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Title: Optimal Iterative Method for Network Utility Maximization with Intertemporal Constraints

Abstract

Network utility maximization (NUM) has been widely used to solve the optimal resource allocation problem in wireless network and power systems. The network planner aims to allocate generation and demand over producers and consumers such that social welfare is maximized while supply and demand are balanced, and network constraints such as branch capacity constraints are satisfied. However, when taking into account dynamics of agents, such as ramp rate constraints on power output for suppliers and impact of cumulative prior consumption on current demand for consumers, a single-period formulation is not sufficient. We propose an iterative method for the multi-period NUM with intertemporal constraints based on dual decomposition. It features a price iteration scheme that achieves optimal social welfare, and the algorithm is guaranteed to converge if proper concavity condition holds. We illustrate the iterative algorithm by power system examples. It is shown that similar to locational marginal price (LMP) in power systems, time-varying congestion prices arise when there exists binding branch constraints. Simulation results also demonstrate that there is increase in social welfare compared to a single-period formulation.

Authors:
 [1]; ORCiD logo [1];  [1];  [1]; ORCiD logo [1]
  1. BATTELLE (PACIFIC NW LAB)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1592699
Report Number(s):
PNNL-SA-138370
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: 3rd IEEE Conference on Control Technology and Applications (CCTA 2019), August 19-21, 2019, Hong Kong, China
Country of Publication:
United States
Language:
English

Citation Formats

Ma, Ke, Wang, Peng, Ramachandran, Thiagarajan, Lian, Jianming, and Hammerstrom, Donald J. Optimal Iterative Method for Network Utility Maximization with Intertemporal Constraints. United States: N. p., 2019. Web. doi:10.1109/CCTA.2019.8920423.
Ma, Ke, Wang, Peng, Ramachandran, Thiagarajan, Lian, Jianming, & Hammerstrom, Donald J. Optimal Iterative Method for Network Utility Maximization with Intertemporal Constraints. United States. doi:10.1109/CCTA.2019.8920423.
Ma, Ke, Wang, Peng, Ramachandran, Thiagarajan, Lian, Jianming, and Hammerstrom, Donald J. Tue . "Optimal Iterative Method for Network Utility Maximization with Intertemporal Constraints". United States. doi:10.1109/CCTA.2019.8920423.
@article{osti_1592699,
title = {Optimal Iterative Method for Network Utility Maximization with Intertemporal Constraints},
author = {Ma, Ke and Wang, Peng and Ramachandran, Thiagarajan and Lian, Jianming and Hammerstrom, Donald J.},
abstractNote = {Network utility maximization (NUM) has been widely used to solve the optimal resource allocation problem in wireless network and power systems. The network planner aims to allocate generation and demand over producers and consumers such that social welfare is maximized while supply and demand are balanced, and network constraints such as branch capacity constraints are satisfied. However, when taking into account dynamics of agents, such as ramp rate constraints on power output for suppliers and impact of cumulative prior consumption on current demand for consumers, a single-period formulation is not sufficient. We propose an iterative method for the multi-period NUM with intertemporal constraints based on dual decomposition. It features a price iteration scheme that achieves optimal social welfare, and the algorithm is guaranteed to converge if proper concavity condition holds. We illustrate the iterative algorithm by power system examples. It is shown that similar to locational marginal price (LMP) in power systems, time-varying congestion prices arise when there exists binding branch constraints. Simulation results also demonstrate that there is increase in social welfare compared to a single-period formulation.},
doi = {10.1109/CCTA.2019.8920423},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}

Conference:
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