Improvement to an existing multi-level capacitated lot sizing problem considering setup carryover, backlogging, and emission control

This paper presents a multi-level, multi-item, multi-period capacitated lot-sizing problem. The lot-sizing problem studies can obtain production quantities, setup decisions and inventory levels in each period fulfilling the demand requirements with limited capacity resources, considering the Bill of Material (BOM) structure while simultaneously minimizing the production, inventory, and machine setup costs. The paper proposes an exact solution to Chowdhury et al. (2018)\u27s[1] developed model, which considers the backlogging cost, setup carryover & greenhouse gas emission control to its model complexity. The problem contemplates the Dantzig-Wolfe (D.W.) decomposition to decompose the multi-level capacitated problem into a single-item uncapacitated lot-sizing sub-problem. To avoid the infeasibilities of the weighted problem (WP), an artificial variable is introduced, and the Big-M method is employed in the D.W. decomposition to produce an always feasible master problem. In addition, Wagner & Whitin\u27s[2] forward recursion algorithm is also incorporated in the solution approach for both end and component items to provide the minimum cost production plan. Introducing artificial variables in the D.W. decomposition method is a novel approach to solving the MLCLSP model. A better performance was achieved regarding reduced computational time (reduced by 50%) and optimality gap (reduced by 97.3%) in comparison to Chowdhury et al. (2018)\u27s[1] developed model

Optimal Routing and Charging of Electric Logistics VehiclesBased on Long-Distance Transportation and Dynamic Transportation System

The application of electric vehicles (EVs) in the logistics industry has become more extensive. However, the mileage limitation of electric logistics vehicles (ELVs) and the long-distance distribution of ELVs have become urgent problems. Therefore, this paper proposes a long-distance distribution model for ELVs based on dynamic traffic information considering fleet mileage, distribution time and total distribution cost as the optimisation objectives, thus reasonably planning road selection and charging, and alleviating “mileage anxiety” in the long-distance distribution of ELVs. The model proposed in this paper comprehensively considers the characteristics of the high-speed and low-speed roads, the changes in road traffic flow on weekdays and non-weekdays, the time-of-use electricity price of electric vehicle charging stations (EVCSs) and uses the M/M/s queuing theory model to determine the charging waiting time. Finally, a real traffic network is taken as an example to verify the practicability and effectiveness of this model

An Economical Model Development for a Hybrid System of Grid Connected Solar PV and Electrical Storage System

Energy sources management is one of the most important concern in the recent decades. There are finite amount of non-renewable energy sources and one day they will run out if they have been used as primary sources of energy. Renewable energy sources have been significantly reduced the environmental effects. For most of them the source of energy is non-depletable. One of the concerns associated with renewable resources is uncertainty or unavailability. Energy Storage Systems (ESSs) can help to have more reliable and more efficient systems by adjusting the charge and discharge time and rate. In this study, an economic model is developed for a hybrid system of grid-connected solar photovoltaic, Compressed Air Energy Storage (CAES), and batteries. PV generation depends on irradiance and it is intermittent in nature. CAES can store energy in larger amounts and for longer periods than other storage systems and can offer lower price for stored energy. Batteries are integrated with CAES in this model mainly for lower demand and shorter periods. The presented model is a non-linear model and it’s been transformed to a linear model in this study. Optimal planning for generation and storage is derived based on the developed model for each day by using operation research techniques to maximize the value of energy which carried over the time. The results are different for each period and are highly dependent on the load demand. The results show that using solar PV panels coupled with energy storage systems increase the efficiency and reliability of the system. In addition to that, efficient use of energy storage system have a great impact on the final prices of electricity since electricity prices in low peak demand periods is lower than high peak periods

Investigating techno-economic factors influencing the future value of energy storage technologies

PhD ThesisThe decarbonization of electricity networks, all over the world, has led to an increasing amount of renewable generation in the energy mix. Although renewable generators produce clean and eco-friendly energy, high-penetration levels of renewables could also impose techno-economic challenges to the grid caused by their intermittent and stochastic character, compromising not only the security of electricity networks but also their energy equity. Renewable Energy Generation (REG) Providers can support electricity networks to address these challenges by providing grid-services and applications using different solutions. Energy Storage (ES) Devices are a flexible, yet expensive, smart grid solution able to store amounts of energy at one instant for their later utilization. The main barrier for their widespread proliferation has been, however, the high investment costs required to acquire and install these devices. This research investigates the factors influencing the future value of Energy Storage Technologies. The strategy to tackle this aim is based on designing, developing and implementing a techno-economic framework that allows the assessment of ES devices at planning stage. The framework is comprised of various models to examine diverse factors contributing with the value of ES devices. The simulation results of these framework models determine the maximum revenue that REG Providers can obtain from using ES devices alongside with the ES sizing design to achieve these outcomes. The outcomes of this work show the value for REG providers of using ES devices to address multiple applications and to profit from different energy market, the benefits and drawbacks of applying ES technologies in mandatory and non-mandatory service schemes, the value of using ES devices in mutual operation with renewable generators, the advantages of selecting ES technologies, and the contributions that enhancing the technical and economic features of ES technologies have on the value. The findings from this research can facilitate the widespread deployment of ES devices by providing valuable information to REG providers and investors when considering investments in ES technologies, technology developers to prioritize areas of enhancement in ES device, policy makers and regulators to understand the end to end effects that current regulations might produce on the interested parties and selling companies to expand the range of ES devices and hybrid combinations to offer for customers