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With the goal of reducing CO2 emissions into the atmosphere and goal of total de pendent on renewable energies to supply electrical demand, high penetration of renewable energy resources with inverter technologies has significantly increased in electric power system. The high penetration of inverter based resources (IBR) in the electric grid in the past few years has created issues and challenges with respect to power system operation and grid stability. This report investigates the impacts of the high penetration of IBR on the system strength, especially the impacts of low system short circuit power and low system inertia. To mitigate these challenges, the thesis develops a security constrained unit com mitment (SCUC) model. The SCUC model includes extra security constraints for short circuit power and system inertia in order to guarantee stable and secure oper ation for the power network. The proposed SCUC simulates with alternating current (AC) power flow model with consideration of both active and reactive power, as well as maintaining volt age security and transmission capacity limits are considered. This thesis also models short circuit calculation in a mathematical programming language (AMPL) software, whose results are verified with known software (digsi lent powerfactory software). Two case studies with two test grids, four bus and fourteen bus test system respec tively, are analyzed to verify the effectiveness of the proposed SCUC model.

Operation Timbang (OPT) Plus is one of the Philippines’ programs that focuses on nutrition by conducting an annual assessment for 0-59 months old children in barangays to identify the malnutrition data in the area. The barangay is the smallest administrative entity in the Philippines. OPT is a plan of action that estimates the number of malnutrition individuals and identifies those who will get prioritized programs in the community. The Iloilo City Health Office conducted the program in seven districts in the Philippines. The office planned to establish a community centre and playground facility based on the priority/demand areas. Maximum Covering Location Problem (MCLP) is used for this study to determine the optimal location that covers the area. A Mathematical Programming Language (AMPL) is used to apply mathematical programming to the MCLP. The results can be used to identify the optimal facility and the maximum coverage of the demand points. The experiment showed that the facility located in Mandurriao District is the optimal facility location. For Underweight/Severely Underweight children, a maximum total of 646 are covered, and for the Overweight/Obese, 1,041 are covered for the chosen facility. In addition, the findings of the sensitivity analysis indicate that the building of the three facilities in the case study can offer 100 percent of the required coverage area.

This study investigates the effective thermal conductivity of a polymer composite reinforced with particulate rice husk (PRH) and particulate carbon fibre (PCF) developed by hand lay-up process. The thermal conductivity of the developed composites at different fibre volume fraction % (FVF) of PRH and PCF at different particle size ratios is analysed by experimentation. Then a mathematical model is developed to find the analytical solution for effective thermal conductivity of the composites. For the developed model, a nonlinear AMPL (A Mathematical Programming Language) programming model is established to find the analytical solution. It is enthusiastic to observe that the experimental values for effective thermal conductivity are in close approximation with the analytical values obtained from the developed AMPL.

The paper is devoted to the construction of mathematical models for problems on the shortest cycles and paths, that pass through a given number of nodes of a directed graph. Such cycles and paths are called k-node, where 1

The purpose of this work is a comparative study of three languages (environments) of optimization modeling: AMPL, Pyomo and JuMP. The comparison will be based on three implementations of the shortest path problem formulated as a linear programming problem. The codes for individual models and differences between them will be presented and discussed. Various aspects will be taken into account, such as: simplicity and intuitiveness of implementation, availability of specific data structures for a LP network problems, etc.

Due to the limited resources and several implementation challenges, frequent link failure is a serious concern in mobile wireless mesh-based Internet of Things (WM-IoT) networks. The unique features of software defined networking (SDN), such as global visibility, network programmability, etc., help to improve the fault tolerance and network management in IoT networks. The integration of SDN and WM-IoT networks leads to a new domain, called software defined WM-IoT (SDWM-IoT) networks. This article discusses the problems caused by the frequent link failures in mobile SDWM-IoT networks. Most of the existing works focus on link failure prevention by precomputing backup paths, link monitoring-based failure detection, etc. However, limited efforts have been devoted for adaptive multiconstrained link failure prevention. This article proposes a proactive optimal policy update mechanism, named Opti-PUM. It is formulated in a promising algebraic modeling language (AMPL), and is solved using a well-known algebraic solver (CPLEX). Opti-PUM is tested under various network scenarios. Additionally, the proposed approach is also implemented in Mininet-WiFi and the obtained results are compared with some well-known existing algorithms. The comparison shows that Opti-PUM helps to achieve the packet delivery ratio (PDR) and packet loss ratio (PLR) improvement of 12.18% and 11.68% , respectively. Similarly, an average delay and jitter improvement of 35.93% and 31.72% have also been achieved.

