scholarly journals Real-Time Active-Reactive Optimal Power Flow with Flexible Operation of Battery Storage Systems

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1697 ◽  
Author(s):  
Erfan Mohagheghi ◽  
Mansour Alramlawi ◽  
Aouss Gabash ◽  
Frede Blaabjerg ◽  
Pu Li
Keyword(s):  
Real Time ◽  
Wind Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Storage Systems ◽  
Mixed Integer ◽  
Second Phase ◽  
Battery Storage ◽  
Optimal Power ◽  
Flexible Operation

In this paper, a multi-phase multi-time-scale real-time dynamic active-reactive optimal power flow (RT-DAR-OPF) framework is developed to optimally deal with spontaneous changes in wind power in distribution networks (DNs) with battery storage systems (BSSs). The most challenging issue hereby is that a large-scale ‘dynamic’ (i.e., with differential/difference equations rather than only algebraic equations) mixed-integer nonlinear programming (MINLP) problem has to be solved in real time. Moreover, considering the active-reactive power capabilities of BSSs with flexible operation strategies, as well as minimizing the expended life costs of BSSs further increases the complexity of the problem. To solve this problem, in the first phase, we implement simultaneous optimization of a huge number of mixed-integer decision variables to compute optimal operations of BSSs on a day-to-day basis. In the second phase, based on the forecasted wind power values for short prediction horizons, wind power scenarios are generated to describe uncertain wind power with non-Gaussian distribution. Then, MINLP AR-OPF problems corresponding to the scenarios are solved and reconciled in advance of each prediction horizon. In the third phase, based on the measured actual values of wind power, one of the solutions is selected, modified, and realized to the network for very short intervals. The applicability of the proposed RT-DAR-OPF is demonstrated using a medium-voltage DN.

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.

Optimal power flow incorporating wind power and optimally allocated energy storage

2019 ◽  
Vol 44 (3) ◽  
pp. 227-238
Author(s):  
Ulagammai Meyyappan
Keyword(s):  
Energy Storage ◽  
Power System ◽  
Wind Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Storage Systems ◽  
Energy Storage Systems ◽  
Wind Generators ◽  
Optimal Power ◽  
Inherent Nature

The rapid growth of wind power poses new challenges for power system operators and electricity marketers. The benefits of using wind power are emission reduction and decrease in consumption of conventional resources. But the inherent nature of wind energy poses challenges in the power system operation and planning. In order to consider the wind power as firm power, auxiliary energy storage is added as a backup to encounter the variations in wind power. In this article, optimal power flow with wind and energy storage is developed. The energy storage systems are installed as a standby of wind generators to meet the demand consistently. The objective is to minimize the loss by optimal location and sizing of energy storage systems. With the optimally located energy storage systems, optimal power flow is carried out using shuffled frog-leaping algorithm technique and tested on IEEE 30 bus system.

Designing the Electricity Market with Energy Storage Devices

2020 ◽  
Vol 12 (12) ◽  
pp. 31-43
Author(s):  
Tatiana A. VASKOVSKAYA ◽  
◽  
Boris A. KLUS ◽  
Keyword(s):  
Energy Storage ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Storage Systems ◽  
Energy System ◽  
Energy Storage Systems ◽  
Storage Model ◽  
Optimal Power ◽  
Wide Range

The development of energy storage systems allows us to consider their usage for load profile leveling during operational planning on electricity markets. The paper proposes and analyses an application of an energy storage model to the electricity market in Russia with the focus on the day ahead market. We consider bidding, energy storage constraints for an optimal power flow problem, and locational marginal pricing. We show that the largest effect for the market and for the energy storage system would be gained by integration of the energy storage model into the market’s optimization models. The proposed theory has been tested on the optimal power flow model of the day ahead market in Russia of 10000-node Unified Energy System. It is shown that energy storage systems are in demand with a wide range of efficiencies and cycle costs.

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