scholarly journals Rapid Prototyping of Multi-Functional Battery Energy Storage System Applications

2018 ◽  
Vol 8 (8) ◽  
pp. 1326 ◽  
Author(s):  
Claudia Zanabria ◽  
Filip Andrén ◽  
Johannes Kathan ◽  
Thomas Strasser
Keyword(s):  
Energy Storage ◽  
Power Distribution ◽  
Distribution System ◽  
Storage System ◽  
Distribution Networks ◽  
Energy Storage System ◽  
Power Utility ◽  
Battery Energy Storage ◽  
Energy Management Systems ◽  
Battery Energy

Battery Energy Storage Systems (BESS) are starting to play an important role in today’s power distribution networks. They provide a manifold of services for fulfilling demands and requests from diverse stakeholders, such as distribution system operators, energy market operators, aggregators but also end-users. Such services are usually provided by corresponding Energy Management Systems (EMS). This paper analyzes the complexity of the EMS development process resulting from an evolving power utility automation.

scholarly journals Optimal Incorporation of Photovoltaic Energy and Battery Energy Storage Systems in Distribution Networks Considering Uncertainties of Demand and Generation

2021 ◽  
Vol 11 (17) ◽  
pp. 8231
Author(s):  
Hussein Abdel-Mawgoud ◽  
Salah Kamel ◽  
Marcos Tostado-Véliz ◽  
Ehab E. Elattar ◽  
Mahmoud M. Hussein
Keyword(s):  
Energy Storage ◽  
Optimization Algorithm ◽  
Distribution System ◽  
Storage System ◽  
Global Solutions ◽  
Distribution Networks ◽  
Energy Storage System ◽  
Buoyant Force ◽  
Battery Energy Storage ◽  
Battery Energy

In this paper, the Archimedes optimization algorithm (AOA) is applied as a recent metaheuristic optimization algorithm to reduce energy losses and capture the size of incorporating a battery energy storage system (BESS) and photovoltaics (PV) within a distribution system. AOA is designed with revelation from Archimedes’ principle, an impressive physics law. AOA mimics the attitude of buoyant force applied upward on an object, partially or entirely dipped in liquid, which is relative to the weight of the dislodged liquid. Furthermore, the developed algorithm is evolved for sizing several PVs and BESSs considering the changing demand over time and the probability generation. The studied IEEE 69-bus distribution network system has different types of the load, such as residential, industrial, and commercial loads. The simulation results indicate the robustness of the proposed algorithm for computing the best size of multiple PVs and BESSs with a significant reduction in the power system losses. Additionally, the AOA algorithm has an efficient balancing between the exploration and exploitation phases to avoid the local solutions and go to the best global solutions, compared with other studied algorithms.

scholarly journals Implementation of Optimal Scheduling Algorithm for Multi-Functional Battery Energy Storage System

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1339 ◽  
Author(s):  
Hee-Jun Cha ◽  
Sung-Eun Lee ◽  
Dongjun Won
Keyword(s):  
Energy Storage ◽  
Electricity Market ◽  
Distribution System ◽  
Wind Farm ◽  
Storage System ◽  
Energy Storage System ◽  
Optimal Scheduling ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy

Energy storage system (ESS) can play a positive role in the power system due to its ability to store, charge and discharge energy. Additionally, it can be installed in various capacities, so it can be used in the transmission and distribution system and even at home. In this paper, the proposed algorithm for economic optimal scheduling of ESS linked to transmission systems in the Korean electricity market is proposed and incorporated into the BESS (battery energy storage system) demonstration test center. The proposed algorithm considers the energy arbitrage operation through SMP (system marginal price) and operation considering the REC (renewable energy certification) weight of the connected wind farm and frequency regulation service. In addition, the proposed algorithm was developed so that the SOC (state-of-charge) of the ESS could be separated into two virtual SOCs to participate in different markets and generate revenue. The proposed algorithm was simulated and verified through Matlab and loaded into the demonstration system using the Matlab “Runtime” function.

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