A Reconfiguração de Sistemas de Distribuição de Energia Elétrica (RSDEE) é um problema tradicional e de alta complexidade matemática visto que, o estado de operação das chaves seccionadoras possibilita a redução de custos de operação totais, bem como a redução das perdas técnicas, de modo que os limites de tensão mínimos necessários para atendimento das cargas sejam respeitados. O problema da RSDEE busca encontrar a combinação ótima dos estados das chaves de interconexão existentes, de maneira que, simultaneamente, atenda as restrições operacionais, minimize a função objetivo em foco e mantenha a radialidade, já o estudo da alocação da Geração Distribuída (GD) busca o melhor local de conexão dos geradores distribuídos no sistema de tal forma que possa minimizar, também, os custos de operação e as perdas totais de potência ativa obedecendo os níveis de tensão estabelecidos pelas normativas nacionais vigentes. Desta forma, este trabalho apresenta uma metodologia de solução ao problema da RSDEE na presença da GD por meio de um modelo de Programação Não-Linear Inteira Mista (PNLIM), desenvolvido em ambiente de programação AMPL - A Mathematical Programming Language - e resolvido pelo solver comercial knitro. Diversos testes foram realizados em sistemas elétricos comumente encontrados na literatura técnica, com o intuito de verificar a convergência do modelo proposto para a solução do problema da RSDEE juntamente com a alocação de GD. Para garantir sucesso nas implementações, inicialmente, resolveram-se de forma independente ambos os problemas e após constatar resultados condizentes, ambos problemas foram resolvidos de forma simultânea. Dos resultados obtidos, constatou-se que o modelo unificado adotado (RSDEE com alocação de GD) possui alta confiabilidade e apresenta soluções ótimas que reduzem significativamente as perdas de potência ativa quando comparadas ao sistema em sua configuração original. Contudo, apesar de sua confiabilidade, a solução do modelo não-linear requer um elevado custo computacional ao se tratar do sistema de 69 barras ou superiores. The Reconfiguration of Electric Power Distribution Systems (REPDS) is a traditional problem and of high mathematical complexity, since the operating state of the disconnecting switches enables the reduction of total operating costs, as well as the reduction of technical losses, so that the minimum voltage limits necessary to meet the loads are respected. The REPDS problem seeks to find the optimal combination of the states of the existing intercon-nection switches, so that, simultaneously, it meets the operational constraints, minimizes the objective function in focus and maintains the radiality, whereas the study of the allocation of the Distributed Generation (DG) it seeks the best connection location for the generators dis-tributed in the system in such a way that it can also minimize operating costs and total active power losses, complying with the voltage levels established by current national regulations. In this way, this work presents a methodology to solve the REPDS problem in the presence of DG through a Mixed Integer Nonlinear Programming (MINLP) model,developed in the AMPL - A Mathematical Programming Language - programming environment and solved by the commercial solver knitro. Several tests were performed on electrical systems commonly found in the technical literature, to verify the convergence of the proposed model to solve the REPDS problem together with the DG allocation. To guarantee success in the implementa-tions, initially, both problems were solved independently and after finding consistent results, both problems were solved simultaneously. From the results obtained, it was found that the adopted unified model (REPDS with DG allocation) has high reliability and presents optimal solutions that significantly reduce active power losses when compared to the system in its original configuration. However, despite its reliability, the solution of the nonlinear model requires a high computational cost when dealing with a system of 69 buses or higher.

