Syed Muhammad Ahsan, Hassan Abbas Khan, and Naveed-ul-Hassan
Smart buildings are being built as a synergetic deployment of electric vehicles (EVs) and renewable energy sources. Smart charging of EVs and vehicle-to-everything (V2X) technologies are seen as way forward in this context in terms of achieving economic, technological, and environmental advantages. This paper proposes a framework for multi-objective techno-economic optimization for profit maximization of multiple inter-connected buildings (with bilateral contracts) and scheduling of EVs. The optimization problem is modeled as mixed integer linear programming problem, which is solved using CPLEX solver in ILOG optimization studio. The primary building owns the photovoltaic system coupled with storage and charging infrastructure for the fleet of EVs. The optimized charging of EVs at affordable rates using local resources at primary building assists the grid in managing the EVs’ load during peak hours. Results indicate that the primary building gains up to 62% daily profit after factoring in solar, storage, and charging station deployment costs. Additionally, secondary buildings (without solar, storage and charging facilities) earn up to 20% cost savings depending upon the nature of bilateral contracts with primary building. The results further suggest that fleet of EVs gains 35%–65% savings in charging cost based on lower charging rates and V2X operations with primary and secondary buildings.
As a representative of clean energy, photovoltaic is expected to become a major supplier of electricity in the future. The combination of electric vehicle (EV) battery and charging station provides a feasible way to promote the effective consumption of photovoltaic. However, the efficiency of mobile power supply is limited by information asymmetry and security problems, and it is urgent to optimize the distribution process. Firstly, the article introduces the energy blockchain to improve the security level of electricity transaction, and designs the photovoltaic-energy storage-charging supply chain. Secondly, based on the selected road network and the actual situation of EV mobile power emergency distribution, the distribution logistics network with 50 distribution points is built. Thirdly, taking the delivery time and comprehensive cost as objective functions, the mathematical model of emergency distribution route optimization for EV mobile power supply is established, and the adaptive NSGA-II algorithm is adopted for example analysis. Finally, the parameter variation of NSGA-II and comparison with two algorithms of GA and MOPSO are carried out to validate the feasibility and applicability of proposed method. The purpose of the research is to quickly and effectively select the optimal distribution route of mobile power supply from many roads by maximizing customer demands and reducing costs, so as to promote the photovoltaic consumption.
The main roles of an advanced Battery Management System (BMS) are to dynamically monitor the battery packs and ensure the efficiency and reliability of the Battery Energy Storage System (BESS). Estimating the State of Charge (SoC), State of Health (SoH), State of Power (SoP), State of Energy (SoE), State of Temperature (SoT), and State of Safety (SoS) depends on collecting, aggregating, and analyzing real-time data of the BESS. Based on the applications of BESSs and their sizes, there are several restrictions in accessing and sharing data between battery manufacturers, power grid operators, and electricity consumers, while building necessary communication infrastructure is required. To resolve such issues, a conceptual and technological Blockchain-based system is developed in this paper to securely share the real-time data collected from BESSs for monitoring and control purposes, i.e., state estimation. The proposed system benefits from integrating the Internet of Things (IoT) devices in a decentralized structure and connectivity of such IoT nodes, data privacy, and transparency and auditability. The proposed Blockchain-based system is capable of accurately estimating SoC, SoH, SoP, SoE, SoT, and SoS of BESSs in small-and grid-scales.
S. Ramesh, J. Seetha, G. Ramkumar, Satyajeet Sahoo · 9 authors
The functioning of a solar hybrid power system is investigated in this research using a unique fuzzy control method. Turbines, solar photovoltaics, diesel engines, fuel cells, aqua-electrolyzes, and other autonomous generation products are used in the hybrid renewable energy system. Further energy storage components of the system include the batteries, turbine, and ultracapacitor. This research incorporates a supercapacitor hybrid energy storage system (HESS) into a solar hybrid power generating system, allowing the consumption and energy storage space and power output to be significantly increased. This study’s approach incorporates a decentralized power generation system with a HESS while increasing electrical output in phases utilizing a dynamic reactive power compensation scheme and a conductance-fuzzy dual-mode control strategy. Due to a nonlinear behavior of photovoltaic (PV) devices’ power output, maximum power point tracking (MPPT) methods must be used to create the greatest power. Infrequently developing atmospheric circumstances, traditional MPPT algorithms do not work adequately. Modeling is used to determine the microgrid’s power output to the photovoltaic hybrid power generating organization, as well as the optimization method for each device in the network. The dynamic power factor correction scheme and also the conductance-fuzzy dual-mode control approach are primarily used in this study to optimize the solar hybrid renewable energy system.
