This paper investigates a double auction-based peer-to-peer (P2P) energy trading market for a community of renewable prosumers with private information on reservation price and quantity of energy to be traded. A novel competition padding auction (CPA) mechanism for P2P energy trading is proposed to address the budget deficit problem while holding the advantages of the widely-used Vickrey-Clarke-Groves mechanism. To illustrate the theoretical properties of the CPA mechanism, the sufficient conditions are identified for a truth-telling equilibrium with a budget surplus to exist, while further proving its asymptotical economic efficiency. In addition, the CPA mechanism is implemented through consortium blockchain smart contracts to create safer, faster, and larger P2P energy trading markets. The proposed mechanism is embedded into blockchain consensus protocols for high consensus efficiency, and the budget surplus of the CPA mechanism motivates the prosumers to manage the blockchain. Case studies are carried out to show the effectiveness of the proposed method.
Climate change persists as a pressing global issue due to high greenhouse gas emissions from fossil fuel-based energy sources. A transition to a greener energy matrix combined with carbon offsetting is imperative to mitigate the rate at which global temperature ascends. While countries have deployed faith in green hydrogen to accelerate worldwide decarbonization efforts, the concurrent rise of blockchain-operated crypto-applications, such as bitcoin, has exacerbated climate change concerns. In this study, we propose technological solutions that combine the green hydrogen infrastructure with bitcoin mining operations to catalyze environmental and socioeconomic sustainability in climate change mitigation strategies. Since the present state of crypto-operations undeniably contributes to worldwide carbon emissions, it becomes vital to explore opportunities for harnessing the widespread enthusiasm for bitcoin as an aid toward a sustainable and climate-friendly future. Our findings reveal that green hydrogen production, paired with crypto-operations, can accelerate the deployment of solar and wind power capacities to boost conventional mitigation frameworks. Specifically, leveraging the economic potential derived from green hydrogen and bitcoin for incremental investment in renewable energy penetration, this dynamic duo can enable capacity expansions of up to 25.5% and 73.2% for solar and wind power installations. Therefore, the proposed technological solutions that leverage green hydrogen and bitcoin mining, bolstered with appropriate policy interventions, can not only strengthen renewable power generation and carbon offsetting capacities but also contribute significantly to achieving climate sustainability.
Currently, there is an active use of distributed registry technology in various sectors of the economy by providing transparency, improving tracking of actions within processes, and ensuring trust in open systems. There is a need to evaluate the performance of distributed registries based on measurable indicators. The article presents an overview of distributed registries performance indicators, methods to improve the efficiency and evaluation of distributed registries.
Sahar Yousif Mohammed, Thaar Kh. Asman, Hadeel M Salih, Alaa Mohammed Mahmood
These days, we are observing a very rapid spread of the electric vehicleindustry. This means a significant increase in the data and energy exchanged betweenthese vehicles. The existing centralized approach is less secure and more vulnerableto data destruction and manipulation by intruders. Therefore, it became necessary tosearch for an alternative that provides excellent protection for this massive amountof data and energy. Although blockchain technology and cryptocurrencies are closelyassociated, they also have many other potential applications in fields including energyand sustainability, the Internet of Things (IoT), smart cities, smart mobility, andmore. In the Internet of Vehicles (IoV) idea, blockchain can provide security forelectric vehicle (EV) transactions, enabling electricity trading to be carried out ina decentralized, transparent, and secure manner. . This paper will explain the use ofblockchain in this field and how it can handle the trade of transmitted and receivedenergy between electric vehicles. The advantages of using blockchain with electriccars and how it can secure the transactions of energy trading will be shown too. Agroup of researchers in this field and the challenges that face this technology in energytrading will be discussed too; the studies will be looked at, and recommendations forinvestments and security will be made. Additionally, the future implications of variousblockchain technologies will be highlighted.
