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7th IEEE International Conference on Power and Energy (PECon)

作者： Obaro, Adewale Z. Munda, Josiah L. Siti, Mukwanga W. Tshwane Univ Technol Elect Engn Pretoria South Africa

ISBN: (纸本)9781538654316

The rising operating cost of power systems and over-utilization of fossil fuel deposits have led to continuous energy scarcity and a wide gap between energy demand and supply. These pose critical challenges across the world. The renewable energy sources (RESs) provide a viable and sustainable energy alternative which is capable of meeting the exponential energy growth, reducing over-dependency on fossil fuels as well as minimizing global warming. This paper presents an optimal control and management of an autonomous hybrid energy system (AHES) that reliably supplies energy demand at a minimum daily operating cost. The non-linear cost function is formulated as a mixed integer nonlinear programming (MINLP) problem to optimize the use of renewable resources and minimize the utilization of diesel generator (DG). The unpredictability inherent in RESs is addressed through the optimal design and management of multiple energy generation sources, and battery storage system (BSS). The MINLP optimization technique employed is validated with a dynamic commercial daily load profiles. The simulation results show that the proposed hybrid system significantly minimizes daily operating cost and improves supply reliability when compared to DG-single system.

关键词： hybrid energy system battery storage system mixed integer nonlinear programming energy management technique

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Solving mixed-integer nonlinear programming problems using improved genetic algorithms

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KOREAN JOURNAL OF CHEMICAL ENGINEERING 2011年第1期28卷 32-40页

作者： Wasanapradit, Tawan Mukdasanit, Nalinee Chaiyaratana, Nachol Srinophakun, Thongchai Kasetsart Univ Dept Chem Engn Fac Engn Bangkok 10900 Thailand King Mongkuts Univ Technol Fac Engn Dept Chem Engn Bangkok 10140 Thailand King Mongkuts Univ Technol Fac Engn Dept Chem Engn Bangkok 10800 Thailand Natl Ctr Excellence Petr Petrochem & Adv Mat Bangkok 10330 Thailand

This paper proposes a method for solving mixed-integer nonlinear programming problems to achieve or approach the optimal solution by using modified genetic algorithms. The representation scheme covers both integer and real variables for solving mixed-integer nonlinear programming, nonlinear programming, and nonlinear integer programming. The repairing strategy, a secant method incorporated with a bisection method, plays an important role in converting infeasible chromosomes to feasible chromosomes at the constraint boundary. To prevent premature convergence, the appropriate diversity of the structures in the population must be controlled. A cross-generational probabilistic survival selection method (CPSS) is modified for real number representation corresponding to the representation scheme. The efficiency of the proposed method was validated with several numerical test problems and showed good agreement.

关键词： Genetic Algorithms mixed integer nonlinear programming Repairing Strategy CPSS Modified Genetic Algorithms

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Reactive Power Planning for Regional Power Grids Based on Active and Reactive Power Adjustments of DGs

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ENERGIES 2018年第6期11卷 1606-1606页

作者： Shen, Yangwu Shen, Feifan Chen, Yaling Liang, Liqing Zhang, Bin Ke, Deping Sate Grid Hunan Elect Power Corp Res Inst Changsha 410007 Hunan Peoples R China Tech Univ Denmark Dept Elect Engn DK-2008 Copenhagen Denmark Hunan Univ Chinese Med Sch Humanities & Management Changsha 410208 Hunan Peoples R China Wuhan Univ Dept Elect Engn Wuhan 430000 Hubei Peoples R China

To deal with extreme overvoltage scenarios with small probabilities in regional power grids, the traditional reactive power planning model requires a huge VAR compensator investment. Obviously, such a decision that makes a large investment to cope with a small probability event is not economic. Therefore, based on the scenario analysis of power outputs of distributed generations and load consumption, a novel reactive power planning model considering the active and reactive power adjustments of distributed generations is proposed to derive the optimal allocation of VAR compensators and ensure bus voltages within an acceptable range under extreme overvoltage scenarios. The objective of the proposed reactive power planning model is to minimize the VAR compensator investment cost and active power adjustment cost of distributed generations. Moreover, since the proposed reactive power planning model is formulated as a mixed-integer nonlinear programming problem, a primal-dual interior point method-based particle swarm optimization algorithm is developed to effectively solve the proposed model. Simulation results were conducted with the modified IEEE 30-bus system to verify the effectiveness of the proposed reactive power planning model.

