1,721,052 research outputs found
Near real time load shifting control for residential electricity prosumers under designed and market indexed pricing models
No full textThis paper presents an event driven model predictive control approach for a local energy management system, enabling residential consumers to the automated participation in demand side management (DSM) programs. We consider a household equipped with smart appliances, a storage unit, electric vehicles and photovoltaic micro-generation. Resources are coordinated according to the needs of maximizing self-consumption and minimizing the cost of energy consumption, in a contractual scenario characterized by designed or market indexed pricing models, with DSM options. The control action (appliances' start times, the storage charging profile and the IEC 61851 compliant charging profile of the electric vehicles) is updated every time an event triggers the controller, such as a user request, a price/volume signal or the notification of a new forecast of micro-generation from the photovoltaic unit. The control framework is flexible enough to meet the real dynamics of a household and short-term grid requirements, while taking into account user preferences, contractual and technical constraints. A proper set of simulations validates the proposed approach. © 2014 Elsevier Ltd
An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management
No full textThis paper proposes the design of a Smart Home Controller strategy providing efficient management of electric energy in a domestic environment. The problem is formalized as an event driven binary linear programming problem, the output of which specifies the best time to run of smart household appliances, under a virtual power threshold constraint, taking into account the real power threshold and the forecast of consumption from not plannable loads. The optimization is performed each time the system is triggered by proper events, in order to tailor the controller action to the real life dynamics of an household. This problem formulation allows to analyze relevant scenarios from consumer and energy retailer point of view: here overload management, optimization of economic saving in case of Time of Use Tariff and Demand Side Management have been discussed and simulated. Simulations have been performed on relevant test cases, based on real load profiles provided by the smart appliance manufacturer Electrolux S.p.A. and on energy tariffs suggested by the energy retailer Edison. Results provide a proof of concept about the consumers benefits coming from the use of local energy management systems and the relevance of automated Demand Side Management for the general target of efficient and cost effective operation of electric networks. © 2012 Elsevier Ltd
Decentralized PEV Control Based on a Subgradient Method for Mixed-Integer Programming Problems
No full textIn this paper, a subgradient method for solving mixed-integer linear programming problems is tailored and used to control in a distributed, and hence scalable way, the recharging process of a fleet of plug-in electric vehicles (PEVs). This makes possible to scale the problem to large PEV fleets, in a privacy-preserving fashion, something that cannot be done when relying on centralized optimization-based methods. A key challenge to face is given by the fact that the mathematical formulation of the PEV charging problem includes both real (i.e., continuous) and integer (in particular, Boolean) variables. This complicates significantly the mathematical theory, compared to the case in which all the involved variables are real. The PEV charging power is realistically modelled as a semi-continuous variable (while most of the works model it as a on/off variable), and the goal is to recharge the PEVs according to the user charging preferences, while letting the aggregated PEV power track a given power reference. Simulation results are discussed and possible directions for future research are outlined
Open source implementation of monitoring and controlling services for EMS/SCADA systems by means of web services
No full textThis paper presents an implementation of monitoring and controlling services for energy-management system/supervisory- control-and-data-acquisition systems, based on IEC 61970 and IEC 61850 international standards. The proposed solution is based on web services technology that enables the typical advantages of an open-source framework, such as applications decoupling, applications integration, reduction of upgrading costs, reuse of existing infrastructures, and ease of development. Standardized interfaces are provided by the generic interface definition interfaces of IEC 61970. The web server that has been developed has been tested in a simulation environment where the physical devices of a generic power system were simulated with databases whose data models were provided by the common information model of IEC 61970
Decentralized Model Predictive Control of Plug-in Electric Vehicles Charging based on the Alternating Direction Method of Multipliers
Full text linkThis paper presents a decentralized Model Predictive Control (MPC) for Plug-in Electric Vehicles (PEVs) charging, in presence of both network and drivers' requirements. The open loop optimal control problem at the basis of MPC is modeled as a consesus with regularization optimization problem and solved by means of the decentralized Alternating Direction Method of Multipliers (ADMM). Simulations performed on a realistic test case show the potential of the proposed control approach and allow to provide a preliminary evaluation of the compatibility between the required computational effort and the application in real time charging control system
A Novel Approach to Generation Portfolio Optimization by using Genetic Algorithms and Stochastic Methods
No full textIn this paper we present the Portfolio Optimization Problem in the electricity generation framework. We consider traditional and fully controllable energy sources together with wind source, strongly supported by economical benefits but exposed to intermittent generation volatility. Due to the statistical uncertainty about parameters, we formalize the optimization problem in a probabilistic sense and solve it by using Genetic Algorithms
Local energy management system: Control scheme and loads modeling
No full textIn this work we present a general control scheme for the management of an energy community and a load modeling approach. We adopt a multilevel control scheme in which the first level computes the energy consumption set point towards the second level and the generation planning towards the energy sources, the second level is in charge of local loads scheduling and micro-generation planning. © 2010 IEEE
Electric vehicles charging control in a smart grid: A model predictive control approach
No full textThe paper presents an event driven model predictive control (MPC) framework for managing charging operations of electric vehicles (EV) in a smart grid. The objective is to minimize the cost of energy consumption, while respecting EV drivers' preferences, technical bounds on the control action (in compliance with the IEC 61851 standard) and both market and grid constraints (by seeking the tracking of a reference load profile defined by the grid operator). The proposed control approach allows "flexible" EV users to participate in demand side management (DSM) programs, which will play a crucial role in improving stability and efficiency of future smart grids. Further, the natural MPC formulation of the problem can be recast into a mixed integer linear programming problem, suitable for implementation on a calculator. Simulation results are provided and discussed in detail. (C) 2013 Elsevier Ltd. All rights reserved
Optimal Stochastic Control of Energy Storage System Based on Pontryagin Minimum Principle for Flattening PEV Fast Charging in a Service Area
Full text linkThis letter discusses stochastic optimal control of an energy storage system (ESS) for reducing the impact on the grid of fast charging of electric vehicles in a charging area. A trade off is achieved between the objectives of limiting the charging power exchanged with the grid, and the one of limiting the fluctuation, around a given reference, of the ESS energy. We show that the solution of the problem can be derived from the one of a related deterministic problem, requiring the realistic assumption that the charging area operator knows an estimate of the aggregated charging power demand over the day. In addition, two alternative configurations of the charging area are discussed, and it is shown that, while they share the same solution, one better mitigates the demand uncertainty. Numeric simulations are provided to validate the proposed approach
Interdependency modeling and analysis of critical infrastructures based on Dynamic Bayesian Networks
No full textThis paper presents a novel approach to the critical infrastructure (CI) interdependencies analysis, based on the Dynamic Bayesian Network (DBN) formalism. Our original modeling procedure divides the DBN in three levels: an atomic events level, which models the adverse events impacting on the analyzed CIs, a propagation level, which captures CI interdependencies, and a services level, which allows to monitor the state of provided services. Three types of analyses can be performed: a reliability study, an adverse events propagation study, and a failure identification analysis. A case study provided by Israel Electric Corporation is considered, and explicative simulations are presented and discussed in detail. © 2011 IEEE
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