Specifically for wind and photovoltaic, energy Storage is well regarded as an important tool for renewable energy. Distributed generation could also give benefits, but the position and use of wind energy are almost reciprocal to the PV system. So the needs of energy storage devices are coming into account for enhancing the power generations. This chapter gives brief idea about the conventional and flow based battery system for energy storage in power system. Here various conventional battery system compared with flow battery system for maintaining the power stabilities and power quality. The objective for this study is to find the better energy storage device which can regulate both stability and efficiency of the renewable energy system. Basically wind energy battery storage systems are depicted here with their construction, operation and usability. This paper can be effective for the researchers to study and to implement the better energy storage device in the wind or solar system to regulate the power quality. A brief comparison was highlighted in the discussion section for better analysis.
In this manuscript, the energy trading model is proposed for investigating the cooperative benefits between several electric vehicle charging stations (EVCSs) and integrated energy systems (IES) based on hybrid system. The proposed hybrid system is combination of Radial‐Basis Function Neural Network (RBFNN) and artificial transgender longicorn algorithm (ATLA), hence it is called RBFNN‐ATLA technique. Initially, the RBFNN approach manages the energy between IES and EVCSs. After that, the original issue breaks down into the main energy trade and payment negotiation issue. The energy trading issue and payment negotiation problem can be solved using ATLA approach. This proposed structure may not only diminish the IES cost, however also enlarge the EVCS profit. The uncertainties in electricity and renewable energy prices are modeled using a robust optimization technique. Additionally, the integrated demand response is modeled for maximizing operational performance. The distributed algorithm depends on the proposed technique is evolved for solving the issue of energy trading, ensuring the privacy of players. The proposed algorithm may obtain the global optimal solutions devoid of adjusting the parameter compared with existing algorithm. The proposed system is performed by the matrix laboratory (MATLAB)/Simulink and the performance is evaluated with other existing methods. The RBFNN‐ATLA method reduces the cost up to 3.76%, 7.793%, 8.210% and 9.01% for independent and cooperative mode. The experimental outcomes demonstrate that the proposed system can accurately detect that optimal global solution.
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