关键词： reactive power planning distributed generation active power adjustment mixed integer nonlinear programming

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Multi-objective Optimization-Tool for the Universal Application in Chemical Process Design

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CHEMICAL ENGINEERING & TECHNOLOGY 2017年第10期40卷 1867-1875页

作者： Ernst, Philipp Zimmermann, Kristina Fieg, Georg Hamburg Univ Technol Inst Proc & Plant Engn Schwarzenberg Campus 4 D-21073 Hamburg Germany

A universally applicable procedure for multi-objective optimization of chemical processes is developed. A set of known methods and procedures is adapted, combined with newly developed concepts, and integrated into the developed optimization tool, namely, the Adv:ProcessOptimizer. It allows for efficient, comfortable, and robust optimization of a process which is modeled in one of the various linked commercial simulation tools. As a result, the application of the process design with an overlaid optimization is easily accessible for academia and process industry. The industrial styrene process was optimized in order to validate the method. The results show a very densely and mostly equally crowded Pareto front and considerable savings in investment as well as operating costs compared to two reference designs.

关键词： Chemical process design Genetic algorithm mixed integer nonlinear programming Multi-objective optimization

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Development of a Diversity-Preserving Strategy for the Pareto Optimization in Chemical Process Design

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CHEMIE INGENIEUR TECHNIK 2017年第10期89卷 1297-1305页

作者： Zimmermann, Kristina Fieg, Georg Hamburg Univ Technol Inst Proc & Plant Engn Schwarzenberg Campus 4 D-21073 Hamburg Germany

The simulation-based design of chemical processes with an overlaid multi-objective optimization is of growing importance. The quality of the determined optimization results, referred to as the Pareto front, influences directly the variety of solutions given to the decision maker. In case of the frequently used genetic algorithms, a lot of studies have been done for a precise approximation of the Pareto front. However, most of the developed methods are inconvenient and/or time-consuming and, thus, inappropriate for industrial applications. A novel approach, the two-step optimization, was successfully tested in order to overcome these challenges.

关键词： Computer-aided process engineering Diversity Genetic algorithm mixed integer nonlinear programming Multi-objective optimization

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Maximizing a class of submodular utility functions with constraints

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MATHEMATICAL programming 2017年第1-2期162卷 145-164页

作者： Yu, Jiajin Ahmed, Shabbir Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA

Motivated by stochastic 0-1 integer programming problems with an expected utility objective, we study the mixed-integer nonlinear set: where N is a positive integer, is a concave function, are nonnegative vectors, d is a real number and B is a positive real number. We propose a family of inequalities for the convex hull of P by exploiting submodularity of the function over and the knapsack constraint . Computational effectiveness of the proposed inequalities within a branch-and-cut framework is illustrated using instances of an expected utility capital budgeting problem.

关键词： Submodularity Cutting planes Lifting mixed integer nonlinear programming Branch-and-cut

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Fuel Inventory of the Multi-Bed Storage System of the SDS Considering Daily Operation of the Tokamak

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FUSION SCIENCE AND TECHNOLOGY 2017年第3期71卷 296-304页

作者： Lee, Jae-Uk Chang, Min Ho Yun, Sei-Hun Ha, Jin-Kuk Lee, Euy Soo Lee, In-Beum Pohang Univ Sci & Technol Dept Chem Engn San 31 Pohang 790784 South Korea Natl Fus Res Inst 169-148 Gil Kwahak Ro Daejon 34133 South Korea Dongguk Univ Dept Chem Biochem Engn Seoul 100715 South Korea

A Tokamak has startup and shutdown periods during which demand specifications differ from those during steady fueling operation. These periods can affect the required number of getter beds of the Storage and Delivery System. In this study, we developed a mathematical model based on the State Task Network, and an algorithm that considers daily operation which includes the period from startup to shutdown to find the optimal number of getter beds. This algorithm can estimate the optimal initial inventory of tritium or deuterium in a getter bed to compensate for fuel consumption until shutdown. The inductive operation mode of the Tokamak is analyzed to illustrate the applicability of the model and algorithm.