The task of carbon emission reduction is severe in the power industry in China under the national goal of “carbon peaking and carbon neutrality”. The current carbon reduction is mainly based on supply side, but the effect is limited. To solve this problem, this paper proposed a coordinated supply–demand carbon emission reduction strategy based on blockchain technology. Based on the carbon emission reduction of complementary thermal power and renewable energy under the carbon trading mechanism of power supply side, users are made to participate in the individual level carbon trading mechanism with the help of blockchain technology, and the carbon emission reduction in power demand side is guided through the market mechanism, thus forming a supply–demand collaborative carbon emission reduction strategy of source side control and terminal inhibition. By analyzing the decision changes of both the supply and demand sides of electricity before and after the introduction of blockchain, quantifying the influence of blockchain on electricity quantity, electricity price and users’ utility in turn, and establishing the personal carbon trading mechanism supported by blockchain, a game model of two-side interaction between supply and demand was constructed. The simulation results show that the collaborative carbon emission reduction strategy based on blockchain gives full play to the potential of carbon reduction in power demand side, and the personal carbon trading mechanism can better inhibit terminal carbon emissions, which is conducive to the deep carbon emission reduction of the power industry.
Kuo-Yang Wu, Tzu-Ching Tai, Bo-Hong Li, Cheng‐Chien Kuo
Under net-zero objectives, the development of electric vehicle (EV) charging infrastructure on a densely populated island can be achieved by repurposing existing facilities, such as rooftops of wholesale stores and parking areas, into charging stations to accelerate transport electrification. For facility owners, this transformation could enable the showcasing of carbon reduction efforts through the self-use of renewable energy while simultaneously gaining charging revenue. In this paper, we propose a dynamic energy management system (EMS) for a solar-and-energy storage-integrated charging station, taking into consideration EV charging demand, solar power generation, status of energy storage system (ESS), contract capacity, and the electricity price of EV charging in real-time to optimize economic efficiency, based on a real-world situation in Taiwan. This study confirms the benefits of ESS in contracted capacity management, peak shaving, valley filling, and price arbitrage. The result shows that the incorporation of dynamic EMS with solar-and-energy storage-integrated charging stations effectively reduces electricity costs and the required electricity contract capacity. Moreover, it leads to an augmentation in the overall operational profitability of the charging station. This increase contains not only the revenue generated from electricity sales at the charging station but also the additional income from surplus solar energy sales. From a comprehensive cost–benefit perspective, introducing this solar-and-energy storage-integrated EMS can increase facility owners’ net income by 1.25 times compared to merely installing charging infrastructure.
Yuxiao Liang, Zhishang Wang, Abderazek Ben Abdallah
In the present era, energy issues are a significant concern, and the energy trading market is the crucial sector to facilitate supply-demand balance and sustainable development. For better demand response and grid balancing, vehicle-to-grid (V2G) technology is rapidly gaining importance in energy markets. To narrow the gap between ideal V2G goals and actual applications needs, energy trading system has to overcome the challenges of over-centralized structure, inflexible timeline adaptation, limited market scale and energy efficiency, excessive feedback time costs, and low rate of economic return. To address these issues and ensure a secure energy market, we propose a decentralized intelligent V2G system called V2G Forecasting and Trading Network (V2GFTN) to achieve efficient and robust energy trading in campus EV networks. A multiple blockchain structure is proposed in V2GFTN to ensure trading security and data privacy between energy requests and offers. V2GFTN also integrates energy forecasting functions for EVs with a smart energy trading and EV allocation mechanism called SRET so that the EVs with driving tasks can supply their extra power back to the grid and achieve higher energy efficiency and economic profit. Through rigorous experimentation and compared with equivalent studies, V2GFTN system has demonstrated higher economic profit and energy demand fill rate by up to 1.6 times and 1.9 times than the state-of-the-art V2G approaches.
