With the increasing consumption of energy, it is of high significance to improve energy efficiency and realize optimal operation of the multi-energy system. Among the many energy system modeling methods, the concept of "energy hub (EH)" is an emerging one. However, the previous EH models only included one or a few of constituting components. The construction of an energy hub model that integrates energy storage systems, photovoltaic (PV) components, a combined cooling heating and power (CCHP) system and electric vehicles (EVs) is explained in this thesis. The inclusion of the CCHP system helps to meet the energy demand and improve the mismatch of heat-to-electric ratio between the energy hub and the load. Additionally, vehicle-to-grid (V2G) technology is applied in this EH; that is, EVs are regarded not only as load demands but also as power suppliers. The energy hub optimization scheduling problem is formulated as a multi-period stochastic problem with the minimum total energy cost as the objective. Compared to 24-hour day-ahead scheduling, rolling horizon optimization is used in the EH scheduling and shows its superiority. In iii real-time rolling horizon scheduling, the optimization principle ensured that the result is optimized each moment, so it avoids energy waste caused by overbuying energy. As part of electricity loads, EVs have certain influence on energy hub scheduling. However, due to the randomness of the driving patterns, it is still very difficult to perfectly predict the driving consumption and the charging availability of the EVs one day in advance. Chance constrained programming can hedge the risk of uncertainty for a big probability and drop the extreme case with a very low probability. By restricting the probability of chance constraints over a specific level, the influence of the uncertainty of electric vehicle charging behavior on energy hub scheduling can be reduced. Simulation results show that the energy hub optimization scheduling with chance constrained programming results in a less energy cost and it can make better use of time-varying PV energy as well as the peak-to-valley electricity price.

The first ±500 kV voltage source converter based high voltage direct current (VSC‐HVDC) grid in the world is being built in China. The half‐bridge submodule‐based modular multilevel converter (MMC), the direct current (DC) circuit breaker (DCCB), and the overhead line are used in the project. Switching overvoltage will occur after the DCCB turns off the short circuit current (SCC) in the VSC‐HVDC grid. The existing average value models (AVMs) of MMC still have some limitations in simulating such a kind of overvoltage. The main reason is that these AVMs cannot accurately simulate the working states of MMC in the VSC‐HVDC grid with DCCB. This article summarizes the possible cases of the action strategies between the DCCB and MMC in the VSC‐HVDC grid. Then, the working states of MMC in the different cases are analyzed. Corresponding to different working states, the limitations of existing AVMs are analyzed. The existing AVMs cannot simulate the alternating current or DC components in the arm current before being blocked and the charging process of the submodule capacitor after being blocked. An enhanced AVM is proposed in this article, which can fully simulate the MMC's working states. Simulation results show that the accuracy of the proposed AVM is highly improved over the existing AVMs. Meanwhile, the simulation efficiency of the proposed model is improved over the detailed equivalent model that is highly accurate but relatively low efficient for VSC‐HVDC grid simulations. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

For China, one of its most important commitments is to realize its "3060" targets of achieving a CO 2 emission peak by 2030 and carbon neutrality by 2060. However, for a developing country with heavy carbon utilization, achieving carbon neutrality in a short period necessitates tough changes. This paper briefly introduces energy and electricity scenarios and analyzes the challenges based on the current power system in China. Moreover, it summarizes the six characteristics of China's future power grid and highlights some partially representative projects in the country.

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