Chile is the world’s leading producer of copper, with a market share of 26.8% and accounting for approximately 10% of the gross domestic product. Given the importance of this industrial sector in the country, mine planning is a fundamental tool for achieving strategic, tactical and operational goals. This paper proposes methods to solve the problem of scheduling production in mining, considering the storage and sequencing of power shovels in open-pit mines. The first problem is tactical and operational and seeks to determine the extraction period and destination of each block. The second problem is of an operational nature and consists of defining the optimal sequence of block extraction, considering the mining power shovels. To solve both problems, two mixed integer linear programming models have been proposed and tested in real and random structured instances. The objective function of the proposed models is to maximize the net present value (NPV) of scheduling and maximize the work efficiency of the power shovels in the extraction. The proposed models have been implemented in AMPL and have been solved through the IBM CPLEX and Gurobi solvers. The results show the efficiency of the proposed models, demonstrating that including the storage option in the production schedule increases the operational NPV.

Made available in DSpace on 2022-04-29T08:29:33Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 Distribution network is an essential part of electric power system, which however has higher power losses than transmission system. Distribution losses directly affect the operational cost of the system. Therefore, power loss reduction in distribution network is very important for distribution system users and connected customers. One of the commonly used ways for reducing losses is distribution system reconfiguration (DSR). In this process, configuration of distribution network changes by opening and closing sectional and tie switches in order to achieve the lowest level of power losses, while the network has to maintain its radial configuration and nodal voltage limits, and supply all connected loads. The DSR aiming loss reduction is a complex mixed-integer optimization problem with a quadratic term of power losses in the objective function and a set of linear and non-linear constraints. Accordingly, distribution network researchers have dedicated their efforts to developing efficient models and methodologies in order to find optimal solutions for loss reduction via DSR. In this paper, an efficient mathematical model for loss minimization in distribution network reconfiguration considering the system voltage profile is presented. The model can be solved by commercially available solvers. In the paper, the proposed model is applied to several test systems and real distribution networks showing its high efficiency and effectiveness for distribution systems reconfiguration. Associated Laboratories Institute of Bioenergy Research (IPBEN) São Paulo State University Campus of Ilha Solteira Department of Electrical Power Engineering Tishreen University School of Electrical and Computer Engineering National Technical University of Athens Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Associated Laboratories Institute of Bioenergy Research (IPBEN) São Paulo State University Campus of Ilha Solteira

This paper gives integer linear programming models for scheduling doubles tennis group competitions. The goal is to build a fair and competitive schedule for all players. Our basic model achieves that for each player the average ranking of his partners in all matches is as close as possible to the average ranking of his opponents in all matches. One of the variations of the basic model provides that each matchup is fair and competitive. We also give models for the case when the number of players is 4n + 2, and thus one of the matches has to be singles. Our models were implemented and tested using optimization software AMPL. Computational results along with schedules for some typical situations are also given the paper.

BULOG (Indonesian Bureau of Logistics) Regional Division West Java is a state-owned public company that regulates and maintains a supply of rice in order to meet the needs of all Indonesian people. Currently, BULOG distributing rice from one SubDivre warehouse to another SubDivre warehouse (point-to-point system) so shipping costs are higher because the frequency of transportation used is higher and the total distance traveled is higher. To reduce the cost of distribution, we propose consolidation model based on hub and spoke network topology. Hub and spoke system is done by determining which points become the hubs and which points become the spoke. The problem in determining the location of the hub and spoke is known as the hub location problem. In this problem, single allocation p-hub median problem is used. We use AMPL to get the solution. Various number of hubs (5,6,7) are tested and evaluated based on total shipping cost. The number of hubs which gives the minimum total shipping cost is 7. Delivery system using the hub and spoke network model can reduce the total cost of distribution by 13,94%.

This research is about the household gas network and the purpose is to find out the optimal number and location of the regulator sectors for 6 urban villages in Depok. The problem is solved using Maximum Coverage Location Problem to get the minimum amount of facility with the distance limit of 500 meters. The tool used in this research is AMPL to get optimal solution of the problem. In validating the model, calculations are done using small instances for each urban villages and it resulted that Beji only needs 6 facilities for serve all consumers. The calculation using large instances resulted that number facilities needed to serve 7.515 consumers is 12 from the 19 available facilities. The facilities used are RS B 001, RS B 006, RS B 007, RS B 009, RS BT 01, RS BT 02, RS BT 03, RS BT 04, RS 01, RS 02, RS 04 and RS 06. This means that the available facilities exceed the facilities are be used to serve consumers. This research is expected to assist the development of household gas networks in Indonesia, especially in Depok by increasing the consumers around existing regulator sectors.

