Search results for " optimization."
showing 10 items of 2333 documents
A Deep Reinforcement Learning scheme for Battery Energy Management
2020
Deep reinforcement learning is considered promising for many energy cost optimization tasks in smart buildings. How-ever, agent learning, in this context, is sometimes unstable and unpredictable, especially when the environments are complex. In this paper, we examine deep Reinforcement Learning (RL) algorithms developed for game play applied to a battery control task with an energy cost optimization objective. We explore how agent behavior and hyperparameters can be analyzed in a simplified environment with the goal of modifying the algorithms for increased stability. Our modified Deep Deterministic Policy Gradient (DDPG) agent is able to perform consistently close to the optimum over multi…
Applications and numerical convergence of the partial inverse method
2006
In 1983, J.E. Spingarn introduced what he called the Partial Inverse Method in the framework of Mathematical Programming. Since his initial articles, numerous applications have been given in various fields including Lagrangian multipliers methods, location theory, convex feasibility problems, analysis of data, economic equilibrium problems. In a first part of this paper we give a survey of these applications. Then by means of optimization problems relevant to location theory such as single and multifacility minimisum or minimax location problems, we examine the main advantages of the algorithm and we point out its drawbacks mainly concerning the rate of convergence. We study how different p…
A brief overview on the numerical behavior of an implicit meshless method and an outlook to future challenges
2015
In this paper recent results on a leapfrog ADI meshless formulation are reported and some future challenges are addressed. The method benefits from the elimination of the meshing task from the pre-processing stage in space and it is unconditionally stable in time. Further improvements come from the ease of implementation, which makes computer codes very flexible in contrast to mesh based solver ones. The method requires only nodes at scattered locations and a function and its derivatives are approximated by means of a kernel representation. A perceived obstacle in the implicit formulation is in the second order differentiations which sometimes are eccesively sensitive to the node configurat…
A novel numerical meshless approach for electric potential estimation in transcranial stimulation
2015
In this paper, a first application of the method of fundamental solutions in estimating the electric potential and the spatial current density distribution in the brain due to transcranial stimulation, is presented. The coupled boundary value p roblems for the electric potential are solved in a meshless way, so avoiding the use of grid based numerical methods. A multi-spherical geometry is considered and numerical results are discussed.
An exact algorithm for preventive maintenance planning of series-parallel systems
2009
Reliability is a meaningful parameter in assessing the performance of systems such as chemical processing facilities, power plant, aircrafts, ships, etc. In the literature, reliability optimization is widely considered during the system design phase and it is carried out by an opportune selection of both system components and redundancy. On the other hand, the problem of maintaining a required level of reliability by an opportune maintenance policy has been poorly examined. The paper tackles this problem for a system whose major components can be maintained only during a planned system downtime. An exact algorithm is proposed in order to single out the set of components that must be maintai…
Unbiased Simultaneous Prediction Limits on Observations in Future Samples
2013
This paper provides procedures for constructing unbiased simultaneous prediction limits on the observations or functions of observations of all of k future samples using the results of a previous sample from the same underlying distribution belonging to invariant family. The results have direct application in reliability theory, where the time until the first failure in a group of several items in service provides a measure of assurance regarding the operation of the items. The simultaneous prediction limits are required as specifications on future life for components, as warranty limits for the future performance of a specified number of systems with standby units, and in various other app…
Integrated Production and Predictive Maintenance Planning based on Prognostic Information
2019
International audience; This paper address the problem of scheduling production and maintenance operation in predictive maintenance context. It proposes a contribution in the decision making phase of the prognostic and health management framework. Theprognostics and decision processes are merged and an ant colony optimization approach for finding the sequence of decisions that optimizes the benefits of a production system is developed. A case study on a single machine composed of several components where machine can have several usage profiles. The results show thatour approach surpasses classical condition based maintenance policy.
A Constrained Optimal Model Predictive Control for Mono Inverter Dual Parallel PMSM Drives
2018
The actual trends in the design of AC drives are directed to the reduction of the total weight, volume and cost. Usually, this implies the necessity to adopt new motor topologies and converter architectures. An important role is played by the mono-inverter dual parallel motor (MIDP), which gives the possibility to reduce the total weight and costs of power converters. This paper proposes a novel model predictive control algorithm in order to improve the transient performances of a MIDP used for an overhead carrier. The effectiveness of the proposal control is verified through some numerical simulations.
A novel meta-heuristic optimization algorithm based MPPT control technique for PV systems under complex partial shading condition
2021
Abstract The need to combat the increase in global warming is well taken by solar energy lead renewable energy resources. The techno-economic feasibility of solar systems in the form of photovoltaic (PV) generation is highly dependent upon its operating conditions. The nonlinear control problem is further worsened by partial shading (PS) environment causing major power losses. Bio-inspired maximum power point tracking (MPPT) control techniques, in literature, exhibit some major common drawbacks such as high tracking and settling time, oscillations at global maxima (GM), and local maxima (LM) trapping under PS conditions. This paper presents a novel search and rescue (SRA) optimization algor…
Assessment of Renewable Sources for the Energy Consumption in Malta in the Mediterranean Sea
2016
The main purpose of this paper is to analyze the energy production in the Maltese islands, focusing on the employment of renewable energies in order to increase their energy independence. The main renewable source here proposed is wave energy: thanks to a strategic position, Malta will be able to produce electrical energy using an innovative type of Wave Energy Converter (WEC) based on the prototype of a linear generator realized by University of Palermo. The use of this new technology will be able to cut down the electrical energy production from traditional power plants and, consequently, the greenhouse gas emissions (GHG). Wave energy source and off-shore photovoltaic (PV) technology are…