Electricity Transactions Research Articles

A Multilateral Transactive Energy Framework of Hybrid Charging Stations for Low-Carbon Energy-Transport Nexus

This article proposes a multilateral multienergy trading framework for synergetic hydrogen (H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) and electricity transactions among renewable-dominated hybrid charging stations (HCSs). In this framework, each autonomous HCS with various renewable energy resource (RES) endowment can harvest local renewables for internal green H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> and electricity generation to simultaneously meet demands of electric vehicles (EVs) and hydrogen-powered vehicles (HVs) from the transportation network. The surplus electricity/H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> production of the HCS is accommodated by external multilateral transactions to increase the additional profit. Besides, each HCS is modeled as a sustainable energy hub, and multiple hubs with multienergy transactions contribute toward a low-carbon energy-transport nexus. A partial differential equation model based on fluid dynamic theory is formed to capture the temporal and spatial dynamics of traffic flows for estimating the EV/HV loads at HCSs. Furthermore, a distributed multilateral pricing algorithm is developed to iteratively derive the optimal prices and quantities for transactive electricity and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> . Comparative studies corroborate the superiority of the proposed methodology on economic merits and RES accommodation.

Game theory applications in the electricity market and renewable energy trading: A critical survey

With the acceleration of China’s electricity market construction, it is urgent to establish a unified electricity transaction mechanism to balance the interests of all parties and build a competitive electricity market. Game theory has significant advantages in the study of decision optimization among multiple decision-making bodies that interact and compete with each other. Therefore, the application of game theory in the electricity system has attracted the attention and research of a large number of scholars, among which the research on the electricity market accounts for the highest proportion. In this study, the concept and evolution of cooperative game theory, non-cooperative game theory, and evolutionary game theory in game theory are described in detail. Second, the status quo and scale of the domestic and foreign electricity market are sorted out and summarized. Finally, according to the research results of the application of three kinds of game theory in the electricity market in recent years, this study evaluates and analyzes the three typical aspects of the power generation side, the power sale side, and the power consumption side, and puts forward the prospect of the application of game theory in the electricity market in the future.

Simulation of hydraulic power matching–based risk and economic evaluation among cascade hydropower stations in spot transactions

The electricity market is evolving rapidly from pre-bid to spot markets, where the transactions between producers and consumers have become crucial and are vulnerable to safety risks. In addition, the new modes of transaction are also becoming popular and are said to have some risks. To reveal the impact of the new electricity transaction mode—spot market—on the safety risk and generation benefit, this article presents a simulation method connecting the transaction results and operation process. To verify the effectiveness of the proposed method, an actual cascade hydropower station (CHS) in the Dadu River basin, Southwestern China, which comprises eight hydropower stations, is selected. Hydraulic power matching among the CHSs is discriminated from four aspects with multiple indicators combined with the reality of a hydropower-dominated market in Sichuan, China. The dispatching decision-making process of hydropower generators is described with a multi-objective optimization model and then solved with a fast search strategy based on the classical output calculation method in hydrology. The security risks and economic damage hidden in the day-ahead market on a certain day are discovered and analyzed. The technology proposed provides support for bidding decisions in spot transactions and satisfies the reality during the transition period of electricity reform.

Optimizing the Price of Electrical Energy Transactions on the Microgrid System Using the Shortest Path Solution

Microgrid networks that reduce greenhouse gas emissions have increased electrical energy. In electrical energy transactions, a strategy is needed to create the lowest electricity sales price optimization for consumers. Currently, optimizing the price of electricity transactions is a challenge because few still discuss offering the cheapest electricity prices. In the wheeling System Transaction (shared use of utility-owned electricity networks), optimizing the price of electrical energy transactions is still a challenge that must be resolved. This is because there is no algorithm developed to solve this problem. This research will develop an algorithm to optimize electricity price sales using the shortest path and Power Flow Tracing methods. Developing the shortest path algorithm can provide recommendations for each area that conducts electrical energy transactions. Then, electrical energy transactions are determined based on the lowest price, the most negligible loss, and the shortest distance to get the optimal price.

