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19th European Conference on the Applications of Evolutionary Computation (EvoApplications)

作者： Alves, Maria Joao Antunes, Carlos Henggeler Carrasqueira, Pedro Univ Coimbra INESC Coimbra Fac Econ Coimbra Portugal Univ Coimbra INESC Coimbra Dept Elect Engn & Comp Coimbra Portugal INESC Coimbra Coimbra Portugal

ISBN: (纸本)9783319312040

In this paper a bilevel programming model is proposed for modeling the interaction between electricity retailers and consumers endowed with energy management systems capable of providing demand response to variable prices. The model intends to determine the optimal pricing scheme to be established by the retailer (upper level decision maker) and the optimal load schedule adopted by the consumer (lower level decision maker) under this price setting. The lower level optimization problem is formulated as a mixed-integer linear programming (MILP) problem. A hybrid approach consisting of a genetic algorithm and an exact MILP solver is proposed. The individuals of the population represent the retailer's choices (electricity prices). For each price setting, the exact optimal solution to the consumer's problem is obtained in a very efficient way using the MILP solver. An illustrative case is analyzed and discussed.

关键词： Genetic algorithm Bilevel problem mixed-integer linear programming Demand response Electricity retail market

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A Domain Specific Language for Optimal Pumping Systems 1

A Domain Specific Language for Optimal Pumping Systems

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1st Industry Track for Software Language Engineering Workshop (ITSLE)

作者： Saul, Benjamin Berg, Christian Zimmermann, Wolf Martin Luther Univ Halle Wittenberg Von Seckendorff Pl 1 D-06120 Halle Saale Germany

ISBN: (纸本)9781450346467

This paper discusses the design and implementation of a domain-specific language for modelling energy optimal pumping systems (realizing specific flows and pressures). The domain model is transformed into a corresponding mixed-integer linear program which can be solved by standard solvers. The solution together with the original model are transformed into executable simulation models (e.g. MODELICA or MATLAB SIMULINK).

关键词： domain specific language mixed-integer linear programming model to model transformation

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A Multi-layer Optimal Chiller Operation Management Framework 52

A Multi-layer Optimal Chiller Operation Management Framework

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52nd Annual Meeting of the IEEE-Industry-Applications-Society (IAS)

作者： Ye, Yanzhu Sharma, Ratnesh Guo, Feng NEC Labs Amer Inc Dept Energy Management Princeton NJ 08540 USA

ISBN: (纸本)9781479983971

This work targets on the chiller plant operation management for a large campus building cooling load. In this paper a multi-layer optimal chiller operation management framework is proposed to operate various chiller units to meet the system cooling load while reduce the system operation cost. The first layer is the day-ahead 24-hour chiller operation planning layer which optimizes multiple chiller sequencing and chillers loading. The second real-time dispatching layer effectively addresses load forecasting uncertainties in real-time. The load uncertainty is solved hierarchically through two steps of approaches. An efficient and accurate system modeling framework for optimization is formulated with mixed-integer linear expressions to reduce the computational complexity. The effectiveness of this proposed management framework is demonstrated for an actual chiller plant operation in university campus. Simulation analyses validate that the proposed method can effectively address various levels of forecast uncertainty and reduce the operation cost.

关键词： chiller operation multi-layer mixed-integer linear programming optimization cost minimization

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Parameter Adaption for Generalized Multiframe Tasks and Applications to Self-Suspending Tasks 22

Parameter Adaption for Generalized Multiframe Tasks and Appl...

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22nd IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTSCA)

作者： Peng, Bo Fisher, Nathan Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

ISBN: (纸本)9781509024797

The generalized multiframe task model (GMF) extends the sporadic task model and multiframe task model. Each frame in the GMF model contains an execution time, a relative deadline, and a minimum inter-arrival time. These parameters are fixed after task specification time in the GMF model. However, multimedia and adaptive control systems may be overloaded and no longer stabilized when the task parameters in such systems are not flexible. In order to address this problem, deadlines and periods may change to alleviate temporal overload, for example in the parameter adaption and elastic scheduling model. In this paper, we propose a new model GMF-PA (the GMF model with parameter adaption). This model allows task parameters to be flexible in arbitrary-deadline systems. A necessary schedulability test based on mixed-integer linear programming (MILP) is given to check the schedulability under EDF scheduling and optimally assign deadlines and periods at the same time. We also prove that the test is a sufficient and necessary schedulability test when task parameters must be integers. An approximation algorithm is also deployed to reduce computational running time. The speed-up factor of our approximation algorithm is 1+is an element of where is an element of can be arbitrarily small, with respect to the exact schedulability test of GMF-PA tasks under EDF. We also apply the GMF model to self-suspending tasks. By extending recent work on scheduling self-suspending tasks, we remove the assumption that deadlines are equally assigned in self-suspending tasks, and the system is extended from constrained-deadline systems to arbitrary-deadline systems. We have done exhaustive experiments to show that the schedulability ratio is improved using our techniques in our GMF-PA model.

