for local electricity markets is one of the major concerns in the electricity market regulation policies for the efficient and reliable delivery of electric power, maximizing social welfare, and decreasing electric infrastructure expenditure. This depends on the changing needs of the power system, objectives, and constraints. Generally, the optimal design of the local market requires both short-term efficiencies in the optimal operation of the distributed energy resources and long-term efficiency investment for high quality. In this paper, a comprehensive literature review of the main layers of microgrids is introduced, highlighting the role of the market layer. Critical aspects of the energy market are systematically presented and discussed, including market design, market mechanism, market player, and pricing mechanism. We also intend to investigate the role and application of distributed ledger technologies in energy trading. In the end, we illuminate the mathematical foundation of objective functions, optimization approaches, and constraints in the energy market, along with a brief overview of the solver tools to formulate and solve the optimization problem.
In order to reduce the system instability caused by credit risk in microgrid transactions in the blockchain, we propose a smart contract microgrid transaction model considering reputation value. Considering the instability caused by credit risk, the reputation factor is introduced to ensure the secure and stable operation of the microgrid energy trading system. The effectiveness of the scheme is verified by comparing traditional electricity trading and the trading with the introduced credit value scheme through simulation experiments.
Xinxin Ge, Di Yang, Yuntong Lv, Fei Wang · 9 authors
Nowadays, Direct Power Purchase (DPP) for industrial users has become an important part of the electricity market. This type of transaction usually needs to rely on regulatory agencies to assist in the transaction, and the transaction algorithm is relatively simple. Blockchain technology based on encryption algorithm has the function of distributed ledger, which can make DPP more transparent and reliable. This paper proposes a DPP transaction method, which incorporates the peak shaving characteristics of industrial users and the green certificate system into transactions, and completes related transactions on the blockchain platform. First, establish a DPP market structure based on blockchain technology. Second, establish a DPP transaction mechanism based on green certificates and peak shaving characteristics. Simulation results for four cases show that the proposed method can respond to peak shaving capacity and bring more profit to renewable energy companies.
Felipe Condon, José Manuel Martínez, Young-Chon Kim, Mohamed A. Ahmed
Nowadays, many households are adopting distributed energy resources (DERs), such as photovoltaics (PV) systems and energy storage systems (ESS) which enable each house to generate and consume energy. Peer-to-peer (P2P) energy trading is a new energy trading management among prosumers and consumers in the distribution power system, allowing excess energy to be traded locally. This work aims to design and implement an oracle blockchain-based system for local energy trading among smart homes in a microgrid. The main focus is the interaction between distributed P2P networks such as blockchain and oracle networks. Our implementation consists of a private Ethereum blockchain network and a Chainlink oracle network. Smart contracts enable prosumers and consumers to trade energy in an open auction while requesting external energy data from our testbed API through the oracle network for the settlement process.
Samuel Karumba, Subbu Sethuvenkatraman, Volkan Dedeoglu, Raja Jurdak · 5 authors
The increasing adoption of clean energy technologies, including solar and wind generation, demand response, energy efficiency, and energy storage (e.g. batteries and electric vehicles) have led to the evolution of the traditional electricity markets from centralised energy trading systems into Distributed Energy Trading (DET) systems. Consequently, savvy business executives are exploring how blockchain might impact their competitive advantage in the emerging DET markets. Due to its salient features of distributed ledger, consensus mechanisms, cryptography, and smart contracts, blockchain technology is being used to provide decentralised trust, immutability, security and privacy, and transparency in DET system. However, integrating blockchain in DET systems is facing technical, administrative, standardisation and economic barriers. Consequently, we seek to conduct a comprehensive market analysis to identify the specific challenges hindering the integration of blockchain in DET systems. Nonetheless, we noticed that there isn't any evaluation and review framework for conducting a systematic literature review on blockchain-based DET systems. Therefore, in this work we first proposed a conceptual evaluation and review framework for conducting a systematic literature review on blockchain-based DET systems. Then, using the proposed framework, we reviewed the current studies on blockchain-based DET systems to the identify specific challenges hindering the adoption of blockchain and their proposed solutions. Our review found that, although there has been tremendous progress in addressing the technical barriers, the administrative, standardisation and economic barriers have grossly been under reviewed.