Research on Coupled Cooperative Operation of Medium- and Long-Term and Spot Electricity Transaction for Multi-Energy System: A Case Study in China

Due to the intermittent and anti-peak shaving characteristics of the new energy generator sets, the phenomenon of power abandonment hinders direct participation in the electricity market transactions. The hybrid electricity market can use spot market transactions to absorb renewable energy to a large extent. The multi-energy complementary operation coupling of the hybrid electricity market transactions can exploit the complementation and substitution between different energy sources, realize flexible energy production, consumption, storage, and transmission, and optimize the allocation of resources on a larger scale. In this paper, a mid-long-term spot transaction coordination scheduling (MTCS) model for a multi-energy system is constructed by considering the medium- and long-term electricity market uncertainty and the trial operation characteristics of the spot power market in China. A two-stage solution method is introduced to solve the complex multi-agent, multi-period, and multi-energy model. The results of testing this model on the Gansu region, one of the first eight spot pilot areas in China, are presented and discussed in detail. The results showed that this MTCS model could reduce the opening of thermal power units to a more considerable extent, prioritize the consumption of new energy power generation, and reduce the output uncertainty of new energy through the hybrid power market.

LLAKEP: A Low-Latency Authentication and Key Exchange Protocol for Energy Internet of Things in the Metaverse Era

The authenticated key exchange (AKE) protocol can ensure secure communication between a client and a server in the electricity transaction of the Energy Internet of things (EIoT). Park proposed a two-factor authentication protocol 2PAKEP, whose computational burden of authentication is evenly shared by both sides. However, the computing capability of the client device is weaker than that of the server. Therefore, based on 2PAKEP, we propose an authentication protocol that transfers computational tasks from the client to the server. The client has fewer computing tasks in this protocol than the server, and the overall latency will be greatly reduced. Furthermore, the security of the proposed protocol is analyzed by using the ROR model and GNY logic. We verify the low-latency advantage of the proposed protocol through various comparative experiments and use it for EIoT electricity transaction systems in a Metaverse scenario.

Hybrid Game Optimization of Microgrid Cluster (MC) Based on Service Provider (SP) and Tiered Carbon Price

Carbon trading is a market-based mechanism towards low-carbon electric power systems. A hy-brid game optimization model is established for deriving the optimal trading price between mi-crogrids (MGs) as well as providing the optimal pricing scheme for trading between the microgrid cluster(MC) and the upper-layer service provider (SP). At first, we propose a robust optimization model of microgrid clusters from the perspective of risk aversion, in which the uncertainty of wind and photovoltaic (PV) output is modeled with resort to the information gap decision theo-ry(IGDT). Finally, based on the Nash bargaining theory, the electric power transaction payment model between MGs is established, and the alternating direction multiplier method (ADMM) is used to solve it, thus effectively protecting the privacy of each subject. It shows that the proposed strategy is able to quantify the uncertainty of wind and PV factors on dispatching operations. At the same time, carbon emission could be effectively reduced by following the tiered carbon price scheme.

AN ANALYSIS OF THE CAUSALITY RELATIONSHIP BETWEEN BITCOIN ELECTRICITY CONSUMPTION, PRICE AND VOLUME

This study aims to analyze the causal relationship between electricity consumption, price and transaction volume of Bitcoin, which is the most important asset of the crypto money market in terms of both market capitalization and transaction volume. In this study, the Bitcoin electricity consumption variable is represented by Cambridge Bitcoin Electricity Consumption Index. As the data set, 1446 days of data between February 2017 and February 2021 were used. The causality relationship between the variables is analyzed using the Hatemi-J (2012) and Toda Yamamoto (1995) tests. In addition, this study is a rare study that examines the relationship between electricity and volume, together with the work done by Schinckus et al. (2020). According to the results of this study, the decrease in Bitcoin electricity consumption causes a decrease in the Bitcoin price. However, a negative relationship is detected Bitcoin electricity consumption and Bitcoin trade volume in this study, like the study by Schinckus et al. (2020), the relationship was found to be very weak.

Smart home energy management system applied for smart electric vehicle charging and energy transaction

Electric vehicles (EV), renewable generation sources and battery storage systems are important energy resources with great potential to impact the demand profile of electrical distribution networks. In this work, a new concept of residential electrical energy management system is presented, which in addition to managing the distributed energy resources present in the residence, also manages the EV charging, integrating three important concepts: mobile storage, V2G and energy transaction. For this, a management algorithm based on mixed integer linear program for real-time operation is developed. From the analyses carried out, the important contribution that the presented management concept can offer to the EV owner in relation to the profitability of its assets is observed. In addition, the presented approach has great potential to contribute to mitigating the negative impacts caused by the uncontrolled operation of the generation intermittent renewable energy and uncontrolled charging of the electric vehicle over the electrical distribution network.

