Optimal Sizing of Battery Energy Storage System in a Shipboard Power System with considering Energy Management Optimization

Abstract

Due to the increasing concerns about the environmental and economic issues of traditional ships, all-electric ships with energy storage and renewable energy integration have become more and more appealing for the forthcoming future. In this paper, an optimal energy storage system (ESS) capacity determination method for a marine ferry ship is proposed; this ship has diesel generators and PV panels. ESSs sizing optimization and power system scheduling optimization are simultaneously conducted and it is converted to a mixed-integer quadratic programming (MIQP) model with special modeling techniques. The case study shows that the proposed method is flexible and effective, and the relationships between the ESSs size and the discharge rate, life cycle times, or initial investment cost are investigated.

Analysis of a linear programming‐based decision‐making model for microgrid energy management systems with renewable sources

“…However, the electrical storage charging/discharging rate impact on the microgrid operating cost is more significant. 250% increase of electrical and heat storage charging/discharging rate leads to a 79% and 32.6% microgrid operating cost improvement respectively 53,54 . The electrical energy storage charging and discharging rate have considerably reduced the non‐consumed renewable generated energy and electrical load shedding by 64% and 83% respectively as illustrated in Figure 7C.…”

“…As the electrical load shedding accounts for 92% of the microgrid operating cost, investigations have been carried out to find how to reduce the load shedding while at the same time maximizing the consumption of the generated renewable power. Hence, as in Reference 53 the electrical/thermal storage capacity ranges from 50 to 200 kWh with a 10‐kW charging/discharging rate and the charging/discharging rate ranges from 10 to 35 kW for a 200‐kWh energy storage capacity has been considered to investigate the effect of the energy storages size capacity and the charging/discharging rate respectively. Figure 7 presents the annual microgrid operating cost in terms of the heat and electrical storage capacity and charging/discharging rate respectively incurred after finding the electrical and thermal power flow decisions of the optimization problem.…”

“…Figure 7 presents the annual microgrid operating cost in terms of the heat and electrical storage capacity and charging/discharging rate respectively incurred after finding the electrical and thermal power flow decisions of the optimization problem. From Figure 7A, it can be shown that the size of the electrical storage significantly affects the microgrid operating cost 53 . Electrical storage increasing from 50 to 90 kWh reduces the operating cost by almost 4% vs 0.6% due to thermal storage capacity increasing.…”

“…From Figure 7A, it can be shown that the size of the electrical storage significantly affects the microgrid operating cost. 53 Electrical storage increasing from 50 to 90 kWh reduces the operating cost by almost 4% vs 0.6% due to thermal storage capacity increasing. Also, over a limited energy storage capacity, the optimization model can no longer improve the microgrid operating cost at a constant charging/discharging rate.…”

Collaborative Optimization of the Battery Capacity and Sailing Speed Considering Multiple Operation Factors for a Battery-Powered Ship

“…Xianqiang Bao et al proposed a joint optimization method of ESSs size and power energy management storage to minimize the ship operation cost over its life. The battery size was used to reduce the fuel consumption of an engineering ship [29]. M. Othman et al proposed a modeling method for battery size optimization, dividing the whole optimization problem into two sub-problems to reduce the computational burden of sim optimization [30].…”