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The transactive energy market (TEM) is a recent development in energy management that enables prosumers to trade directly, promising many environmental and economic benefits. Prosumer trading necessitates sharing information to facilitate transactions. Additionally, many TEMs propose using blockchains to manage auctions and store transactions. These facts introduce privacy concerns: consumption data, trading history, and other identifying information pose risks to users if leaked. Anonymity by trading under a pseudonym is commonly presented as a solution; however, this creates risks for market participants: scammed users will not have recourse, and users with innocent malfunctions may be banned from trading. We propose the Individually Linkable Pseudonymous Trading Scheme (ILPTS), which enables users to trade under a pseudonym, protecting their identity, while a smart contract monitors reputations and can temporarily deanonymize a user, ensuring market integrity. ILPTS was developed in stages. Examination of existing TEM literature was performed to identify desirable features. Analysis of cryptography literature was performed to identify techniques that may confer certain features. It was found through formal analysis that ILPTS adheres to identified design goals, improves upon existing solutions, and resists common attacks against TEMs. Future work includes software simulation and on-device implementation to further verify security and feasibility. [ABSTRACT FROM AUTHOR]

Advances in energy generation and distribution technology have created the need for new power management paradigms. Transactive energy markets are integrated software and hardware systems that enable optimized energy management and direct trading between prosumers. This literature review covers unresolved security and privacy vulnerabilities in the proposed implementations of such markets. We first performed a coarse search for such implementations. We then combed the resulting literature for references to privacy concerns, security vulnerabilities, and attacks that their system was either vulnerable to or sought to address. We did so with a particular focus on threats that were not mitigated by the use of blockchain technology, a commonly employed solution. Based on evidence from 28 peer-reviewed papers, we synthesized 14 categories of concerns and their proposed solutions. We found that there are some concerns that have been widely addressed, such as protecting trading history when using a public blockchain. Conversely, there were serious threats that are not sufficiently being considered. While a lack of real-world deployment has limited information about which attacks are most likely or feasible, there are clear areas of priority that we recommend to address going forward, including market attacks, false data injection attacks, single points of failure, energy usage data leakage, and privacy. [ABSTRACT FROM AUTHOR]

In this paper, a detailed mathematical optimization model of electrolyzer/fuel cell technology connected to the grid through limited rating converters is developed. The model is so defined that it can tackle voltage fluctuation and meet the power ramp rate limitations inflicted by integration of constant-speed wind turbines at the Point of Common Coupling. The flicker mitigation and power ramp rate control problem in the presence of wind generation and variable electrical loads is defined as a nonlinear constrained optimization problem, in which voltage fluctuation is minimized as the objective function and the power ramp rate limitations are respected by the defined real-time ramp rate constraint. The problem is solved using the sequential quadratic programming method, which is a fast solver, by adjusting suitable initial points to be appropriate for real-time applications. The simulation results validate the efficiency of the proposed method and show dramatic improvement in flicker mitigation, power ramp rate control, and system rating reduction in comparison with the proportional–integral control method that was developed in previous studies. [ABSTRACT FROM AUTHOR]

In this study, an effective energy management system (EMS) for application in integrated building and microgrid system is introduced and implemented as a multi‐objective optimisation problem. The proposed architecture covers different key modelling aspects such as distributed heat and electricity generation characteristics, heat transfer and thermal dynamics of sustainable residential buildings and load scheduling potentials of household appliances with associated constraints. Through various simulation studies under different working scenarios with real data, different system constraints and user's objectives, the effectiveness and applicability of the proposed model are studied and validated compared with the existing residential EMSs. The simulation results demonstrate that the proposed EMS has the capability not only to conserve energy in sustainable homes and microgrid system and to reduce energy consumption costs accordingly, but also to satisfy user's comfort level through optimal scheduling and operation management of both demand and supply sides. [ABSTRACT FROM AUTHOR]