This paper presents a simple microwave non-destructive method to assess the uniformity of fiber distribution in the steel fiber reinforced concrete (SFRC). To simplify the assessment, only the ampl...

Ballast tamping is considered as an important maintenance process for railway infrastructures and has a large influence on the capacity of any railway networks. But optimizing the plan of that process is a complex problem with a high cost. This paper discusses optimizing tamping operations on ballasted tracks to improve the track geometry and reduce the total maintenance cost. A mathematical model for this problem in the literature is improved here by including the restriction on the resources (tools, workers and budget) in the model and including constant/variable values for track possession cost and available resources. The optimal solutions obtained for all instances are found by using the global optimization. Besides, a numerical study is presented to test and evaluate the model performance. The results show that the proposed model can be adopted by the infrastructure manager (IM) to make suitable tamping scheduling decisions under normal or private conditions; however, the private conditions lead to an increase of the final cost compared to that of the normal ones. Doi: 10.28991/cej-2020-03091601 Full Text: PDF

The first mention of the concept of an inconsistency measure for sets of formulas in first-order logic was given in 1978, but that paper presented only classifications for them. The first actual inconsistency measure with a numerical value was given in 2002 for sets of formulas in propositional logic. Since that time, researchers in logic and AI have developed a substantial theory of inconsistency measures. While this is an interesting topic from the point of view of logic, an important motivation for this work is also that some intelligent systems may encounter inconsistencies in their operation. This research deals primarily with propositional knowledge bases, that is, finite sets of propositional logic formulas. The goal of this paper is to extend the concept of inconsistency measure in a formal way to sets of formulas with the modal operators “necessarily” and “possibly” applied to propositional logic formulas. We use frames for the semantics, but in a way that is different from the way that frames are commonly used in modal logics, in order to facilitate measuring inconsistency. As a set of formulas may have different inconsistency measures for different frames, we define the concept of a standard frame that can be used for all finite sets of formulas in the language. We do this for two languages. The first language, AMPL, contains formulas where a prefix of operators is applied to a propositional logic formula. The second language, CMPL, adds connectives that can be applied to AMPL formulas in a limited way. We show how to extend propositional logic inconsistency measures to such sets of formulas. Finally, we define a new concept, weak inconsistency measure, and show how to compute it.

From September 15 up to September 20, 2019, the regular, 14th International Conference on Pulsed Lasers and Laser Applications – AMPL (abbreviation from the English name Atomic and Molecular Pulsed Lasers) was held in Tomsk. AMPL Conference (https://symp.iao.ru/ru/ampl), which is a periodic scientific event and takes place every two years in the city of Tomsk. The first conference was held in 1992, and all subsequent ones since 1995 took place on odd years. The AMPL conference is traditionally held in mid-September. Conference topics – fundamental issues of laser physics, physicochemical processes in active laser media, new types of lasers and laser systems, the use of lasers in science, technology, medicine, other fields of activity, problems of bringing laser devices and technologies to the market, as well as fundamental and applied issues on the creation and use of spontaneous radiation sources (excilamps). Along with Russian scientists, specialists, graduate students and students, representatives of near and far abroad regularly participate in the conference. The article provides a brief overview of past conferences, notes how the conference topics were expanded and modified in response to the challenges of gaining new knowledge in the field of photonics, as well as the needs of the laser equipment and technology market. An analysis of the current state of fundamental and applied research is given, and trends in the development of laser technologies are discussed.

The Software Product Line approach is well-known for the advantages it brings to the software-development field. However, single SPLs had been found to be inadequate in managing the variability of ...