The widespread adoption of electric cars (EVs) can be attributed to their many advantages over conventional gas-powered automobiles. However, there may be difficulties in incorporating EVs into the grid due to increased energy demand and peak load. We propose a blockchain-based federated learning scheme using different linear regression algorithms for energy demand prediction for EVs. The information gathered from EVs is stored on the blockchain network. Only those with the proper credentials can decrypt the data from its encrypted storage. Data from EVs is utilized to train a machine learning model with the use of a federated learning algorithm. Each EV is used to train a model, and then the models’ parameters are distributed throughout the blockchain. Our approach is innovative in analyzing of BCFL communications overhead and latency issues, while delving deeper into its dynamics to measure and reduce communication delays to maximize system efficiency. The implementation results verify the effectiveness of our system in anticipating EVs’ energy requirements. For the training of the BCFL model, a huge real-world dataset was used from over 60,000 transactions at EV charging stations in Boulder city, Colorado. The results show that the framework is reliable, since all the models have R2values above 0.91, which indicates a high degree of accuracy in predicting energy use.
Distributed energy generation disrupts traditional energy markets by blurring the line between producers and consumers and enabling the emerging prosumers to trade energy in per-to-peer transactions. Blockchain technology automates peer-to-peer energy trades in a distributed database architecture that achieves security and cost-effectiveness using cryptographic hashing and consensus-based verification. Before its deployment, an energy blockchain trading application needs to be tested in a virtual environment that is analogous to the real-world setting to ensure correct implementation and identify potential obstacles and opportunities. This study suggests executing such a testing within a framework that integrates a Geographic Information System (GIS) environment with an Agent-Based Modeling (ABM) simulation platform. The application of this testing framework to a case study of solar Photovoltaic (PV) energy trade among household peers in in Doha, Qatar, shows how the integration of the GIS environment offers a detailed analysis of transactions in local housing community markets. The ABM simulation reveals that population density, energy market prices, and household proximity significantly influence residential PV energy trading in Qatar. The ensuing simulation environment provides a decision-support platform for designing and implementing decentralized trading systems based on blockchain technology, and high-performance computing can enhance model performance for scalable energy blockchain analysis in Qatar and beyond.
Imran Hussain, Hafiz Ashiq Hussain, Nasim Ullah, Stanislav Mišák
Conventional centralized optimization and management approaches may not work well in an emerging and distributed energy system with a high penetration of electric vehicles and green energy sources. The usage of blockchain technology is growing as a strong competitor as it can provide this kind of market with a transparent, secure, and efficient transactional platform. Nevertheless, most energy systems usually depend on complex mathematical optimization, which is poorly incorporated into blockchain applications. Moreover, time-sensitive message dissemination requirements, resource-intensiveness, high computational load, and communication overhead of the traditional blockchain consensus mechanisms make it difficult to connect with real-time vehicular networks. Here, we employ Proof of Intelligence (PoI), a novel prosumer-centric blockchain consensus mechanism to develop a comprehensive model of trust based on commitments of supply and demand through the application of peer-to-peer energy exchange with effective and dynamic integration of renewable sources and electric vehicles both in the day ahead and real-time energy trading platforms. Additionally, the PoI smart contract is developed to seamlessly incorporate mathematical optimization with an increased level of security, scalability, throughput, and low confirmation latency of transactions achieved through the reduced effort involved in finding and confirming the optimal solution in comparison with conventional blockchain consensus mechanisms.
Alia Al Sadawi, Eiman ElGhanam, Mohamed S. Hassan, Ahmed Osman
With the increasing investments in on-the-move electric vehicle (EV) charging solutions and wireless charging lanes (WCLs), coordination of the energy requirements of mobile EVs becomes essential to ensure load balancing while maximizing demand coverage. This necessitates the development of online and mobility-aware algorithms for assigning EV-to-charging lanes. In this work, a decentralized, blockchain-based EV assignment and energy allocation system is presented. The objective of system is to coordinate the charging requirements of mobile EVs among the available WCLs within a network of EV chargers in an Internet of Electric Vehicles (IoEVs). This blockchain-based system offers higher security, transparency and immutability over traditional rule-based coordination schemes. It also offers an integrated end-to-end framework that handles user registration, authentication, lane activation and energy reporting. This is in addition to its main functionality of establishing a real-time and load-balanced EV-to-WCL assignment process that addresses the EV energy requirements within constraints of traveling distance and remaining EV energy. The proposed system is tested on the Ethereum blockchain and its security and transparency are both validated accordingly.
