Optimal placement of battery energy storage in distribution networks considering conservation voltage reduction and stochastic load composition

Abstract

Deployment of battery energy storage (BES) in active distribution networks (ADNs) can provide many benefits in terms of energy management and voltage regulation. In this study, a stochastic optimal BES planning method considering conservation voltage reduction (CVR) is proposed for ADN with high-level renewable energy resources. The proposed method aims to determine the optimal BES sizing and location to minimise the total investment and operation cost considering energy saving achieved by CVR, while satisfying system operational constraints in the presence of stochastic renewable power generation. The uncertainty of load composition is also modelled through scenario analysis. The proposed planning scheme is tested in a modified IEEE 15-bus system and 43-bus radial system, respectively. The numerical results validate that the combination of CVR and BES can achieve more energy savings.

A probabilistic electric power distribution automation operational planning approach considering energy storage incorporation in service restoration

“…Moreover, SOC es ijkts refers to the state of charge of the ES system connected to load point i in the tth hour of service restoration after fault occurrence on the jth equipment of the EPDN for the sth service restoration scenario of the kth year of the DA operational planning period. The second part of the objective function is formulated in expression (6) and expression (7). Herein, ENS ijks is the energy not sold to customers connected to load point i in the tth hour of service restoration after fault occurrence on the jth equipment of the EPDN for the sth service restoration scenario of the kth year of the DA operational planning period.…”

“…4 In this regard, there exist a number of valuable studies proposing novel approached for reliability enhancement through ESs incorporation in service restoration process. [5][6][7][8][9][10][11] The reliability level of EPDNs is improved in Moafi et al 5 through presenting an algorithm that incorporates ESs during service restoration aiming at minimizing the EPDNs reliability cost, regarding the DGs operation during service restoration. A novel methodology is proposed for reliability enhancement of the EPDNs through ESs incorporation in service restoration via energy not supplied index minimization in Alharbi and Bhattacharya.…”

“…A novel methodology is proposed for reliability enhancement of the EPDNs through ESs incorporation in service restoration via energy not supplied index minimization in Alharbi and Bhattacharya. 6 Zhang et al 7 proposed an approach in which ESs are incorporated in service restoration in order to enhance the reliability level of the EPDN up to a pre-defined level. ESs are suggested to be employed in service restoration in Wen et al 8 in order to improve the microgrids reliability level while considering the uncertainty of DGs generated power and their outage frequency and time.…”

Hierarchical Look-Ahead Conservation Voltage Reduction Framework Considering Distributed Energy Resources and Demand Reduction

“…In Equations (9) and (10), the exponential voltage terms for the real and reactive load consumption can be approximated via piecewise linearization, expressed in Equations (11) and (12). For a total of K breaking points, ∆V k h,i is the increment in V h,i in the kth piecewise interval (k = 1, .…”

“…Using mixed-integer nonlinear programming (MINLP), day-ahead models with voltage regulating devices [9] and model predictive control (MPC)-based approaches were formulated by considering solar PV and wind turbine (WT) generators [10]. From a planning perspective, several approaches for CVR implementation have been proposed for optimal distributed generation (DG) and ESS placement in stochastic optimization problems along with: (1) uncertain DG outputs/load consumptions [11]; (2) chance constraints [12]; and (3) the determination of the optimal location and size of capacitors and DERs in microgrids [13]. Through modeling and estimations for time-varying loads such as air conditioners and refrigerators, the impact of such loads on CVR has been quantified [14][15][16].…”