An environmental based techno-economic assessment for battery energy storage system allocation in distribution system using new node voltage deviation sensitivity approach

Author(s):  
Pawan Saini ◽  
Lata Gidwani
2016 ◽  
Vol 17 (2) ◽  
pp. 173-189 ◽  
Author(s):  
Ryuto Shigenobu ◽  
Ahmad Samim Noorzad ◽  
Cirio Muarapaz ◽  
Atsushi Yona ◽  
Tomonobu Senjyu

Abstract Distributed generators (DG) and renewable energy sources have been attracting special attention in distribution systems in all over the world. Renewable energies, such as photovoltaic (PV) and wind turbine generators are considered as green energy. However, a large amount of DG penetration causes voltage deviation beyond the statutory range and reverse power flow at interconnection points in the distribution system. If excessive voltage deviation occurs, consumer’s electric devices might break and reverse power flow will also has a negative impact on the transmission system. Thus, mass interconnections of DGs has an adverse effect on both of the utility and the customer. Therefore, reactive power control method is proposed previous research by using inverters attached DGs for prevent voltage deviations. Moreover, battery energy storage system (BESS) is also proposed for resolve reverse power flow. In addition, it is possible to supply high quality power for managing DGs and BESSs. Therefore, this paper proposes a method to maintain voltage, active power, and reactive power flow at interconnection points by using cooperative controlled of PVs, house BESSs, EVs, large BESSs, and existing voltage control devices. This paper not only protect distribution system, but also attain distribution loss reduction and effectivity management of control devices. Therefore mentioned control objectives are formulated as an optimization problem that is solved by using the Particle Swarm Optimization (PSO) algorithm. Modified scheduling method is proposed in order to improve convergence probability of scheduling scheme. The effectiveness of the proposed method is verified by case studies results and by using numerical simulations in MATLAB®.


Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3065 ◽  
Author(s):  
Monika Sandelic ◽  
Daniel-Ioan Stroe ◽  
Florin Iov

This paper focuses on the sizing of a battery energy storage system providing frequency containment reserves in a power system with a large wind power penetration level. A three-stage sizing methodology including the different aspect of battery energy storage system performance is proposed. The first stage includes time-domain simulations, investigating battery energy storage system dynamic response and its capability of providing frequency reserves. The second stage involves lifetime investigation. An economic assessment of the battery unit is carried out by performing the last stage. The main outcome of the proposed methodology is to choose the suitable battery energy storage system size for providing frequency containment reserve from augmented wind power plants while fulfilling relevant evaluation criteria imposed for each stage.


Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1339 ◽  
Author(s):  
Hee-Jun Cha ◽  
Sung-Eun Lee ◽  
Dongjun Won

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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