An Enhanced Immune-Annealing Algorithm for Mixed-Integer Optimal Power Flow

2007 ◽  
Author(s):  
Cong-Hui Huang ◽  
Whei-Min Lin
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Mixed Integer ◽  
Optimal Power ◽  
Annealing Algorithm

scholarly journals A Scalable Mixed-Integer Decomposition Method for Security-Constrained Optimal Power Flow with Complementarity Constraints

2021 ◽  
Author(s):  
Kibaek Kim ◽  
Youngdae Kim ◽  
Daniel Maldonado ◽  
Michel Schanen ◽  
Victor Zavala ◽  
...  
Keyword(s):  
Decomposition Method ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Mixed Integer ◽  
Complementarity Constraints ◽  
Optimal Power

scholarly journals Distribution Optimal Power Flow With Energy Sharing Via a Peer-To-Peer Transactive Market

2021 ◽  
Vol 9 ◽  
Author(s):  
Boshen Zheng ◽  
Yue Fan ◽  
Wei Wei ◽  
Yourui Xu ◽  
Shaowei Huang ◽  
...  
Keyword(s):  
Equilibrium Condition ◽  
Power Flow ◽  
Distribution Systems ◽  
Optimal Power Flow ◽  
Distribution Network ◽  
Market Equilibrium ◽  
Peer To Peer ◽  
Mixed Integer ◽  
Optimal Power ◽  
Transactive Energy

The technology advancement and cost decline of renewable and sustainable energy increase the penetration of distributed energy resources (DERs) in distribution systems. Transactive energy helps balance the local generation and demand. Peer-to-peer (P2P) energy trading is a promising business model for transactive energy. Such a market scheme can increase the revenue of DER owners and reduce the waste of renewable energy. This article proposes an equilibrium model of a P2P transactive energy market. Every participant seeks the maximum personal interest, with the options of importing or providing energy from/to any other peer across different buses of the distribution network. The market equilibrium condition is obtained by combining the Karush–Kuhn–Tucker conditions of all problems of individual participants together. The energy transaction price is endogenously determined from the market equilibrium condition, which is cast as a mixed-integer linear program and solved by a commercial solver. The transactive energy flow is further embedded in the optimal power flow problem to ensure operating constraints of the distribution network. We propose a remedy to recover a near optimal solution when the second-order cone relaxation is inexact. Finally, a case study demonstrates that the proposed P2P market benefits all participants.

scholarly journals An integrated OPF dispatching model with wind power and demand response for day-ahead markets

2019 ◽  
Vol 9 (4) ◽  
pp. 2794
Author(s):  
Ricardo Moreno ◽  
Johan Obando ◽  
Gabriel Gonzalez
Keyword(s):  
Wind Power ◽  
Demand Response ◽  
Electricity Markets ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Mixed Integer ◽  
New Paradigm ◽  
Linear Quadratic ◽  
Distributed Resources ◽  
Optimal Power

In the day-ahead dispatching of network-constrained electricity markets, renewable energy and distributed resources are dispatched together with conventional generation. The uncertainty and volatility associated to renewable resources represents a new paradigm to be faced for power system operation. Moreover, in various electricity markets there are mechanisms to allow the demand participation through demand response (DR) strategies. Under operational and economic restrictions, the operator each day, or even in intra-day markets, dispatchs an optimal power flow to find a feasible state of operation. The operation decisions in power markets use an optimal power flow considering unit commitment to dispatch economically generation and DR resources under security restrictions. This paper constructs a model to include demand response in the optimal power flow under wind power uncertainty. The model is formulated as a mixed-integer linear quadratic problem and evaluated through Monte-Carlo simulations. A large number of scenarios around a trajectory bid captures the uncertainty in wind power forecasting. The proposed integrated OPF model is tested on the standard IEEE 39-bus system.

scholarly journals Robust Stochastic Dynamic Optimal Power Flow Model of Electricity-Gas Integrated Energy System considering Wind Power Uncertainty

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zhengfeng Qin ◽  
Xiaoqing Bai ◽  
Xiangyang Su
Keyword(s):  
Stochastic Optimization ◽  
Wind Power ◽  
Power Output ◽  
Gas Turbines ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Model ◽  
Mixed Integer ◽  
Stochastic Dynamic ◽  
Optimal Power

The application of gas turbines and power to gas equipment deepens the coupling relationship between power systems and natural gas systems and provides a new way to absorb the uncertain wind power as well. The traditional stochastic optimization and robust optimization algorithms have some limitations and deficiencies in dealing with the uncertainty of wind power output. Therefore, we propose a robust stochastic optimization (RSO) model to solve the dynamic optimal power flow model for electricity-gas integrated energy systems (IES) considering wind power uncertainty, where the ambiguity set of wind power output is constructed based on Wasserstein distance. Then, the Wasserstein ambiguity set is affined to the eventwise ambiguity set, and the proposed RSO model is transformed into a mixed-integer programming model, which can be solved rapidly and accurately using commercial solvers. Numerical results for EG-4 and EG-118 systems verify the rationality and effectiveness of the proposed model.

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