This paper aims to present a mathematical model that describes the operation of an activated sludge system during one day. Such system is used in the majority of wastewater treatment plants and depends strongly on the dissolved oxygen, since it is a biological treatment. To guarantee the appropriate amount of dissolved oxygen, expensive aeration strategies are demanded, leading to high costs in terms of energy consumption. It was considered a typical domestic effluent as the wastewater to test the mathematical model and it was used the ASM1 to describe the activated sludge behaviour. An optimal control problem was formulated whose cost functional considers the trade-off between the minimization of the control variable herein considered (the dissolved oxygen) and the quality index that is the amount of pollution. The optimal control problem is treated as a nonlinear optimization problem after discretization by direct methods. The problem was then coded in the AMPL programming language in order to carry out numerical simulations using the NLP solver IPOPT from NEOS Server.

Orientador: Prof. Dr. Edmarcio Antonio Belati Coorientador: Prof. Dr. Ivo Chaves da Silva Júnior Coorientador: Prof. Dr. Leonardo Willer de Oliveira Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Energia, Santo André, 2022. O sistema elétrico brasileiro, tipicamente hidrotérmico, possui um perfil operacional formulado pela estratégia básica de otimização econômica, buscando determinar quais unidades geradoras termoelétricas e quais quantidades de energia cada uma deve produzir, a fim de suprir a demanda a custos mínimos. O custo do combustível das unidades termoelétricas no problema do despacho econômico (DE) pode ser modelado através de uma função quadrática, entretanto, deve considerar efeitos realísticos observados no funcionamento das unidades, sobretudo secundários, tais como: o efeito do ponto de válvula, operações com múltiplos combustíveis e zonas de operações proibitivas. Estes efeitos impõem ao problema de DE um maior nível de complexidade. Assim, o problema pode apresentar funções não lineares, não convexas, descontínuas e não diferenciáveis; logo, é essencial o emprego de ferramentas confiáveis de otimização, capazes de prover celeridade e precisão na obtenção de valores ótimos do problema abordado. Neste cenário, o presente trabalho tem como objetivo realizar o emprego de otimização clássica, implementada a partir de programação matemática e baseada em Programação Não Linear Inteira Mista. A modelagem proposta foi implementada em linguagem de programação AMPL. A otimização é alcançada utilizando o solucionador Knitro com o uso o algoritmo Branch-and-Bound para tratar as variáveis discretas. Nas análises, foram utilizados sistemas testes amplamente adotados pela literatura especializada, onde unidades termelétricas são modeladas considerando suas restrições operacionais. Os resultados obtidos, quando comparados com outros trabalhos que empregam diversas técnicas de otimização, demonstram que a técnica alcançou êxito considerável na otimização dos sistemas analisados, com resultados superiores ou próximos aos obtidos pelas técnicas abordadas no estudo comparativo, e com tempos de processamento satisfatórios. Um sistema teste foi proposto para analisar diversas restrições realísticas, com o objetivo de mensurar os erros introduzidos na solução, quando restrições realísticas são negligenciadas na modelagem do problema. Outra contribuição é o emprego de plataformas conhecidas e consolidadas na área de programação, o ambiente de programação AMPL e a ferramenta Knitro ao despacho econômico, a fim de aplicar suas potencialidades ao problema de otimização proposto. The Brazilian electrical system, typically hydrothermal, has an operational profile formulated by the basic strategy of economic optimization, seeking to determine which thermoelectric generating units and what amounts of energy each must produce, in order to supply the demand at minimum costs. The fuel cost of thermoelectric units in the problem of economic dispatch (DE), can be modeled through a quadratic function, however, it must consider realistic effects observed in the operation of the units, mainly secondary, such as: the effect of the valve point, multi-fuel operations and no-operation zones. These effects impose a higher level of complexity on the DE problem. Thus, the problem may present non-linear, non-convex, discontinuous and non-differentiable functions; therefore, it is essential to use reliable optimization tools, capable of providing speed and precision in obtaining optimal values for the problem addressed. In this scenario, the present work aims to perform the use of classical optimization, implemented from mathematical programming, and based on Non-Linear Mixed Integer Programming. The proposed modeling was implemented in the AMPL programming language. Optimization is achieved using the Knitro solver with the use of the Branch-and-Bound algorithm to handle the discrete variables. In the analyses, test systems widely adopted by the specialized literature were used, where thermoelectric units are modeled considering their operational restrictions. The results obtained, when compared with other works that employ different optimization techniques, demonstrate that the technique achieved considerable success in the optimization of the analyzed systems, with results superior or close to those obtained by the techniques addressed in the comparative study, and with satisfactory processing times. A test system was proposed to analyze several realistic constraints, in order to measure the errors introduced in the solution, when realistic constraints are neglected in the modeling of the problem. Another contribution is the use of well-known and consolidated platforms in the programming area, the AMPL programming environment and the Knitro tool for economic dispatch, in order to apply their potential to the proposed optimization problem.

