Solar power and wind power forecast include prediction uncertainty. Recently, the Japan Meteorological Agency (JMA) developed meso-ensemble prediction system (MEPS) and has been operated the MEPS since June 2019. MEPS provides various scenarios (uncertainty) for weather forecasts. This paper explains an ensemble forecast and describe the future use of the MEPS data in an energy management system with the renewable energy fields (e.g., solar power and wind power).
Power generation of variable renewable energy depends on the weather and therefore has uncertainty. In this paper, we utilize the ensemble prediction to address the uncertainty of solar photovoltaics (PV) power and wind turbine (WT) power. Forecasted scenarios that obtained by ensemble prediction are applied to stochastic unit commitment (SUC). The SUC model is formulated to minimize sum of startup costs and expected fuel costs, allowing multiple forecasts such as ensemble prediction to be considered. Following the UC, economic dispatch control (EDC) using observed PV output and WT output is calculated and operation cost is analyzed. We also consider a model utilizing ensemble prediction to determine water reserve rate of pumped hydro. Finally, we evaluated these models from the viewpoints of economic efficiency and found that SUC models are more reasonable compared to other deterministic models.
There are studies which assume that the bid price is same as the generator's marginal operation cost in the kWh market. However, it cannot be same because of the market participants' bidding strategy to increase their profit. In this study, the marginal cost price is calculated according to the merit order curve, and this paper discusses the difference between the marginal cost price and the JEPX clearing price. In the calculation of the marginal cost price, the thermal power plant's marginal cost is estimated by the open-source information. The market splitting, which is caused by the interconnected tie line's capacity's constraint, is also considered. The marginal cost price is calculated from financial year 2017 to 2019, and the comparison with the JEPX clearing price is analyzed.
This paper proposes the model reduction method for smart inverters having Frequency-Watt control. The proposed reduction method consists of the following three steps: (1) derive the mathematical model of the smart inverter connected to low-voltage feeder, (2) combine the smart inverter mathematical model developed in (1) with the mathematical models for upstream electric circuits consisting of series impedances, line impedances, and transformers, and (3) aggregate the combined models found in (2) using the Padé approximation method or the Routh approximation, which can derive the aggregate transfer functions for the system with different poles. The proposed reduction method is also designed with the current limit of smart inverters. The proposed model reduction method can generate an equivalent aggregated dynamic model for smart inverters, seen from the distribution substation. The validity of the proposed reduction method is ascertained through computational simulation on the Matlab/Simulink environment.
It is possible that the mixture of single walled carbon nanotubes (SWCNTs) with high crystallinity and narrow diameter improve the catalyst layer performance of polymer electrolyte fuel cells (PEFC). In this study, Pt-based catalysts mixed with SWCNTs are prepared as the electrocatalysts for PEFC. The electrochemical properties of the catalyst layer mixed with SWCNTs were investigated by cyclic voltammetry (CV) under difference scanning conditions. The catalyst layers with SWCNTs showed significantly high electrochemical surface area (ECSA) under the high scanning rate on CV compared with the catalyst layer without SWCNTs. It was found that SWCNTs in the catalyst layer had a bundle structure and the bundles increased gaps between carbon supports used for Pt-based catalysts. SWCNT bundles contributed as conductive paths inside of the catalyst layers and improved porous structures in the catalyst layers. The improvement of the porous structures increased Pt nanoparticles functioned as the catalyst. Therefore, the mixture of SWCNTs leaded to improve the catalyst layer performance.
The R&D Steering Committee is working in planning and Steering of the Research and development of Power and Energy Society. In this article, activities of the committee of the last term are reported, and recent trend and future problems are also discussed. The process of planning and steering of the research and development, and the challenges to activation of Power and Energy Society are shown.