Alessandro Neri, Maria Angela Butturi, Henrique L. Sauer, Francesco Lolli · 6 authors
The growing demand for electric vehicles necessitates an efficient and sustainable life-cycle management of lithium-ion batteries. This work examines existent literature on digital battery passports, crucial for high-quality data for decision-making purposes, and distributed ledger technologies as transparent and efficient enablers. An hybrid BWM-TOPSIS approach is employed to rank various platforms for digital passport implementation in an automotive company. The analysis identifies Hedera as the most suitable ledger, followed by IOTA and EOS. Future research directions include empirical validation of the findings and exploring collaborative decision-making models to enhance the robustness of the selection process.
Liaqat Ali, M. Imran Azim, Nabin B. Ojha, Jan Peters · 8 authors
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 second-generation (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, cost-revenue 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.
Presently, majority of car-pooling services depend on a central third party which makes these platforms susceptible to data privacy, security concerns, and a single point of failure. Moreover, drivers and passengers are charged with different services fees by the electric mobility service provider. The emergence of emerging technologies such as Distributed Ledger Technologies (DLT) can foster trust, boost electric car-pooling business models. Hence, DLT is utilized to store electric car-pooling trips, drivers, and passengers’ information to ensure user privacy and maintain security. Similarly, social practice theories such as Community of Practice (CoP) is progressively considered as a significant structure within societies as it aids the development and sharing of resources across groups. But very little attention has been devoted to examined how CoP can be employed to support the design of decentralized on-demand electric car-pooling. Leveraging CoP and DLT, this paper proposes a decentralized community of practice-based model that enables drivers to publish electric car-pooling services and passengers to be matched to a driver without depending on a trusted third party. A systematic literature review was adopted to collect data and a case study of a decentralized on-demand electric car-pooling was presented. Findings from this study highlights conceptualization of CoP for improving decentralized on-demand electric car-pooling and provide insights on efficient decentralized mechanisms for electric car-pooling. Theoretically, this article identifies the current problems, state-of-the-art of decentralized electric car-pooling. For policy implications this study provides guidelines to effectively govern and manage the development of on-demand electric car-pooling for sustainable public transportation.
Efficient energy management of Distributed Re-newable Energy Resources (DRER) enables a more sustainable and efficient energy ecosystem. Therefore, we propose a holistic Energy Management System (EMS), utilising the computational and energy storage capabilities of nearby Electric Vehicles (EVs), providing a low-latency and efficient management platform for DRER. Through leveraging the inherent, immutable features of Distributed Ledger Technology (DLT) and smart contracts, we create a secure management environment, facilitating interactions between multiple EVs and energy resources. Using a privacy preserving load forecasting method powered by Vehicular Fog Computing (VFC), we integrate the computational resources of the EVs. Using DLT and our forecasting framework, we accommodate efficient management algorithms in a secure and low-latency manner enabling greater utilisation of the energy storage resources. Finally, we assess our proposed EMS in terms of monetary and energy utility metrics, establishing the increased benefits of multiple interacting EVs and load forecasting. Through the proposed system, we have established the potential of our framework to create a more sustainable and efficient energy ecosystem whilst providing measurable benefits to participating agents.
With the rapid development and technological innovation in the energy market, peer-to-peer (P2P) energy trading, as a decentralised and efficient trading model, has been widely studied and practically applied. However, in P2P energy transactions involving multiple prosumers, there are challenges such as information asymmetry, trust issues, and transaction transparency. To address these challenges, blockchain technology, as a distributed ledger technology, provides solutions. In this paper, we propose a blockchain technology-based prosumer–virtual power plant (VPP) two-tier interactive energy management framework to assist P2P energy transactions between multiple prosumers. In this framework, the virtual power plant acts as a leader and sets differentiated tariffs for different prosumers to equal the distribution of social welfare. The various prosumers act as followers and respond to the leader’s decisions in a cooperative manner. Blockchain’s immutability and transparency enable prosumers to participate in P2P energy trading with greater trust, share idle energy, and share revenues based on contribution. In addition, given the uncertainty of renewable energy, this paper employs a stochastic planning approach with conditional value at risk (CVaR) to describe the expected loss of VPP. Ultimately, as verified by the arithmetic simulation, the blockchain co-governance transaction model effectively supports energy coordination and optimization of complementarities while ensuring the utility of each transaction node. This model promotes the application of renewable energy in local consumption, while facilitating the innovation and sustainable development of the energy market.
