With the development of renewable energy sources, single-ended transient-based boundary protection, unaffected by the characteristics of electronic devices, has regained public attention. However, some issues remain: 1) due to the elimination of line traps, the line boundary characteristics relying solely on the bus stray capacitance are unclear; 2) conventional boundary protection has insufficient sensitivity to fault type, fault inception angle, fault resistance, and number of transmission lines; and 3) the internal faults and the remote bus faults cannot be reliably distinguished. Therefore, this paper presents a novel boundary protection scheme for a 220 kV transmission system. First, the transient model of the bus system is established, confirming that the line boundary without line traps still has a remarkable attenuating effect on high-frequency transients. Then, based on the Teager energy operator, a novel protection criterion with sufficient sensitivity is constructed by utilizing the high- to low-frequency instantaneous energy ratio of fault-generated traveling waves (TWs). Furthermore, remedial reclosing measures without the communication channel are proposed to address remote bus faults effectively. Finally, based on PSCAD software, the excellent performance of the proposed approach is verified in a renewable power system.

When many distributed generators (DGs) are connected to active distribution networks (ADNs), the performance of conventional overcurrent protection can seriously deteriorate. In response, single-ended transient-based boundary protection is considered an effective scheme for improving relay performance in ADNs due to its independence from power supply properties and its ability to cover an entire protected feeder. However, this approach depends on the filtering effect of the line boundary. This paper finds that capacitive voltage transformers (CVTs), metal-oxide arresters (MOAs), and the stray capacitances of the other apparatuses can serve together as line boundaries at substations and switching stations, and their excellent high-frequency filtering characteristics can assist in boundary protection design. A protection criterion is constructed based on the differences in high-frequency spectral energy between the internal and external fault-generated traveling waves (TWs). Furthermore, a novel two-stage boundary protection scheme is formed by reasonably coordinating the operation sequence and the protection scope of the first- and second-stage boundary protection. Finally, based on the PSCAD platform, the effectiveness, sensitivity, and reliability of the proposed protection scheme are verified under different fault scenarios.

Wave energy generator (WEG) is a new renewable energy source with prominent advantages and disadvantages. Theoretically, it can move around the sea to harvest wave energy better and will not take up valuable land resources. Normally, WEG collects tiny wave energy continuously and generates electricity intermittently on the minute time-scale to enhance energy harvesting efficiency. Thus, the output of WEG shows prominent impulsive characteristics, which needs to be compensated by the battery energy storage system (BESS) and therefore brings about significant battery life losses. For the purpose of stable and economic operation of the weak power grid connected by WEG, a flexible control method enabling a quantifiable tradeoff between its energy harvesting efficiency and impulsive characteristics is proposed. Then, a novel source-storage coordination strategy and the corresponding energy exchange model of WEG with several optimizable control parameters is formulated to depict the energy flow within the microgrid. Subsequently, an optimization algorithm is proposed to schedule the WEG’s mobile route and optimizable control parameters simultaneously. Simulation results show that the proposed source-storage strategy and the energy management scheme can balance WEG’s energy harvesting and impulsive impact, and utilize its mobility to improve the isolated island microgrid’s operation economy and power quality.

With computing demand continuously increasing, data centers in extreme-climate regions typified by the Middle East and North Africa (MENA) face challenges including persistently high cooling energy consumption and a temporal mismatch between computing-driven cooling demand and the availability of natural cooling resources. Considering the regional climatic characteristics of high daytime temperatures and large diurnal temperature swings, a novel thermal management structure integrating phase-change materials (PCM), cooling towers, and heat pumps is proposed. By leveraging the thermal buffering capability of PCM together with the cooling tower’s nighttime natural cooling potential, peak shaving and valley filling for cooling is achieved, which alleviates the temporal mismatch between computing-driven cooling demand and availability of natural cooling resources and increases the natural cooling resources utilization. Furthermore, to coordinate the coupled interactions among transferable computing workloads, electricity pricing, and natural cooling resources in the novel structure, a “computing-electrical-thermal” coordinated optimization model is proposed to reduce electricity cost and optimize the allocation of cooling resources. Since the proposed coordinated optimization model features strong variable coupling and nonlinear characteristics, which cause parameter-propagation delays when conventional hierarchical solution methods are applied, a global solution algorithm is proposed to jointly optimize key variables, including cooling tower power, heat-pump power, and computing workloads migration. Considering a certain data center as a case study, compared with a conventional air–liquid cooling system, electricity consumption is reduced by 17% and the daily operating cost is decreased by USD 2,075 by using the novel thermal management structure. In addition, compared with a conventional electrical–thermal coordination model, the daily operating cost is decreased by USD 556 by using the “computing–electrical–thermal” coordinated optimization model”.