关键词： Storage and delivery system multi-bed system mixed integer nonlinear programming

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Technical and economic analysis of home energy management system incorporating small-scale wind turbine and battery energy storage system

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JOURNAL OF CLEANER PRODUCTION 2017年 159卷 106-118页

作者： Hemmati, Reza Kermanshah Univ Technol Dept Elect Engn Kermanshah Iran

Home energy management system (HEMS) is an important problem that has been attracting significant attentions in the recent years. However, the conventional HEMS includes several shortcomings. The conventional HEMSs mainly utilize battery energy storage system (BESS) to deal with energy uncertainties. But they only ascertain optimal charging-discharging pattern for BESS and the power and capacity of BESS are not optimally determined. Furthermore, most of the HEMSs are modeled as a mixed integer linear programming (MILP) including linearization and relaxations. Additionally, considering all possible operating conditions for home has not been adequately addressed in the existing HEMSs. The possible operating conditions are (i) receiving energy from the main grid (i.e., purchasing energy), (ii) sending energy to the utility grid (i.e., selling energy), (iii) working on standalone mode as disconnected from the network (i.e., net-zero energy building). As a result, current paper deals with these existing challenges at the same time. This paper presents HEMS including small-scale wind turbine, BESS, load curtailment option, and fuel cell vehicle. The introduced HEMS not only determines optimal charging discharging pattern for BESS, but also specifies optimal capacity and optimal rated power of the BESS at the same time. The proposed HEMS is expressed as a mixed integer nonlinear programming (MINLP) and solved by cultural algorithm as an effective Meta-heuristic optimization algorithm. All three operating conditions are considered for home. Output power of wind unit is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to deal with uncertainties. Results emphasize on the feasibility and usefulness of the introduced HEMS. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Battery energy storage system Home energy management system Stochastic optimization mixed integer nonlinear programming Wind turbine

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Penalty and relaxation methods for the optimal placement and operation of control valves in water supply networks

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2017年第1期67卷 201-223页

作者： Pecci, Filippo Abraham, Edo Stoianov, Ivan Imperial Coll London Dept Civil & Environm Engn London England

In this paper, we investigate the application of penalty and relaxation methods to the problem of optimal placement and operation of control valves in water supply networks, where the minimization of average zone pressure is the objective. The optimization framework considers both the location and settings of control valves as decision variables. Hydraulic conservation laws are enforced as nonlinear constraints and binary variables are used to model the placement of control valves, resulting in a mixed-integer nonlinear program. We review and discuss theoretical and algorithmic properties of two solution approaches. These include penalty and relaxation methods that solve a sequence of nonlinear programs whose stationary points converge to a stationary point of the original mixed-integer program. We implement and evaluate the algorithms using a benchmarking water supply network. In addition, the performance of different update strategies for the penalty and relaxation parameters are investigated under multiple initial conditions. Practical recommendations on the numerical implementation are provided.

关键词： Water distribution networks mixed integer nonlinear programming Mathematical programs with complementarity constraints nonlinear programming

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Integration of oilfield planning problems: infrastructure design, development planning and production scheduling

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2017年 158卷 585-602页

作者： Redutskiy, Yury Molde Univ Coll POB 2110 N-6402 Molde Norway

The oil and gas industry faces considerable technological challenges nowadays, mainly associated with nonconventional reserves and offshore environments. To ensure the economic efficiency of operations under such complicated conditions, industrial solutions called "smart fields" were introduced. A vital part of these solutions is strategic planning which aims to coordinate field development and hydrocarbons production operations to optimize the entire field lifecycle, given the chosen planning criterion (e.g., net present value of the project). Still, in many cases engineering design is conducted with a conservative approach of solving one problem at a time. In this study, a multi-period mixed integer nonlinear problem (MINLP) covering the relevant issues of both development and production phases, is introduced. The contribution of the proposed model to the area of oilfield development planning is related to the model's simultaneously incorporating technological details regarding the infrastructure layout, pressures and flows in the gathering system, and artificial lift performance, all of which ultimately aims to provide realistic production scheduling results and cost evaluation. The composed model is used to study the benefits of joint development and production planning in comparison to planning these two phases of the project separately. This research is relevant to the engineering design departments and contractors for the preliminary design stage of the engineering project when the infrastructures layout and capacities are chosen, and rough estimates of costs and revenues are calculated.

关键词： Development and production planning Electrical submersible pump Integrated decision-making mixed integer nonlinear programming Oilfield infrastructure design Operational efficiency Production scheduling

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