Liaqat Ali, M. Imran Azim, Nabin B. Ojha, Jan Peters · 9 authors
The electricity market has increasingly played a significant role in ensuring the smooth operation of the power grid. The latest incarnation of the electricity market follows a bottom-up paradigm, rather than a top-down one, and aims to provide flexibility services to the power grid. The blockchain-based local energy market (LEM) is one such bottom-up market paradigm. It essentially enables consumers and prosumers (those who can generate power locally) within a defined power network topology to trade renewable energy amongst each other in a peer-to-peer (P2P) fashion using blockchain technology. This paper presents the development of such a P2P trading-facilitated LEM and the analysis of the proposed blockchain-based LEM by means of a case study using actual German residential customer data. The performance of the proposed LEM is also compared with that of BAU, in which power is traded via time-of-use (ToU) and feed-in-tariff (FiT) rates. The comparative results demonstrate: (1) the participants’ bill savings; (2) mitigation of the power grid’s export and import; (3) no/minimal variations in the margins of energy suppliers and system operators; and (4) cost comparison of Ethereum versus Polygon blockchain, thus emphasising the domineering performance of the developed P2P trading-based LEM mechanism.
Blockchain technology is very useful. This paper considers the application of blockchain technology to smart contracts, green certification, and market information disclosure, and introduces the carbon trading market price as a parameter to solve the dynamic incentive problem of the government for port enterprises to reduce emissions under the carbon trading policy. Based on the state change of port carbon emission reduction, this paper uses principal–agent theory to construct the dynamic incentive contract model of government without blockchain, with blockchain, and when carbon trading is considered under blockchain, respectively, and uses the optimal control method to solve and analyze the model. This paper finds that only when the opportunity cost of port enterprises is greater than a certain critical point and the fixed cost of blockchain is less than a certain critical point, the implementation of blockchain will help improve government efficiency. However, only when the critical value of carbon emission reduction of port enterprises and the unit operating cost of blockchain are small, the government should start the carbon trading market under blockchain technology. Through numerical simulation, this paper also finds that it is usually beneficial for the government to regulate and appropriately increase the carbon trading market price.
Yubao Zhang, Xin Chen, Yi Gu, Zhicheng Li · 5 authors
With the growing prevalence of electric vehicles (EVs) and advancements in EV electronics, vehicle-to-grid (V2G) techniques and large-scale scheduling strategies have emerged to promote renewable energy utilization and power grid stability. This study proposes a multi-stakeholder hierarchical V2G coordination based on deep reinforcement learning (DRL) and the Proof of Stake algorithm. Furthermore, the multi-stakeholders include the power grid, EV aggregators (EVAs), and users, and the proposed strategy can achieve multi-stakeholder benefits. On the grid side, load fluctuations and renewable energy consumption are considered, while on the EVA side, energy constraints and charging costs are considered. The three critical battery conditioning parameters of battery SOX are considered on the user side, including state of charge, state of power, and state of health. Compared with four typical baselines, the multi-stakeholder hierarchical coordination strategy can enhance renewable energy consumption, mitigate load fluctuations, meet the energy demands of EVA, and reduce charging costs and battery degradation under realistic operating conditions.
