KEYWORDS: Algorithm development, Design, Analog electronics, Tunable filters, Windows, Telecommunications, Interpolation, Detection and tracking algorithms, Analog to digital converters, Electronic filtering
With the rapid construction of a new power system with new energy as the main body, aiming at the problems of high voltage fluctuation intensity and randomness caused by new energy access to the grid, this paper proposes an electric energy measurement method for new energy access by optimizing hardware and software based on high-precision analog signal sampling and measurement algorithm design. The hardware scheme of the measurement module is constructed by using the optimal design of zero-flux current transformer, sampling resistor and high precision ADC chip. In order to improve the synchronization of current and voltage signals and the accuracy of power measurement, a strategy of compensating the phase deviation of current and voltage is proposed. Finally, different experimental conditions are set to verify the effectiveness of the proposed method. The results show that the proposed method achieves high measurement accuracy, which is better than the technical requirement of 0.2S of active power accuracy.
KEYWORDS: Solar energy, Data modeling, System integration, Reliability, Mathematical optimization, Power consumption, Atmospheric modeling, Education and training, Power grids, Wind energy
The multiple loads of the integrated energy system have the characteristics of complex coupling, strong volatility, and strong randomness, and accurate prediction is the foundation and guarantee for optimizing the scheduling of the integrated energy system. An integrated energy system scheduling method based on SSA-BI-GRU multivariate load forecasting is proposed. Firstly, in order to explore the relationships between data more fully, the SSA-BI-GRU algorithm is proposed. Random forest regression model and cross-telecommunication validation are introduced into the data processing module. Then, we construct an integrated energy system optimization scheduling model to incorporate system reliability into the objective function. Finally, the load prediction results of the SSA-BI-GRU model are used as input to solve the IES scheduling problem using the improved MOGWO algorithm. The results show that SSA-BI-GRU improves the accuracy and speed of load forecasting, and the established multi-energy flow coupling optimization scheduling model achieves the economic, efficient, and reliable operation of IES.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.