Compatibility of Glyphosate with Galerucella calmariensis; a Biological Control Agent for Purple Loosestrife (Lythrum salicaria)

By integrating Galerucella calmariensis with glyphosate there is potential to achieve both immediate and sustained control of purple loosestrife (Lythrum salicaria). The objective of this study was to determine the compatibility of glyphosate on the oviposition and survival of adult G. Calmariensis and on the ability of G. calmariensis third instar larvae to pupate to teneral adults. Our results revealed glyphosate (formulated as Roundup) at a concentration of 2% (2.43L/acre) and 4% solution (4.86 L/acre) had no impact on the ability of G. calmariensis third instar larvae to pupate to new generation adults. To examine the effect of a 2% solution of glyphosate on adult G. calmariensis oviposition and survival, adults were randomly divided between a direct contact group (adults sprayed directly), an indirect contact group (host plants with adults were sprayed), and a control group. Our results revealed that glyphosate does not impact G. calmariensis oviposition or adult survival. The results of this study indicate that G. calmariensis is compatible with glyphosate indicating that further field studies examining integrated control strategies for purple loosestrife are warranted.

Multi-agent modelling for the simulation of a simple smart microgrid

The smart grid is a highly complex system that is being formed from the traditional power grid, adding new and sophisticated communication and control devices. This will enable integrating new elements for distributed power generation and also achieving an increasingly automated operation so for actions of the utilities as for customers. In order to model such systems a bottom-up method is followed, using only a few basic elements which are structured into two layers: a physical layer for the electrical power transmission, and one logical layer for element communication. A simple case study is presented to analyse the possibilities of simulation. It shows a microgrid model with dynamic load management and an integrated approach that can process both electrical and communication flows.

Complete agent based simulation of mini-grids

EuroPES 2009

An agent-based multi-scale wind generation model

(EuroPES 2009)

Agent based modeling of energy networks

Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed.

Distributed optimization in power networks and general multi-agent systems

The dissertation studies the general area of complex networked systems that consist of interconnected and active heterogeneous components and usually operate in uncertain environments and with incomplete information. Problems associated with those systems are typically large-scale and computationally intractable, yet they are also very well-structured and have features that can be exploited by appropriate modeling and computational methods. The goal of this thesis is to develop foundational theories and tools to exploit those structures that can lead to computationally-efficient and distributed solutions, and apply them to improve systems operations and architecture.

Specifically, the thesis focuses on two concrete areas. The first one is to design distributed rules to manage distributed energy resources in the power network. The power network is undergoing a fundamental transformation. The future smart grid, especially on the distribution system, will be a large-scale network of distributed energy resources (DERs), each introducing random and rapid fluctuations in power supply, demand, voltage and frequency. These DERs provide a tremendous opportunity for sustainability, efficiency, and power reliability. However, there are daunting technical challenges in managing these DERs and optimizing their operation. The focus of this dissertation is to develop scalable, distributed, and real-time control and optimization to achieve system-wide efficiency, reliability, and robustness for the future power grid. In particular, we will present how to explore the power network structure to design efficient and distributed market and algorithms for the energy management. We will also show how to connect the algorithms with physical dynamics and existing control mechanisms for real-time control in power networks.

The second focus is to develop distributed optimization rules for general multi-agent engineering systems. A central goal in multiagent systems is to design local control laws for the individual agents to ensure that the emergent global behavior is desirable with respect to the given system level objective. Ideally, a system designer seeks to satisfy this goal while conditioning each agent’s control on the least amount of information possible. Our work focused on achieving this goal using the framework of game theory. In particular, we derived a systematic methodology for designing local agent objective functions that guarantees (i) an equivalence between the resulting game-theoretic equilibria and the system level design objective and (ii) that the resulting game possesses an inherent structure that can be exploited for distributed learning, e.g., potential games. The control design can then be completed by applying any distributed learning algorithm that guarantees convergence to the game-theoretic equilibrium. One main advantage of this game theoretic approach is that it provides a hierarchical decomposition between the decomposition of the systemic objective (game design) and the specific local decision rules (distributed learning algorithms). This decomposition provides the system designer with tremendous flexibility to meet the design objectives and constraints inherent in a broad class of multiagent systems. Furthermore, in many settings the resulting controllers will be inherently robust to a host of uncertainties including asynchronous clock rates, delays in information, and component failures.

Optimization of the pyrolysis process for the production of a biomass derived reducing agent and hydrogen-rich gases

221 p.

Pawpaw seed as fertility control agent on male Nile tilapia

To find out if pawpaw (Carica papaya) seeds can induce sterility in male Nile tilapia (Oreochromis niloticus) and to determine if sterility so induced is reversible or otherwise, mature male tilapia of mean weight 40 g were treated for 30 days with a low dose (4.9 g/kg/day) and a high dose (9.8 g/kg/day) of ground pawpaw seeds incorporated into their feed. Fish of similar sizes in the control experiment were fed with feed that did not contain pawpaw seed. The pawpaw seeds induced permanent sterility in the fish that received the high dose, while sterility in the low dose treatment was reversible. Fish in the control experiment spawned two weeks into the experiment and again in the fifth week. Fish in the low dose treatment spawned three weeks after the treatment had been discontinued. Histological sections of the testes showed that pawpaw seeds produced swollen nuclei in the low dose treatment and disintegrated cells in the high dose treatment. The study showed that pawpaw seeds, which are easy to obtain, can be incorporated into fish feeds and used by farmers to control prolific breeding of Nile tilapia.