The need to improve power system performance, enhance reliability, and reduce environmental effects, as well as advances in communication infrastructures, have led to demand response (DR) becoming an essential part of smart grid operation. DR can provide power system operators with a range of flexible resources through different schemes. From the operational decision-making viewpoint, in practice, each scheme can affect the system performance differently. Therefore, categorizing different DR schemes based on their potential impacts on the power grid, operational targets, and economic incentives can embed a pragmatic and practical perspective into the selection approach. In order to provide such insights, this paper presents an extensive review of DR programs. A goal-oriented classification based on the type of market, reliability, power flexibility and the participants' economic motivation is proposed for DR programs. The benefits and barriers based on new classes are presented. Every involved party, including the power system operator and participants, can utilize the proposed classification to select an appropriate plan in the DR-related ancillary service ecosystem. The various enabling technologies and practical strategies for the application of DR schemes in various sectors are reviewed. Following this, changes in the procedure of DR schemes in the smart community concept are studied. Finally, the direction of future research and development in DR is discussed and analyzed.

Today, the pace of development of decentralized transactive management systems has increased significantly due to growing renewable energy source technologies and communication infrastructure at the distribution system level. Such bilateral energy transactions have changed the structure of electricity markets and led to the emergence of a local energy market in electricity distribution. While examining this change of attitude, this paper analyzes the effects of local market formation on the performance and performance of distribution companies. Accordingly, the technical requirements in the three areas of operation, network control, and ICT in the new workspace are thoroughly examined. The hardware requirements will be presented in two parts for the end-user and the distribution systems. Then, the proposed local distribution market framework will be introduced, and finally, the conclusion will be presented.

Today, the development of decentralized energy management systems has accelerated due to the daily growth of renewable energy technologies and communications infrastructure. At the distribution system level, this approach has manifested itself with the emergence of the local energy market. In fact, the local energy market is becoming a new operating model to control local generation units. This paper describes the general architecture and elements used to implement a blockchain-based local energy market within a transactive management platform. After an overview of internet of things (IoT) communication technologies and the existing central-authority-based applications, the general structure and elements of peer-to-peer (P2P) networks are reviewed. Next, the concepts of blockchain-based technologies and the required specifications for different building layers are outlined based on the limited relevant literature available. The concepts and requirements are investigated to provide practical insights to design trading platforms.

This paper presents a new stochastic optimization approach for parameter tuning of conventional power system stabilizer (PSS). Quantum-behaved particle swarm optimization (QPSO) technique is suggested in this paper to search for optimal settings of PSS parameters. An eigenvalue-based objective function to enhance system damping of electromechanical modes is considered. The performance of the proposed PSS is investigated under different disturbances and loading conditions for a single machine infinite bus (SMIB) system. The effectiveness of the proposed PSS is demonstrated through nonlinear time-domain simulation and two performance indices. The results analysis reveals that the designed QPSO based PSS has an excellent capability in damping power system oscillations in comparison with designed classical particle swarm optimization (CPSO) based PSS and enhance greatly the dynamic stability of the power systems.