In the current era, the skyrocketing demand for energy necessitates a powerful mechanism to mitigate the supply–demand gap in intelligent energy infrastructure, i.e., the smart grid. To handle this issue, an intelligent and secure energy management system (EMS) could benefit end-consumers participating in the Demand–Response (DR) program. Therefore, in this paper, we proposed a real-time and secure incentive-based EMS for smart grid, i.e., RI-EMS approach using Reinforcement Learning (RL) and blockchain technology. In the RI-EMS approach, we proposed a novel reward mechanism for better convergence of the RL-based model using a Q-learning approach based on the greedy policy that guides the RL-agent for faster convergence. Then, the proposed RI-EMS approach designed a real-time incentive mechanism to minimize energy consumption in peak hours and reduce end-consumers’ energy bills to provide incentives to the end-consumers. Experimental results show that the proposed RI-EMS approach induces end-consumer participation and increases customer profitabilities compared to existing approaches considering the different performance evaluation metrics such as energy consumption for end-consumers, energy consumption reduction, and total cost comparison to end-consumers. Furthermore, blockchain-based results are simulated and analyzed with the help of deployed smart contracts in a Remix Integrated Development Environment (IDE) with the parameters such as transaction efficiency and data storage cost.
Alireza Ghadertootoonchi, masoumeh bararzadeh, Maryam Fani
Bitcoin”s (BTC) mining process utilizes the proof of work (PoW) concept as the consensus algorithm., which consumes electricity. As a result., there are concerns regarding its sustainability and carbon emission. If one wants to estimate these, they first should have an estimation of the network's energy consumption which is hard to calculate due to its decentralized nature. To do so., two methods are conceivable. First, considering electricity price and miner's revenue (electricity costs are considered as a part of total revenue., then divided by electricity price to obtain electricity consumption), second, using hash rate along with the efficiency of mining devices. The latter is utilized in this study for short- and long-term predictions. In the short-term, recurrent neural network (RNN) is used, whereas in the long-term logistic functions are applied. It has been concluded that the ultimate energy consumption of the Bitcoin network, which will happen around 2025, is in the range of 40.4 to 73.41 TWh annually and its estimated value is 58.56 TWh.
Using microgrids to charge Electric Vehicles (EVs) is a significant step toward achieving Electric mobility. The microgrids generate electricity for self-use and sell surplus energy locally in Peer-to-Peer (P2P) manner, where seller and buyer meet to trade electricity directly on agreed terms without any intermediary. The energy trading decision for the microgrid is a challenging issue due to uncertainty of renewable energy yield, the electric demands of EVs and without knowing the offers of other competitive microgrids together makes it hard to decide the selling price of energy per unit. Further, there is a need to audit and verify the energy trading and store energy transactions securely in distributed manner to avoid collapse of the system in case of single point of failure. In this context, this paper presents a Blockchain and Quantum Reinforcement Learning based optimized Energy Trading (BQL-ET) model for E-mobility. Firstly, a double-auction mechanism is proposed to set optimal market-trading price by observing the selling price of each microgrid and the demand of EV's. Secondly, using smart contracts, consortium blockchain is deployed for the evaluation of overall utility, which includes energy supply, demand, and cost for both microgrids and EVs. Finally, Utility maximization problem is transformed into a Markov Decision Process (MDP), and in order to develop the learning policy and maximize overall utility, a QRL optimization for solving the MDP problem is proposed. Convergence analysis and performance results attest that BQL-ET convergences faster, maximizes the utility of both microgrids an EVs with lower transaction confirmation time and setting of the optimal market-trading price compared to state-of-the art models.