In this paper, the idea of applying phase change materials (PCMs) as a method of energy use reduction in bitcoin mining will be investigated. The possible applications discussed include the implementation of PCMs in the mining equipment itself, the integration of PCMs into the mining warehouse envelope, and the use of PCMs in air conditioning systems. These applications aim to decrease energy requirements for warehouse climate control systems by decreasing their cooling load, and by increasing the efficiency of the miners by keeping them at a cooler operating temperature. This reduction in energy usage will help reduce bitcoin’s carbon footprint produced by fossil fuels electricity production.
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.
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.
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.
The grid connected photovoltaic (PV) power plants (PVPPs) are booming nowadays. The main problem facing the PV power plants deployment is the intermittency which leads to instability of the grid. In order to stabilize the grid, either energy storage device - mainly batteries - or a power curtailment technique can be used. The additional cost on utilizing batteries make it not preferred solution, because it leads to a drop in the return on investment (ROI) of the project. A good alternative, is using a customized load (such as; cryptocurrency-based loads) which consumes the surplus energy. This paper investigating the usage of a customized load - cryptocurrency mining rig - to create an added value for the owner of the plant and increase the ROI of the project. These devices are widely used to perform the required calculations for validating the transactions on the network of the Blockchain. A comparison between the ROI of the mining rig and the battery have been conducted in this study. Based on this study the mining rig has superior ROI of 7.7% - in the case with the lowest ROI - compared to 4.5% for battery. Moreover, an improved controlling strategy is developed to combine both the battery and mining rig in the same system. The developed strategy is able to keep the profitability as high as possible during the fluctuation of the mining network.
Increasing electric vehicle (EV) penetration in distribution networks necessitate EV charging coordination. This paper proposes a two-stage EV charging coordination mechanism that frees the distribution system operator (DSO) from extra burdens of EV charging coordination. The first stage ensures that the total charging demand meets facility constraints, and the second stage ensures fair charging welfare allocation while maximizing the total charging welfare via Nash-bargaining trading. A decentralized algorithm based on the alternating direction method of multipliers (ADMM) is proposed to protect individual privacy. The proposed mechanism is implemented on the blockchain to enable trustworthy EV charging coordination in case a third-party coordinator is absent. Simulation results demonstrate the effectiveness and efficiency of the proposed approach.
Yuris Mulya Saputra, Diep N. Nguyen, Dinh Thai Hoang, Thang X. Vu · 6 authors
In this paper, we propose a novel economic-efficiency framework for an electric vehicle (EV) network to maximize the profits (i.e., the amount of money that can be earned) for charging stations (CSs). To that end, we first introduce an energy demand prediction method for CSs leveraging federated learning approaches, in which each CS can train its own energy transactions locally and exchange its learned model with other CSs to improve the learning quality while protecting the CS's information privacy. Based on the predicted energy demands, each CS can reserve energy from the smart grid provider (SGP) in advance to optimize its profit. Nonetheless, due to the competition among the CSs as well as unknown information from the SGP, i.e., the willingness to transfer energy, we develop a multi-principal one-agent (MPOA) contract-based method to address these issues. In particular, we formulate the CSs’ profit maximization as a non-collaborative energy contract problem under the SGP's unknown information and common constraints as well as other CSs’ contracts. To solve this problem, we transform it into an equivalent low-complexity optimization problem and develop an iterative algorithm to find the optimal contracts for the CSs. Through simulation results using a real CS dataset, we demonstrate that our proposed framework can enhance energy demand prediction accuracy up to 24.63 percent compared with other machine learning algorithms. Furthermore, our proposed framework can outperform other economic models by 48 and 36 percent in terms of the CSs’ utilities and social welfare (i.e., the total profits of all participating entities) of the network, respectively.
