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The security and economy of multienergy systems (MESs) are directly threatened by the potential cyberattacks. It is of great importance to investigate the effects of cyberattacks, e.g., denial of service (DoS) attacks, on distributed energy management algorithms. To this end, this article focuses on exploring how the frequency and the time of duration of DoS attacks influence the behavior of Newton–Raphson-based distributed energy management (NRBDEM) algorithm for MES and in which condition the optimal operations can still be obtained. First, a switched NRBDEM algorithm is presented, which is composed of the normal operation mode and the attack mode. In the attack mode, the attackers are able to change the communication structure at will and make it unconnected to destroy the convergence of the switched NRBDEM algorithm. Then, by making use of automatons to generate the hybrid time domain, the switched NRBDEM algorithm is further modeled and formulated as a hybrid dynamical system, which provides a mathematical model for the subsequent convergence analysis. Therein, the generated hybrid time domain satisfies the average dwell-time constraint and time-ratio constraint to limit the persistent attacks. Furthermore, we analyze the restrained conditions for persistent attacks, under which the optimality and convergence of the switched NRBDEM algorithm can be guaranteed still. Finally, simulation results demonstrate the effectiveness of the proposed method. Note to Practitioners—The multienergy system (MES) is viewed as a typical cyber-physical system. Since it works in a networked environment, the convergence and optimality of the corresponding distributed energy management algorithms are easily destroyed by various cyberattacks, such as the DoS attack. Few noticeable studies have been documented to investigate the distributed energy management problem for MES under persistent DoS attacks. To address this issue, this article proposes a switched NRBDEM algorithm subject to persistent DoS attacks, which is made up of normal operation mode and attack mode. Moreover, sufficient conditions are derived for the tolerable frequency of attack and the time of duration. It is helpful for the practitioners to know in which conditions the global convergence and optimality can be maintained still. Several simulations are provided to verify the correctness of the proposed theoretical analysis results. Our future work will aim at analyzing the performance of different energy management algorithms under different cyberattacks. [ABSTRACT FROM AUTHOR]

Distributed algorithms are increasingly being used to solve the economic dispatch problem of integrated energy systems (IESs) because of their high flexibility and strong robustness, but those algorithms also bring more risk of cyber-attacks in IESs. To solve this problem, this article investigates the distributed robust economic dispatch problem of IESs under cyber-attacks. First, as the first line of defense against attacks, a privacy-preserving protocol is designed for covering up some vital information used for economic dispatch of IESs. On this basis, a distributed robust economic dispatch strategy is presented to achieve the energy management of IESs in the presence of misbehaving units, which consists of a neighbor-observe-based detection process and a reputation-based isolation process. The proposed strategy is implemented in a fully distributed fashion and possesses strong robustness against various colluding and noncolluding attacks. In addition, the strategy can not only ensure the reliability of information transmission among energy units, but also solve the problem of incorrect measurement of distributed local load data caused by cyber-attacks. Finally, the effectiveness of the proposed strategy is illustrated by simulation cases on a 39-bus 32-node power–heat IES. [ABSTRACT FROM AUTHOR]

This paper investigates the residential energy management problems in the power-heat-coupling system. For better solving this issue, based on the novel concept of We-Energy (WE) for energy Internet (EI), this paper proposes a residential WE (R-WE) framework faced by the terminal users who play an important role in renewable energy consumption. Inspired by the full-duplex feature of R-WE, the power and heat supply-demand balance constraints are fulfilled in a regional unit of EI, but it may be inequality constraints for corresponding consumer, producer, or WE operation modes in only one R-WE. The R-WE framework can be classified into four operation modes, which is island mode, consumer mode, producer mode, and WE mode. On this basis, the R-WE models cooperate to achieve the objective of minimizing the operation costs, smoothing out the loads’ variations, and renewable resource fluctuations. Specifically, the R-WE framework with respect to the heat-power-coupling problem can be solved in the distributed double-consensus algorithm (DDCA), which is designed two sets of consensus algorithms by using four completely different consensus variables to calculate the power and heat multipliers, evaluate the power and heat generations and, thereby, further obtain the power mismatches of electricity and heat. Also, the Karush-Kuhn-Tucker (KKT) optimal conditions of the proposed DDCA is further proved. Meanwhile, a novel projection operation method for combined heat and power devices is designed to take the infeasible solutions mapped into the feasible region. Finally, the simulation results in different cases further demonstrate that the proposed R-WE frame can be an appropriate method to analyze the terminal consumers and harmonize multienergy producers in the process of constructing EI projects. And an R-WE framework of the campus has experimented with minority loads in island mode. [ABSTRACT FROM AUTHOR]

This paper investigates the issues of day-ahead and real-time cooperative energy management for multienergy systems formed by many energy bodies. To address these issues, we propose an event-triggered-based distributed algorithm with some desirable features, namely, distributed execution, asynchronous communication, and independent calculation. First, the energy body, seen as both energy supplier and customer, is introduced for system model development. On this basis, energy bodies cooperate with each other to achieve the objective of maximizing the day-ahead social welfare and smoothing out the real-time loads variations as well as renewable resource fluctuations with the consideration of different timescale characteristics between electricity and heat power. To this end, the day-ahead and real-time energy management models are established and formulated as a class of distributed coupled optimization problem by felicitously converting some system coordinates. Such problems can be effectively solved by implementing the proposed algorithm. With the effort, each energy body can determine its owing optimal operations through only local communication and computation, resulting in enhanced system reliability, scalability, and privacy. Meanwhile, the designed communication strategy is event-triggered, which can dramatically reduce the communication among energy bodies. Simulations are provided to illustrate the effectiveness of the proposed models and algorithm. [ABSTRACT FROM AUTHOR]