Abstract
An Airborne Wind Energy System (AWES) is a concept to convert wind energy into electricity, which comprises a tethered aircraft connected to a ground station. These systems are capable of harvesting high altitude winds, which are more frequent and more consistent. Among AWES, there are Pumping Kite Generators (PKG) that involve a rigid or flexible kite connected to a motor/generator placed on the ground through a light-weight tether. Such PKG produces electrical power in a cyclical two-phased motion with a traction phase and a retraction phase. During the traction phase, the aim is to maximize power production. This goal is achieved by controlling the kite such that it performs an almost crosswind motion, keeping a low elevation angle in order to maximize the tether tension. During the retraction phase, the tether tension force is minimized by steering the kite while the tether is reeled-in. Such strategy assures that the cyclical two-phased motion has a positive electrical balance at the end of the overall cycle. In a first stage, we solve an optimal control problem to compute the optimal plan for the kite trajectory during the traction phase, maximizing power production. Such trajectory is then used to define a time-independent geometrical path, which in turn is used as the reference path for the path-following control procedure that is developed in a second stage, and for which results are also presented. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract

Abstract
Decision-making is one of the crucial factors in soccer (association football). The current focus is on analyzing data sets rather than posing what if questions about the game. We propose simulation-based methods that allow us to answer these questions. To avoid simulating complex human physics and ball interactions, we use data to build machine learning models that form the basis of an event-based soccer simulator. This simulator is compatible with the OpenAI GYM API. We introduce tools that allow us to explore and gather insights about soccer, like (1) calculating the risk/reward ratios for sequences of actions, (2) manually defining playing criteria, and (3) discovering strategies through Reinforcement Learning.

Abstract
Based on the perspective of information asymmetry theory and transaction cost theory, this paper discusses the effect of agricultural industrialization organizations on the quality of agricultural products. Through the survey of litchi growers in Guangdong Province and surrounding areas, it designs indicators suitable for measuring litchi quality from the two dimensions of safety and texture, uses factor analysis, correlation analysis, OLS model to test the hypothesis proposed herein. The results show that: the involvement of agricultural industrialization organizations has played an important role in improving litchi quality of growers. Enlightenment: unified management and unified standards through industrial organization forms such as enterprises, cooperatives, and associations are an important way to implement large-scale production of litchi, strengthen respective advantages, share risks, seek mutual benefit and win-win results. Government departments should play a leading and propaganda role, provide financial and technical support, improve the service system for the industrialization of the litchi industry, cultivate leading litchi enterprises, and accelerate the development of professional litchi cooperatives, associations and other intermediary organizations to make them become standardized and competitive main market players. © 2021 ACM.

Abstract
The scarcity of resources is one of the main concerns for the present and the future of the environment and society. The "load factor" in logistic transport has a great potential for improvement, especially in the last-mile deliveries, as the transport of goods is largely fragmented between several small companies using small vehicles. This paper investigates the potential for collaboration to increase efficiency in urban logistics. Based on an overview of the concepts and initiatives regarding vertical and horizontal collaboration, a research agenda is proposed.

Abstract
Peak shaving of utility grid power is an important application, which benefits both grid operators and end users. In this article, an optimal rule-based peak shaving control strategy with dynamic demand and feed-in limits is proposed for grid-connected photovoltaic (PV) systems with battery energy storage systems. A method to determine demand and feed-in limits depending on the day-ahead predictions of load demand and PV power profiles is developed. Furthermore, an optimal rule-based control strategy that determines day-ahead charge/discharge schedules of battery for peak shaving of utility grid power is proposed. The rules are formulated such that the peak utility grid demand and feed-in powers are limited to the corresponding demand and feed-in limits of the day, respectively, while ensuring that the state-of-charge (SoC) of the battery at the end of the day is the same as the SoC of the start of the day. The optimal inputs required for applying the proposed rule-based control strategy are determined using a genetic algorithm for minimizing peak energy drawn from the utility grid. The proposed control algorithm is tested for various PV power and load demand profiles using MATLAB.