Electric Vehicles (EVs) have generated a lot of interest in recent years, due to the advances in battery life and low pollution. Similarly, the expansion of the Internet of Things (IoT) allowed more and more devices to be interconnected. One major problem EVs face today is the limited range of the battery and the limited number of charging or battery swapping stations. A solution is to not only build the necessary infrastructure, but also to be able to correctly estimate the remaining power using an efficient battery management system (BMS). For some EVs, battery swapping can also be an option, either at registered stations, or even directly from other EV drivers. Thus, a network of EV information is required, so that a successful battery charge or swap can be made available for drivers. In this paper two blockchain implementations for an EV BMS are presented, using blockchain as the network and data layer of the application. The first implementation uses Ethereum as the blockchain framework for developing smart contracts, while the second uses a directed acyclic graph (DAG), on top of the IOTA tangle. The two approaches are implemented and compared, demonstrating that both platforms can provide a viable solution for an efficient, semi-decentralized, data-driven BMS.
Zahra Foroozandeh, Sérgio Ramos, João Soares, Fernando Lezama · 7 authors
Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs charge and discharge processes and also those of BESS, in which the binary decision variables represent the charging and discharging of EVs/BESS in each period. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis are considered. The results point to a 65% reduction in peak load consumption supplied by an external power grid and a 28.4% reduction in electricity consumption costs.
The adoption of blockchain in the public electrical vehicle charging market has yet to be realized to its full potential, despite existing proof-of-concept. A positive outlook for blockchain is suggested by contemporary research, as well as the need for empirical studies to fully identify blockchain’s barriers to adoption. Through qualitative methods, a focused literature review, and in-depth interviews with subject matter experts, this thesis investigated which barriers to blockchain adoption exist in the public electrical vehicle charging market. The results indicated that the main barrier to blockchain adoption was the structure of the public electrical vehicle charging market itself, since it is an immature market experiencing constant change. This was followed by: coordination, norms and cultures, business process, incumbent technological solutions, regulations and legislations, shared infrastructure, and distributed ledger technology. These barriers were not shown individually, but were affected by each other. It is concluded that blockchain technology is not needed by the market in its current state, as its key defining attributes of privacy, security and decentralization are not deemed worth the cost of its own implementation. This research contributes to, and updates, the knowledge of blockchain utilization for the public electrical vehicle charging market. The results can be used by private and public organizations and scholars as reference material with regards to blockchain adoption for public electrical vehicle charging.
Godwin C. Okwuibe, Zeguang Li, Thomas Brenner, Ole Langniß
The increase in development of electric vehicle(EV) will have a strong impact on the power distribution grid if adequate care is not taken on the high power demand required for charging EV. Consequently, there is need to create a platform to enable charging point operators to effectively manage the EV user’s charging requests and ensure that there charging needs are satisfied while not exceeding the distribution grid capacity. If this is not done, there is no doubt that in few a years, EV owners will be faced with the problems of unavailability of charging stations and congestion in grid sequel to simultaneous charging of many EV’s. This work proposes a smart EV charging infrastructure based on a blockchain platform. With the charging demand (kWh) and maximum duration of the charging event provided by the EV user, the EV load flexibility is determined and utilized through smart charging to achieve a stable grid. EV owners and charging stations are linked through the platform thereby reducing the actors in EV charging ecosystem from six to four. Flexibility (power and time) in charging of EV is traded within the blockchain platform. By this, additional investors will be attracted into the business of EV charging station and through flexible offers, EV loads are shifted from the peak load hours. Consequently, the simulations shows that the acceptance rate of EV users increased by more than 50% when our smart charging system was adopted compared to the normal charging scenario.