Energy market optimization based on dynamic Pricing

With various social capital gradually into the electric power market, different virtual power plants will belong to different interest subjects in the future. The main development direction of China's energy market is to build a regional comprehensive energy market with multi-agent participation. Because the traditional power grid electricity price adopts monopoly transaction mode, the market enthusiasm is not high. In view of the situation, this paper proposes a two-level optimization model of master-slave game based on dynamic pricing. In order to encourage electric energy transactions between distribution network operators and multiple virtual power plants, distribution network operator solves the internal optimal electricity price according to the price response of virtual power plants in the optimization process. Simulation results show that the proposed strategy can promote energy sharing among integrated energy systems.

Research on emergency distribution optimization of mobile power for electric vehicle in photovoltaic-energy storage-charging supply chain under the energy blockchain

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.

Research on supporting mechanism of ancillary service of PV system to grid energy efficiency based on multi-time and space-time operation

Under the background of high-energy penetration of new energy into the power grid, this paper takes the ancillary service capability of photovoltaic energy integrated into the grid as the starting point and builds a photovoltaic system reactive power service impact evaluation model on the grid energy efficiency. This is based on the multi-temporal and spatial scale operation mode, in order to study the supporting principles of photovoltaic system reactive power services on the energy efficiency of grid operation and the law of influence on system energy efficiency changes. In this way, the space for power system energy efficiency improvement and the reactive power service market value of renewable energy are explored to improve the renewable energy auxiliary services participation in the theoretical system of electric power spot market transactions. The research conclusions can provide a decision-making reference for system dynamic energy efficiency management and can assist relevant market entities to make optimal decisions in spot market transactions, and provide empirical data for improving the theory of renewable energy participation in auxiliary service market transactions.

Evaluation of the Energy Transaction Cost for Microgrid-Based Wheeling System Using Power Flow Tracing: a Case Study

The increasing use of microgrid-based renewable energy has led to energy trading. One of the energy trades arising is based on the utility's transmission network (wheeling case). However, it is necessary to calculate the price of electric energy transactions for all the wheeling players to get the appropriate profit. This study has used a Power Flow Tracing algorithm modified according to the load conditions and the sun conditions all the time. It uses the Power Flow Tracing method by considering transmission, loss, and profit margins based on actual usage. On the other hand, the calculation of transaction costs of electrical energy uses the MW-Mile method by considering power quality in order to determine transmission costs and network losses. At the same time, the Full Cost Method is used to calculate the profit margin on the side of the microgrid owner. This research provides the results of tracking power flow according to the actual usage. The price calculation considers all the contributing players such as utilities, microgrids, and consumers. The research also shows that the transaction distance affects the transaction price.

Research on Multimicrogrid Transaction Model and Cross-Chain Transaction Mechanism Based on Blockchain

The traditional microgrid electricity transactions face a low security, poor economic benefits, and weak stability. To solve these problems, this paper proposes a multimicrogrid cross-chain transaction model based on quantum blockchain. Specifically, a bidding strategy was developed for the noncooperative dynamic game of aggregator-multimicrogrid alliance, aiming to balance and optimize the benefits of all parties and effectively enhance the consumption rate of electric energy. To improve the transaction efficiency between aggregators, a consensus mechanism was designed for multimicrogrid cross-chain communication, realizing consistent self-adaptation to cross-chain information. In addition, the quantum threshold signature technology was adopted to ensure the reliability of transaction data and create an unconditional secure communication environment. Case analysis shows that our model proposed in this paper not only ensures the security and stability of transactions but also enhances the economic benefits, providing theoretical support and decision support for the optimization of multimicronetwork cross-chain transaction model.

