Introduction of variable renewable energy systems (VRE), such as solar and wind power, into power systems is growing rapidly around the world. While this growth provides a step towards more sustainable societies, it also brings challenges. One important challenge regards the VREs output weather-related variability. If deployed in large scale, such variability can cause issues in the balancing of power demand and supply. To deal with this challenge on the power system side, one possibility is to increase the system's flexibility, which means the capability to deal with potential mismatches between VRE and demand. For example, conventional power generators could be operated in such a way to compensate partially for the VREs output variability. On the VRE side, forecasting, curtailment, and battery-coupled operation are often considered. Regardless of the measures employed, they typically require tackling complex problems using massive databases, and modeling natural phenomena, such as the weather. Such problems are particularly fit for machine learning (ML) techniques, and they have been the front-runner in research and applications related with the integration of VREs to power systems. In this report, we introduce examples of the latest ML techniques, and the most recent trends regarding their applications in VREs.

Electric power system is one of the most important infrastructures and regular maintenance works (inspection, repair, replacement and so on) are very important tasks for transmission system operators (TSO). The maintenance work with partial outage is referred to as outage work” and the authors have so far studied a highly reliable outage work planning system for large scale power grids. In these days, however, a huge number of photovoltaic (PV) generation systems are being installed into the power grids. PV outputs are strongly affected by weather conditions and very difficult to be anticipated in advance. In addition, it is getting difficult for TSOs to grasp operation patterns of even traditional large-scale power sources due to the deregulation in the electricity industry. The planning task of annual outage work program is also getting difficult. The authors, therefore, believe that it is necessary to consider suitable supply-demand conditions for obtaining reliable grid configurations during outage works even in the uncertain circumstances. In this paper, the authors investigate what kind of conditions should be assumed for outage work planning and propose a deriving method to obtain appropriate grid configurations during outage works. The effectiveness of the proposed method is verified through several numerical simulations.

This paper proposes the application of an adjustable speed diesel engine-driven power plant employing a doubly-fed induction generator to an isolated small-scale power system including renewable power sources. This type of power plant can contribute to fast and flexible power balancing regulation under vacillating power supply such as wind, solar and other renewable power sources. Installation of a battery system is also considered, which can assist coordinately with the power plant to augment renewable power sources in the isolated power system.

Recently, the technology of controlling the demand-side reactive power to stabilize a power distribution system has been attracting attention. Since building multi-type air-conditioners are widely installed in office buildings, they have the potential to participate in distribution system stabilization if they can fulfill the request of the reactive power demand response. This paper proposes a new approach of reactive power demand response using building multi-type air-conditioners in a cluster of neighboring office buildings near the feeder location where a voltage deviation problem has occurred. We define a set of operation modes for the active converter built-in each air-conditioner to inject/absorb the reactive power. Next, we propose a new method of reactive power allocation to each air-conditioner taking into account each air-conditioning load and comfort. An integrated simulator has been developed combining our model of air-conditioner's transient behaviors and a model of the standard urban distribution system. The simulation result has shown, for example, a neighboring cluster of 25 air-conditioners in 5 office buildings continued the aggregated reactive power injection of approximately 400kvar for 10 minutes while maintaining room-temperatures within the comfort range.

We made a DC switch, which is composed of the commercial power relay and Si-IGBT. They are connected in parallel, and we controlled the timing of the relay metal contact switch and the IGBT ON/OFF timing. The operation principle is that the relay switch is open when the IGBT is ON. Then, the relay current flowed into the IGBT, and its commutation time is ∼0.25µ s. Finally, the current is interrupted by the IGBT. Therefore, we realized the non-arc operation. We also used the flywheel diode to avoid the surge voltage induced when we interrupted the direct current of the inductor by the IGBT. We tested its performance under the voltage and current of DC400V and 1A to 10A. We also tested multiple operations, up to 20,000 times, and had no failure of the non-arc operation completely. After the 20,000 times operations, we observed the surface of the metal contacts by scanning electron microscopy (SEM) and optical microscopy. The arc mark is observed clearly on the positive contact because the arc is not induced perfectly. But the arc mark on the negative contact is unclear. The rely resistance is almost the same as the new contact's after 20,000 times operation. This principle will be effective for high voltage and large current switches.