To cope with the energy crisis and environmental pollution, the future development of the power system has to change towards a clean, low-carbon, flexible, and diversified direction. This paper proposes a decentralized power dispatching model based on blockchain technology to address the problems of uncertainty, privacy, security, and reliability in power dispatching systems containing renewable energy and flexible loads. Considering the uncertainty of wind, photovoltaic, and flexible load integration into the power grid, the total generation costs of the system are established, and the smart contracts of the decentralized power dispatching are proposed. The proof of work (PoW) consensus mechanism is improved in this paper. The hash operation that must be repeated in the PoW algorithm is replaced by an optimized computation process using a blockchain-based genetic algorithm (BD-GA). The proof of work-load-genetic algorithm-based (PoW-GAD) consensus algorithm is proposed. The decentralized power dispatching model and improved consensus algorithms’ effectiveness was confirmed by simulation. The power dispatching method in this paper reduces the system cost and increases wind and photovoltaic usage. The improved PoW-GAD algorithm, while inheriting the security features of the PoW algorithm, adapts to the blockchain-based decentralized dispatching structure and enhances system security.

In China, a structure in which multiple line-commutated converter based high-voltage direct current (LCC-HVDC) systems feed into the same AC system has been formed. For the multiple LCC-HVDC infeed system, the electrical strength and real operating condition evaluation of the receiving AC system are of great significance for system operation. The multi-infeed short circuit ratio (MISCR) is generally utilized to assess the strength based on the rated parameters; hence, it cannot analyze the real operating condition under the non-rated status. In this paper, an LCC-HVDC system is equivalent to a grounded impedance without changing the external characteristics. The multi-infeed operating short circuit ratio (MIOSCR) is then deduced from the equivalent impedance and equivalent nodal analysis. Relationships between the MIOSCR and electrical strength indices of AC and AC/DC systems are analyzed, and the MISCR is deduced as a special case of the MIOSCR under the rated status. The multi-infeed operating margin coefficient (MIOMC) is finally proposed, which can be utilized to evaluate the operating margin of the LCC-HVDC system and provide guidance for designing operating strategies. The proposed MIOSCR and MIOMC overcome the previous shortcomings of inaccuracy about operating status assessment by the MISCR. The results of the case study demonstrate the effectiveness of the MIOSCR and the MIOMC for assessing the operating condition and margin of converter buses.

Since there is a longitudinal and horizontal penetration problem between multi-level data centers in the smart grid information transmission network. Based on the improved Simulated Annealing algorithm, this paper proposes a data storage optimization model for smart grids based on Hadoop architecture. Combining the characteristics of distributed storage in cloud computing, the smart grid data are equivalent to a task-oriented data set. The smart grid information platform is flattened, equal to a collection of multiple distributed data centers. The smart grid data over time were counted to derive the dependencies between task sets and data sets. According to the dependency between task sets and data sets, the mathematical model was established in combination with the actual data transmission of the power grid. The optimal transmission correspondence between each data set and the data center was calculated. An improved Simulated Annealing algorithm solves the longitudinal and horizontal penetration problem between multi-level data centers. When generating a new solution, the Grey Wolf algorithm provides direction for finding the optimal solution. This paper integrated the existing business data and computational storage resources in the smart grid to establish a mathematical model of the affiliation between data centers and data sets. The optimal distribution of the data set was calculated, and the optimally distributed data set was stored in a distributed physical disk. Arithmetic examples were used to analyze the efficiency and stability of several algorithms to verify the improved algorithm’s advantages, and the improved algorithms’ effectiveness was confirmed by simulation.

Green and low-carbon transformation has become a global development theme. This paper provides a systematic survey of the literature related to key technologies for green and low-carbon future buildings, including the green design method system of low-carbon future buildings; the low-carbon future buildings construction system and green building materials; the low-carbon future buildings energy system; the low-carbon intelligent operation of buildings and carbon emission control in the operation stage; and the low-carbon future buildings assessment system. This paper analyzes and summarizes the whole chain of “carbon monitoring-carbon accounting-carbon assessment-carbon control” of the whole life cycle of buildings. We systematically surveyed the development overview and the latest development trend of scientific and technological innovation; the existing starting level of science and technology; and the existing intellectual property, competition, and industrialization prospects in each stage of the whole life cycle. We conducted an overall analysis of the characteristics, thematic context, and knowledge evolution of low-carbon future building-related research, both domestically and internationally; referring to the relevant standards and specifications for new types of buildings, such as green buildings, a preliminary theoretical framework for low-carbon future buildings is constructed from the perspective of the entire life cycle.

AC–DC power-flow calculation is the basis for studying HVDC systems. Since traditional iterative methods need many alternative iterations and have convergence problems, this paper proposes an alternating iterative power-flow algorithm for hybrid AC–DC power grids incorporating line-commutated converters (LCCs) and voltage source converters (VSCs). Firstly, the algorithm incorporates the converter interface model into the AC side, considering the influence of the DC side on the AC side, and establishes an AC-augmented Jacobian matrix model with LCC/VSC interface equation variables. Then, according to the type of converter, control mode, and DC grid control strategy, a DC grid power-flow calculation model under various control modes is established for realizing the power-flow decoupling calculation of AC–DC power grids incorporating LCCs and VSCs. The accuracy and effectiveness of the improved algorithm are evaluated using modified IEEE 57 bus AC–DC networks and the CIGRE B4 DC grid test system. The improved algorithm is applicable to various DC grid control modes and considers the reasonable adjustment of the DC grid variable constraints and operating modes.