Blockchain‐based distributed electricity transaction model

Blockchain‐based distributed electricity transaction model

Stochastic-Weighted Robust Optimization Based Bilayer Operation of a Multi-Energy Building Microgrid Considering Practical Thermal Loads and Battery Degradation

This paper discusses a bilayer coordinated operation scheme for the multi-energy building microgrid (MEBM) with comprehensive uncertainty sources. First, a building model considering the battery degradation, practical/detailed thermal loads, and various operating tasks of residential appliances is presented. Second, to alleviate the adverse effects from diverse uncertainties of electricity demands, cooling water temperature, outdoor temperature, occupants’ metabolism as well as solar irradiance, a bilayer model is applied which makes full utilization of historical data and manages the solution conservativeness. The first layer is the stochastic-weighted robust optimization-based day-ahead operation. It determines the dispatch of heterogeneous energy storage assets, multi-energy demand response, and on-off status of combined cooling, heat and power (CCHP) plants on an hourly basis for the entire day. The second layer sequentially finalizes the operation of the power-to-thermal conversion unit, CCHP plant, and electricity transactions between the MEBM and utility grid hourly with uncertainty realizations. Numerical case studies demonstrate the effectiveness of the proposed approach in obtaining the economic MEBM operation with the high comput-ational performance and immunizing against uncertainties.

A privacy protection scheme for electricity transactions in the microgrid day-ahead market based on consortium blockchain

The electricity trading plan made by the users in the microgrid day-ahead market (DAM) contains the electricity consumption information of the future day. Aiming at the problem that the leakage of electricity consumption information threatens the privacy security of users and the leakage of electricity trading plan destroys the fairness of the DAM, a privacy protection scheme for electricity transactions in microgrid DAM based on consortium blockchain is proposed. Firstly, the scheme is based on the ElGamal algorithm that generates anonymous identities for users involved in transactions, preventing leakage of electricity consumption information and allowing the real identity of the fraudster to be traced in the event of fraudulent transactions. Secondly, a certificateless signcryption (CLS) algorithm is improved to realize the encryption and authentication of the user's electricity trading plan, which enhances the efficiency of the scheme. Finally, the scheme realizes decentralized trading of users in the microgrid in the DAM through the consortium blockchain and smart contracts, ensuring transaction security and improving transaction efficiency. The scheme is proved to have high security under different types of attacks by stochastic prediction machine model. Moreover, by calculating the computation time for different kinds of operations in the two stages of signcryption and unsigncryption, it is concluded that the computation cost of this scheme is lower than that of other schemes of the same type has higher efficiency.

Merit Evaluation of Peer‐to‐Peer Electricity Trading Between Prosumers

The enforcement of a feed‐in tariff (FIT) program in Japan has increased the number of installations of photovoltaic generation systems in its residential sector. After the end of an FIT program, the surplus electricity of an individual prosumer is purchased by the utility company at a reduced price, which may have an economic impact on the prosumer. To avoid this adverse effect, peer‐to‐peer (P2P) electricity transactions among prosumers based on blockchain and smart contract technologies as well as introduction of residence‐use stationary storage batteries are generating significant interest. In this study, the potential economic merit of P2P transactions and residential storage battery introduction are evaluated using a total optimization approach. For realizing a more practical perspective, this study also investigates the economic merit based on a partial optimization approach, in which an individual prosumer pursues its own profit. Furthermore, in this study, the grid‐side merit of P2P electricity transactions among prosumers is examined. Comparison of the merits determined by the total and partial optimization approaches shows that the realization of P2P transactions could provide a notable economic merit to the participants and reduce both the required facility capacity and power flow variation. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Guest Editorial: Enhancing hosting capability for renewable energy generation in active distribution networks

Guest Editorial: Enhancing hosting capability for renewable energy generation in active distribution networks

A Review of Bayesian Networks Applications for Electrical Systems

Abstract: The development in the field of electrical energy has been growing increasingly due to the need for this energy in daily life. The reliability and safety of electrical power systems and equipment represent complex problems that are difficult to solve by conventional methods such as Fuzzy Logic and Artificial Neural Networks. Bayesian network is recently used to overcome some limitations in conventional methods. This paper represents a bibliographic review about the use of Bayesian networks in the field of electric systems. This paper seeks to answer the following questions: (i) What are the areas of interest? (ii) What are the most active countries in this field?? (iii) Who are the most participating authors in this field? (iv) which year witnessed the largest number of publications? (v) What is the most widespread field related to this research? (vi) What is the most used system in terms of application? This field witnesses a slight increase in the number of publications in the last two decades (1999–2021), with a note of a sharp increase in publishing in the last two years. It is observed that reliability assessment and fault diagnosis are the most common fields. Furthermore, it is found that China and USA are the active countries in this field. Electric Power and Energy Systems Journal and IEEE Transactions on Power Systems Journal are the lead source documents, and most of the documents used electric power systems as an application. This paper will help researchers to know the versability features of BN and to identify the gaps in the use of BN in electric domains.