Optimal Discrete Net-Load Balancing in Smart Grids with High PV Penetration
- Univ. of Southern California, Los Angeles, CA (United States)
- Army Research Lab., Playa Vista, CA (United States)
Mitigating supply-demand mismatch is essential for smooth power grid operation. Traditionally, load curtailment techniques such as demand response have been used for this purpose. However, these cannot be the only component of a net-load balancing framework for smart grids with high PV penetration. These grids sometimes exhibit supply surplus, causing overvoltages. Currently, these are mitigated using voltage manipulation techniques such as Volt-Var Optimizations, which are computationally expensive, thereby increasing the complexity of grid operations. Taking advantage of recent technological developments that enable rapid selective connection of PV modules of an installation to the grid, we develop a unified net-load balancing framework that performs both load and solar curtailment. We demonstrate that when the available curtailment values are discrete, this problem is NP-hard and we develop bounded approximation algorithms. Our algorithms produce fast solutions, given the tight timing constraints required for grid operation, while ensuring that practical constraints such as fairness, network capacity limits, and so forth are satisfied. We also develop an online algorithm that performs net-load balancing using only data available for the current interval. Using both theoretical analysis and practical evaluations, we show that our net-load balancing algorithms provide solutions that are close to optimal in a small amount of time.
- Research Organization:
- Univ. of Southern California, Los Angeles, CA (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
- Grant/Contract Number:
- EE0008003
- OSTI ID:
- 1607513
- Journal Information:
- ACM Transactions on Sensor Networks, Vol. 14, Issue 3-4; ISSN 1550-4859
- Publisher:
- Association for Computing MachineryCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
An Ultrashort-Term Net Load Forecasting Model Based on Phase Space Reconstruction and Deep Neural Network
|
journal | April 2019 |
Similar Records
NO-LESS: Near optimal curtailment strategy selection for net load balancing in micro grids
Risk aware net load balancing in micro grids with high DER penetration