关键词： generalized multiframe task model multisegment self-suspending tasks uniprocessor scheduling mixed-integer linear programming approximation algorithms

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Network Interdiction through Length-Bounded Critical Disruption Paths: A Bi-Objective Approach

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Electronic Notes in Discrete Mathematics 2016年 52卷 375-382页

作者： Granata, Donatella Sgalambro, Antonino Istituto per le Applicazioni del Calcolo Mauro Picone National Research Council of Italy Italy

In this paper the Bi-Objective k-Length-Bounded Critical Disruption Path (BO-kLB-CDP) optimization problem is proposed, aimed at maximizing the interdiction effects provided on a network by removing a simple path connecting a given source and destination whose length does not exceed a certain threshold. The BO-kLB-CDP problem extends the Critical Disruption Path (CDP) problem introduced by Granata et al. in [Granata, D. and Steeger, G. and Rebennack, S., Network interdiction via a Critical Disruption Path: Branch-and-Price algorithms, Computers & Operations Research, Volume 40, Issue 11, November 2013, Pages 2689-2702]. Several real applications of this class of optimization problems arise in the field of security, surveillance, transportation and evacuation operations. In order to overcome some limits of the original CDP problem and increase its suitability for practical purposes, first we consider a length limitation for Critical Disruption Paths. Second, we generalize the concept of network interdiction considered in the CDP: beside minimizing the cardinality of the maximal connected component after the removal of the CDP, now we are also interested in maximizing the number of connected components in the residual graph. A mixed integer programming formulation for the BO-kLB-CDP problem is therefore proposed and discussed, presenting the results of a multiple objective analysis performed through a computational experience on a large set of instances. © 2016 Elsevier B.V.

关键词： Connected Components Critical Disruption Path mixed-integer linear programming Multi-Objective Network interdiction

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Modelling minimum pressure height in short-term hydropower production planning 5

Modelling minimum pressure height in short-term hydropower p...

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5th International Workshop on Hydro Scheduling in Competitive Electricity Markets

作者： Dorn, Frederic B. Farahmand, Hossein Skjelbred, Hans Ivar Belsnes, Michael M. SINTEF Energy Res Trondheim Norway

When planning the production for certain hydropower plants, minimum pressure is one of the major critical points. Violation of the minimum pressure causes the power plant to automatically shut down, hence violating the obligations of the plant. Automatic pressure switches and pressure constraints are difficult to model in particular when embedded in a complex water way. This problem is expected to increase when retrofitting hydro installations with new parallel units and increased exploitation of inflow resources. From a scheduling point of view, however, such switches become hard to integrate in an optimal operation plan as the constraint depends on the system state. This paper introduces a novelty in short-term production planning, namely a solution for modelling minimum pressure height in regulated watercourses when optimizing the energy production of hydropower plants. This solution is integrated in the short-term hydropower scheduling tool SHOP. The tool finds an optimal strategy to run a power station with such minimum pressure restrictions and the state dependent topological couplings within the water system. We apply the model on a complex topology, the Sira-Kvina water system, where Norway's largest hydropower station Tonstad Kraftstajon is operationally subject to this rigorous pressure constraint. First, in order to illustrate the concepts of the model, we apply the model on a simplified water course including one reservoir. Next, the outcome and tests are demonstrated on the final model of two reservoirs whose respective outflows are joining together above the pressure gauge, as found in the Sira-Kvina water system. (C) 2016 Published by Elsevier Ltd.

关键词： Hydropower scheduling optimization mixed-integer linear programming

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Generation Ramping Valuation in Day-Ahead Electricity Markets 49

Generation Ramping Valuation in Day-Ahead Electricity Market...

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49th Hawaii International Conference on System Sciences (HICSS)

作者： Parvania, Masood Scaglione, Anna Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84112 USA Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85287 USA

ISBN: (纸本)9780769556703

In this paper, we first introduce a variational formulation of the Unit Commitment (UC) problem, in which generation and ramping trajectories of the generating units are continuous time signals and the generating units cost depends on the three signals: the binary commitment status of the units as well as their continuous-time generation and ramping trajectories. We assume such bids are piecewise strictly convex time-varying linear functions of these three variables. Based on this problem derive a tractable approximation by constraining the commitment trajectories to switch in a discrete and finite set of points and representing the trajectories in the function space of piece-wise polynomial functions within the intervals, whose discrete coefficients are then the UC problem decision variables. Our judicious choice of the signal space allows us to represent cost and constraints as linear functions of such coefficients;thus, our UC models preserves the MILP formulation of the UC problem. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total day ahead and real-time operation cost, and the number of ramping scarcity events in the real-time operations.