The collection, transport, and final disposal of hospital waste may cause contamination and disease if improperly handled. Therefore, such residues are hazardous to the health of waste collectors. These wastes are generated by public agencies, such as hospitals, family health centers, dialysis centers, and private healthcare providers. In this study, a mixed-integer linear programming model is proposed for monthly customer scheduling and route assignment. The proposed approach was fulfilled according to customers’ collection frequency, truck capacity, and customer geographical location. The proposed mathematical model successfully balanced the number of customers and the workload during each day. The effectiveness of the proposed model was tested on data obtained from a waste collection company. The model has been implemented in AMPL language, and the performance of commercial solvers, GUROBI and CPLEX, to obtain an optimal solution were tested. The results show the efficiency of the proposed approach to balance the workload concerning previous scheduling is done ad hoc at the company. The use of the formulated model provides an automatic procedure that was previously performed manually. The methodology can be adapted to other companies with similar requirements.

In this work, the state estimation problem of electric power systems is represented through a mathematical programming approach. Initially, a non-linear mathematical model based on the classical method of weighted least squares is proposed to solve the state estimation problem for comparative purposes. Due to the inherent limitations that this classical model presents when dealing with errors in the set of measurements, a new mathematical model is proposed that can be used within an iterative procedure to reduce the impact of measurement errors on the estimated results. Several tests on a didactic 5-bus power system and IEEE benchmark power test systems showed the effectiveness of the proposed approach which achieved better results than the proposed classical state estimation model. The non-linear programming models proposed in this paper are implemented in the mathematical modeling language AMPL. Additionally, to validate the results of the proposed methodologies, the power system operation points are compared with the results obtained using the Matpower simulation package. The results allowed concluding that the proposed mathematical models can be successfully applied to perform state estimation studies in power systems.

Submitted by Leonardo Henrique Faria Macedo Possagnolo (lhfm.possagnolo@unesp.br) on 2021-10-28T16:40:21Z No. of bitstreams: 1 Ref1.pdf: 1483245 bytes, checksum: 9a11ddd963e395f76adc040b120825ac (MD5) Approved for entry into archive by Raiane da Silva Santos (raiane.santos@unesp.br) on 2021-11-11T18:40:11Z (GMT) No. of bitstreams: 1 macedo_lh_posprint_ilha_optimal.pdf: 1483245 bytes, checksum: 9a11ddd963e395f76adc040b120825ac (MD5) Made available in DSpace on 2021-11-11T18:40:11Z (GMT). No. of bitstreams: 1 macedo_lh_posprint_ilha_optimal.pdf: 1483245 bytes, checksum: 9a11ddd963e395f76adc040b120825ac (MD5) Previous issue date: 2021-09-29 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) This paper presents a new mixed-integer linear programming model for the optimal restoration of active distribution networks during permanent fault events considering not only network reconfiguration but also the islanded operation of distributed generation, thereby giving rise to the formation of microgrids. To that end, the proposed approach accounts for both the black-start capacity of generators and the connection of multiple generators to the same microgrid. Moreover, voltage control devices such as substations on-load tap changers, voltage regulators, and capacitor banks are also considered in the formulation. The model is driven by the minimization of the out-of-service load after single or multiple faults in the network using the minimum number of switching operations and modifications in the statuses of the voltage control devices. The proposed model is implemented in the mathematical modeling language AMPL and solved with the CPLEX solver. Tests are conducted using a 53-node distribution system considering different fault locations. Numerical results show the relevant effect of microgrid formation and voltage control in the restoration process. Simulations also prove the effective performance of the proposed approach in terms of computation time. Postprint Universidade Estadual Paulista Universidad de Castilla-La Mancha CAPES: 001 CNPq: 305852/2017-5 FAPESP: 2015/21972-6 FAPESP: 2018/20355-1 FAPESP: 2019/19632-3 Ministry of Science, Innovation and Universities of Spain: RTI2018-096108-A-I00 Ministry of Science, Innovation and Universities of Spain: RTI2018-098703-B-I00 Universidad de Castilla-La Mancha: 2021-GRIN-30952