Syed Muhammad Ahsan, Hassan Abbas Khan, Sarmad Sohaib, Anas Hashmi
The operation of smart buildings (with solar, storage and suitable power routing infrastructure) can be optimized with the addition of parking stations for electric vehicles (EVs) with vehicle-to-everything (V2X) operations including vehicle-to-vehicle (V2V), vehicle-to-building (V2B) and vehicle-to-grid (V2G) operations. In this paper, a multi-objective optimization framework is proposed for the smart charging and discharging of EVs along with the maximization of revenue and savings of smart building (prosumers with solar power, a battery storage system and a parking station) and non-primary/ordinary buildings (consumers of electricity without solar power, a battery storage system and parking station). A mixed-integer linear program is developed to maximize the profits of smart buildings that have bilateral contracts with non-primary buildings. The optimized charging and discharging (V2X) of EVs at affordable rates utilizing solar power and a battery storage system in the smart building helps to manage the EV load during on-peak hours and prevent utility congestion. The results indicate that in addition to the 4–9% daily electricity cost reductions for non-primary buildings, a smart building can achieve up to 60% of the daily profits. Further, EVs can save 50–69% in charging costs while performing V2X operations.
The complexities associated with modern energy grids, including high penetration levels of renewable energy sources at the end use customers, the proliferation of electric vehicles (EVs), as well as decentralized energy management systems and energy data portals and services, require secure, reliable and cost-effective new platforms to administer such systems in a transparent manner. Blockchain technology can address such challenging complexities efficiently. This paper presents a thorough literature review of all potential blockchain applications in electric energy systems. First, all potential blockchain application possibilities and constraints in electric energy systems have been identified. Then, the implementations of blockchain technology in power systems are divided into various categories, such as demand response (DR), EVs, decentralized energy management, energy trading and distributed renewable energy. A detailed literature analysis is conducted by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines in a systematic approach using credible and reliable database systems such as IEEE Xplore, ScienceDirect, and Scopus to highlight current advancements in blockchain technology uses in electric energy systems particularly in DR, as well as future potential and existing problems. The paper is divided into three parts. The first part lists the important publications that have delved into the implementation of Blockchain in demand response. Trends of Blockchain applications in other electric energy system areas are detailed in the second section. The final part highlights the evolution and advancement of blockchain-based electric energy systems including favourable attributes of structures and designs, as well as the challenges and future trends.
Liaqat Ali, M. Imran Azim, Jan Peters, Nabin B. Ojha · 10 authors
In this paper, a framework is proposed for integration of peer-to-peer (P2P) trading-based local energy market (LEM) with the blockchain technology. The proposed LEM model allows prosumers and consumers to trade electricity among each other ensuring the presence of the retailer and network utility – who are also essential parts of a P2P network. The P2P contracts settled between various prosumers and consumers are governed by mutually agreed upon smart contracts – which are then written in an Ethereum blockchain to record and store bidding history, P2P transactions, and settlements. An effective formulation is also presented to capture P2P trading quantities and prices among participating prosumers and consumers in a decentralised fashion with an appropriate analysis of financial viability. Finally, a case study is conducted in a real Australian context; in which the engagement of both prosumers and consumers are taken into account, and the performance of the proposed blockchain-enabled LEM is compared with business-as-usual (BAU) to demonstrate the model's superiority.
Liaqat Ali, M. Imran Azim, Jan Peters, Nabin B. Ojha · 10 authors
This paper presents a local energy market (LEM) model to conduct peer-to-peer (P2P) energy trading between a number of participants by dint of the Ethereum-based blockchain technology. The proposed LEM mechanism is structured by considering relevant functional constraints while energy trading is arranged between several participants in the presence of other stakeholders including energy retailer and network operator. LEM participants’ mutual bidding intended P2P trading, actual settlement, and final billing are executed using the smart contracts in Ethereum blockchain to record LEM transactions and related data in an unchangeable and distributed fashion. Lastly, a case study is performed in an Australian suburb with 300 LEM participants, and the simulation results are benchmarked with an existing business-as-usual (BAU)scenario. The simulation results outline that the formulated LEM mechanism 1) reduces the electricity cost of participants remarkably while improving their self-sufficiency, 2) minimises power grid export and import, and 3) retains income margins for the energy retailer and network operator.