A game-theoretic control approach for the optimal energy storage under power flow constraints in distribution networks

2020 ◽  
Author(s):  
Paolo Scarabaggio ◽  
Raffaele Carli ◽  
Mariagrazia Dotoli
Keyword(s):  
Energy Storage ◽  
Power Flow ◽  
Distribution Networks ◽  
Control Approach ◽  
Optimal Energy ◽  
Game Theoretic ◽  
Flow Constraints

scholarly journals Stochastic Expansion Planning of Various Energy Storage Technologies in Active Power Distribution Networks

2021 ◽  
Vol 13 (10) ◽  
pp. 5752
Author(s):  
Reza Sabzehgar ◽  
Diba Zia Amirhosseini ◽  
Saeed D. Manshadi ◽  
Poria Fajri
Keyword(s):  
Energy Storage ◽  
Power Distribution ◽  
Power Flow ◽  
Lithium Ion ◽  
Distribution Networks ◽  
Renewable Energy Resources ◽  
Flow Equations ◽  
Second Order Cone ◽  
Li Ion ◽  
The Cost

This work aims to minimize the cost of installing renewable energy resources (photovoltaic systems) as well as energy storage systems (batteries), in addition to the cost of operation over a period of 20 years, which will include the cost of operating the power grid and the charging and discharging of the batteries. To this end, we propose a long-term planning optimization and expansion framework for a smart distribution network. A second order cone programming (SOCP) algorithm is utilized in this work to model the power flow equations. The minimization is computed in accordance to the years (y), seasons (s), days of the week (d), time of the day (t), and different scenarios based on the usage of energy and its production (c). An IEEE 33-bus balanced distribution test bench is utilized to evaluate the performance, effectiveness, and reliability of the proposed optimization and forecasting model. The numerical studies are conducted on two of the highest performing batteries in the current market, i.e., Lithium-ion (Li-ion) and redox flow batteries (RFBs). In addition, the pros and cons of distributed Li-ion batteries are compared with centralized RFBs. The results are presented to showcase the economic profits of utilizing these battery technologies.

scholarly journals Hour-Ahead Energy Trading Management with Demand Forecasting in Microgrid Considering Power Flow Constraints

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3494
Author(s):  
Kuo Feng ◽  
Chunhua Liu ◽  
Zaixin Song
Keyword(s):  
Power Flow ◽  
Low Voltage ◽  
Supply And Demand ◽  
Demand Forecasting ◽  
Distribution Networks ◽  
Small Scale ◽  
Energy Trading ◽  
Medium Voltage ◽  
The Neural Network ◽  
Flow Constraints

Multiple small-scale low-voltage distribution networks with distributed generators can be connected in a radial pattern to form a multi-bus medium voltage microgrid. Additionally, each bus has an independent operator that can manage its power supply and demand. Since the microgrid operates in the market-oriented mode, the bus operators aim to maximize their own benefits and expect to protect their privacy. Accordingly, in this paper, a distributed hour-ahead energy trading management is proposed. First, the benefit optimization problem of the microgrid is solved, which is decomposed into the local benefit optimization sub problems of buses. Then, the local sub problems can be solved by the negotiation of operators with their neighbors. Additionally, the reference demand before negotiation is forecasted by the neural network rather than given in advance. Furthermore, the power flow constraints are considered to guarantee the operational stability. Meanwhile, the power loss minimization is considered in the objective function. Finally, the demonstration and simulation cases are given to validate the effectiveness of the proposed hour-ahead energy trading management.

H∞ Control Approach to Reduction of Energy Capacity of Energy Storage Systems

2017 ◽  
Vol 137 (8) ◽  
pp. 596-597
Author(s):  
Kenta Koiwa ◽  
Kenta Suzuki ◽  
Kang-Zhi Liu ◽  
Tadanao Zanma ◽  
Masashi Wakaiki ◽  
...  
Keyword(s):  
Energy Storage ◽  
Storage Systems ◽  
Energy Capacity ◽  
Energy Storage Systems ◽  
Control Approach

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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