Optimal Energy Control Of A Rubber Tyred Gantry Crane With Potential Energy Recovery

Abstract

Seaports and rail terminals use Rubber Tired Gantry (RTG) to organise container aisles, loading, and moving cargo-containers. They operate as the link between the cranes and the means of transportation by road, rail, or sea connections. The handling of containers and the motion of RTG cranes are powered by electric motors, which are powered mainly by two sources, namely the standalone diesel powered and the grid connection from the local electrical network. Looking at an operation efficiency and energy management’s point of view, the main problem occurring in RTG crane system, is that the majority of electrical energy or fuel consumed comes from hoisting containers with different weights to several heights; additionally, the peak demand increases when the RTG crane handles heavier containers. Furthermore, during the lowering phase of the containers, potential power is dissipated as heat through resistor banks, used for braking purposes. To solve these problems, this work developed optimal energy management models of the proposed hybrid diesel/battery and hybrid grid/battery RTG cranes, respectively, to minimize the total electricity costs. The first model was based on the optimal energy management model for a RTG crane, supplied by a hybrid diesel generator/battery system. The aim of the model is to reduce the energy cost spending and CO2 emission, by minimizing the amount of fuel consumed by the diesel generator and maximizing the potential energy recovered through the regenerative braking during the container lowering phase. As a case study, a 40 tonne RTG crane, operating in South Africa, has been selected. The demand profile, size of the diesel generator, as well as the battery storage system are used as input for the developed model. Simulations, for a complete RTG handling cycle, have been conducted, to evaluate the techno-economic performances of the developed model use, to optimally dispatch the power flow in the system during the different phases of operation. As compared to the baseline case, where the diesel generator is used alone to accommodate the same demand, the simulation results for the selected day of operation have shown that, using the proposed model, a 40.6% reduction in the operation cost, as well as CO2 emission, is achievable in the case of the proposed system, without energy recovery; 82.17% is achievable in the case where the energy recovery is included. Looking further into the stochastic nature of the demand, the analysis of a year of operation has revealed that 76.04% in operation costs may be potentially saved, using the proposed system. The result of the true payback period analysis has shown that the overall investment cost may be recovered in 1.36 years. Additionally, it may be observed, from the results, that the peak power demand on the diesel generator, has been reduced. This may assist in reducing the power rating and the initial cost of the diesel generator. The second model was based on the optimal energy management model for the grid powered electric RTG, with a battery storage system. The aim of the model is to reduce the operation cost, by minimizing the component linked to the maximum demand charges from the grid, as well as the component linked to the Time of Use (ToU) pricing structure. As a case study, a RTG crane operating in South Africa, has been selected. The load profile, the battery storage system, ToU tariff, as well as the maximum demand charges, are used as input for the developed model. Simulations, for a complete RTG handling cycle, have been conducted, to evaluate the techno-economic performances of the developed model, used to optimally dispatch the power flow in the system during the different phases of operation. Three main configurations have been simulated as energy sources for the RTG crane, namely, the exclusive supply from the grid, grid/battery hybrid system without energy recovery during the lowering phase and grid/battery hybrid with energy recovery, during the lowering phase. As compared to the baseline, the simulation results have shown that, using the proposed model, a possible 50.36%, 60.6% and 64.4% cost reduction, per full handing cycle, is possible in off-peak standard and peak pricing period, for the selected winter day. Table 2 further shows that the maximum demand charges, for a full load in any of the pricing periods is USD 2 639.39, when the baseline is considered. This may be reduced by 45.20%, to USD 1446.24, when the RTG crane is supplied by the optimally controlled hybrid system, with energy recovery. The yearly analysis has revealed that the break-even point of the proposed optimally controlled hybrid grid/Battery, with energy recovery, suppling the RTG crane, may take place after 1.36 years, corresponding to USD 121 900. For the 20 years’ project lifetime, the computed lifecycle, in the case of the proposed optimally controlled grid/Battery with energy recovery, is USD 1 425 000. However, when solely the baseline is considered, the projected lifecycle cost is USD 5 384 000. There is a potential cost saving of USD 3 950 000, corresponding to 73.53%. The result of the true payback period analysis has shown that the overall investment cost may be recovered in 1.716 years. Additionally, using the proposed system, the peak power demand on the grid has been reduced. This may assist in reducing the size of the inverter by more than 50%, which may lower the initial cost of the system. These results further demonstrate that, using the proposed optimal control models, the peak power demands on the grid, or on the DG, have been reduced. This may assist in reducing the size of the inverter, or of the DG by more than 50%, which may lower the initial cost of the system. This, in turn, serves as a greater incentive for seaports and rail terminals to implement these energy management strategies, reducing their operating cost and increasing their benefits.