关键词： Unit commitment generation trajectory ramping trajectory ramping cost continuous-time function space mixed-integer linear programming

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Enhancing the Efficiency of Electricity Utilization Through Home Energy Management Systems within the Smart Grid Framework

Enhancing the Efficiency of Electricity Utilization Through ...

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作者： Tiago Daniel Penedo Mendes UNIVERSIDADE DA BEIRA INTERIOR

学位级别：博士

The concept behind smart grids is the aggregation of "intelligence" into the grid, whether through communication systems technologies that allow broadcast/data reception in real-time, or through monitoring and systems control in an autonomous way. With respect to the technological advancements, in recent years there has been a significant increment in devices and new strategies for the implementation of smart buildings/homes, due to the growing awareness of society in relation to environmental concerns and higher energy costs, so that energy efficiency improvements can provide real gains within modern society. In this perspective, the end-users are seen as active players with the ability to manage their energy resources, for example, microproduction units, domestic loads, electric vehicles and their participation in demand response events. This thesis is focused on identifying application areas where such technologies could bring benefits for their applicability, such as the case of wireless networks, considering the positive and negative points of each protocol available in the market. Moreover, this thesis provides an evaluation of dynamic prices of electricity and peak power, using as an example a system with electric vehicles and energy storage, supported by mixed-integer linear programming, within residential energy management. This thesis will also develop a power measuring prototype designed to process and determine the main electrical measurements and quantify the electrical load connected to a low voltage alternating current system. Finally, two cases studies are proposed regarding the application of model predictive control and thermal regulation for domestic applications with cooling requirements, allowing to minimize energy consumption, considering the restrictions of demand, load and acclimatization in the system.

关键词： Communication protocols Energy efficiency Electric vehicles Demand response Smart grids Smart homes mixed-integer linear programming Predictive control

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A MILP-Based Distribution Optimal Power Flow Model for Microgrid Operation

A MILP-Based Distribution Optimal Power Flow Model for Micro...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Liu, Guodong Starke, Michael Zhang, Xiaohu Tomsovic, Kevin Oak Ridge Natl Lab Power & Energy Syst Grp Oak Ridge TN 37830 USA Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN USA

ISBN: (纸本)9781509041688

This paper proposes a distribution optimal power flow (D-OPF) model for the operation of microgrids. The proposed model minimizes not only the operating cost, including fuel cost, purchasing cost and demand charge, but also several performance indices, including voltage deviation, network power loss and power factor. It co-optimizes the real and reactive power form distributed generators (DGs) and batteries considering their capacity and power factor limits. The D-OPF is formulated as a mixed-integer linear programming (MILP). Numerical simulation results show the effectiveness of the proposed model.

关键词： Distribution optimal power flow microgrids distributed generators multiobjective optimization mixed-integer linear programming

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The Effect of Demand Response in the Minimum Available Reserve of Energy Management

The Effect of Demand Response in the Minimum Available Reser...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Soares, Joao Borges, Nuno Fotouhi, Ali Vale, Zita Polytech Porto ISEP IPP GECAD Knowledge Engn & Decis Support Res Ctr Rua Dr Antonio Almeida 431 P-4200072 Oporto Portugal

ISBN: (纸本)9781509041688

This paper presents a multi-objective energy scheduling for the daily operation of a Smart Grid (SG) considering maximization of the minimum available reserve in addition to the cost minimization, to take into account the reliability requirements of critical and vulnerable loads. A Virtual Power Player (VPP) manages the day-ahead energy resource scheduling in the smart grid, considering Distributed Generation (DG) and Vehicle-To-Grid (V2G), while maintaining a highly reliable power for the critical loads. This work considers high penetration of critical loads, e.g. industrial processes that require high power quality, high reliability and few interruptions. A mathematical formulation is described and a deterministic technique based on mixed-integer linear programming (MILP) is used to solve the multi-objective problem. The effect of some customers with DR in this context is analyzed to assess the benefits in the energy scheduling problem. A case study using a 180-bus Portuguese distribution network with 90 load points, several DG units and a large fleet of Electric Vehicles (EVs) with V2G is used to illustrate the performance of the proposed method.

关键词： Electric Vehicles Multi-objective optimization Pareto front mixed-integer linear programming Smart Grid

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