Eduardo Francisco, Luís Tiago Ferreira, Carlos Silva, Joaquim Braga
The electric vehicle (EV) market is evolving fast with an expected high penetration of EV in the coming years. These EVs are dependent on charging infrastructure and since most charging will happen at home this will bring challenges to the low-voltage distribution network. The main challenge addressed in this study is the available grid capacity and what could be done to prevent the massive request of residential buildings grid connection reinforcements, which represents significant costs to consumers, large waiting times, which are not compatible with the rising necessities for charging EV and a general oversizing of the distribution network, which will drive the already low utilisation factors even lower. The presented solution for this challenge is to introduce a flexible power grid connection, which takes advantage of smart charging technology and the applications of flexible power contracts to allow the charging of 5–7 times more EV in the common garages of residential buildings without any building grid connection reinforcement and for a fraction of the cost. The distribution system operator (DSO) will represent a key role in the implementation of this solution, not only regarding the technical aspects but also regarding the onboarding of the consumers.
Jan 1, 2018·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Hua Song, Ence Zhou, Bingfeng Pi, Jun Sun · 6 authors
Battery swapping is a solution of electric vehicle (EV) battery refueling. For EV owners, the battery information and transaction’s correctness, openness, traceability and immutability is difficult to get guarantee in traditional centralized system. The trust lacking between EV owners and swapping station is caused, and becomes a big challenge to EV’s rapid development. An objective mechanism based on decentralized blockchain system is proposed to manage battery swapping and solve the trust lacking issue. With this solution, both battery’s life-cycle information and all operations histories are permanently saved in blockchain network. All key logics are driven by smart contracts, the battery price calculation and the digital currency exchange between EV owners and station are realized by smart contracts automatically and accurately. A primary prototype based on Ethereum is analyzed and implemented to illustrate the feasibility of managing battery swapping and refueling based on blockchain system to solve the trust lacking issue.
Chao Liu, Kok Keong Chai, Xiaoshuai Zhang, Eng Tseng Lau · 5 authors
The electric vehicle (EV) charging scheme can reduce the power generation costs and improve the smart grid resilience. However, the huge penetrations of EVs can impact the voltage stability and operating costs. In this paper, a novel EV participation charging scheme is proposed for a decentralized blockchain-enabled smart grid system. Our objectives are to minimize the power fluctuation level in the grid network and the overall charging cost for EV users. We first formulate the power fluctuation level problem of the smart grid system that take into accounts of EV battery capacities, charging rates, and EV users charging behavior. And then, we propose a novel adaptive blockchain-based electric vehicle participation (AdBEV) scheme that uses the Iceberg order execution algorithm to obtain an improved EV charging and discharging schedule. The simulation results show the proposed scheme outperforms the scheme that applying genetic algorithm approach in term of lowering the power fluctuation level and overall charging costs.
Albert Y. S. Lam, Ka-Cheong Leung, Victor O. K. Li
Due to various green initiatives, renewable energy will be massively incorporated into the future smart grid. However, the intermittency of the renewables may result in power imbalance, thus adversely affecting the stability of a power system. Frequency regulation may be used to maintain the power balance at all times. As electric vehicles (EVs) become popular, they may be connected to the grid to form a vehicle-to-grid (V2G) system. An aggregation of EVs can be coordinated to provide frequency regulation services. However, V2G is a dynamic system where the participating EVs come and go independently. Thus, it is not easy to estimate the regulation capacities for V2G. In a preliminary study, we modeled an aggregation of EVs with a queueing network, whose structure allows us to estimate the capacities for regulation-up and regulation-down separately. The estimated capacities from the V2G system can be used for establishing a regulation contract between an aggregator and the grid operator, and facilitating a new business model for V2G. In this paper, we extend our previous development by designing a smart charging mechanism that can adapt to given characteristics of the EVs and make the performance of the actual system follow the analytical model.
The important energy requirements for the desalination process impose especially in autonomous and decentralized plants supplied by Renewable Energy Sources (RES). In this paper, five alternative energy generation topologies of Reverse Osmosis desalination process are evaluated. The proposed topologies assessed in terms of economic, environmental, technological and societal indices are compared using multi-criteria analysis, namely the Analytic Hierarchy Process (AHP) and the Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE). Ranking of topologies resulted in the selection of direct connection and hybrid configuration as optimum solutions. In case economic priorities prevail diesel generation should also be considered.