This paper presents a methodology for sizing and operating microgrids using an energy management system (EMS) strategy embedded in the software HOMER Pro. The proposed EMS-based strategy, represented by a mixed-integer linear model, determines the optimal day-ahead operation of a grid-connected microgrid, which considers photovoltaic generation, battery storage system, and energy purchases and sales from/to the grid while minimizing the total operational costs. The integration of the optimal EMS-based dispatch strategy to HOMER Pro is done through the AMPL API for Matlab and the Matlab Link module. The proposed methodology was tested using real data from the CampusGrid microgrid that will be deployed at the UNICAMP campus. Results show that the proposed strategy presents economical advantages over the default dispatch strategies provided by HOMER.

Microgrids (MGs) are considered a reliable solution for the integration of a high level of intermittent distributed energy resources. However, renewable energy generation has added complexity to the optimal energy management of MGs (OEMMs) due to its high degree of uncertainty. As a result, the development of efficient models for handling these uncertainties is essential. As a result, a hybrid stochastic/information gap decision theory (IGDT) based model is proposed for the OEMMs. For that purpose, firstly, a two-stage stochastic mixed-integer second-order conic programming model is presented by producing scenarios for the power generated by wind turbine and photovoltaic units. Then, the proposed model has become robust against active and reactive power demand uncertainties by the deployment of IGDT. Both stochastic and hybrid Stochastic/IGDT models are implemented in AMPL and they are solved by using the commercial solver CPLEX. Moreover, the power flow equations are included to guarantee the validity of the proposed models for real-world applications. A modified IEEE 33-bus test system with a high level of renewable energy integration is utilized as a test system. The results show that the hybrid stochastic/IGDT model can efficiently cope with the uncertainties associated with renewable energy generation and electric demand.

In the coming years, several transformations in the transport sector are expected, associated with the increase in electric vehicles (EVs). These changes directly impact electrical distribution systems (EDSs), introducing new challenges in their planning and operation. One way to assist in the desired integration of this technology is to allocate EV charging stations (EVCSs). Efforts have been made towards the development of EVCSs, with the ability to recharge the vehicle at a similar time than conventional vehicle filling stations. Besides, EVs can bring environmental benefits by reducing greenhouse gas emissions. However, depending on the energy matrix of the country in which the EVs fleet circulates, there may be indirect emissions of polluting gases. Therefore, the development of this technology must be combined with the growth of renewable generation. Thus, this proposal aims to develop a mathematical model that includes EVs integration in the distribution system. To this end, a mixed-integer linear programming (MILP) model is proposed to solve the allocation problem of EVCSs including renewable energy sources. The model addresses the environmental impact and uncertainties associated with demand (conventional and EVs) and renewable generation. Moreover, an EV charging forecast method is proposed, subject to the uncertainties related to the driver's behavior, the energy required by these vehicles, and the state of charge of the EVs. The proposed model was implemented in the AMPL modelling language and solved via the commercial solver CPLEX. Tests with a 24-node system allow evaluating the proposed method application, The work was supported from FEDER funds through the Operational Programme for Competitiveness and Internationalization (COMPETE2020), under Project POCI-01-0145-FEDER-028983; by National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017(CENERGETIC), CEECIND/02814/2017, and UIDB/000760/2020. This Brazillian team was supported by the Brazilian institutions Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, CNPq (process 313047/2017–0) and São Paulo Research Foundation (FAPESP), grants 2015/21972–6, 2017/02831–8, 2018/23617–7, and 20018/08008–4 (CENERGETIC research project).