Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

A new wind farm in Santiago Island, cape verde - simulation and economic studies

Ensuring sustainable development conditions is presently world widely recognized as a critically important goal. This makes the use of electricity generation technologies based on renewable energy sources very relevant. Developing countries depend on an adequate availability of electrical energy to assure economic progress and are usually characterized by a high increase in electricity consumption. This makes sustainable development a huge challenge but it can also be taken as an opportunity, especially for countries which do not have fossil resources. This paper presents a study concerning the expansion of an already existent wind farm, located in Praia, the capital of Cape Verde Republic. The paper includes results from simulation studies that have been undertaken using PSCAD software and some economic considerations.

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.

Estudo da implementação de uma central hídrica reversível na Ilha Terceira

Dissertação de Mestrado em Engenharia e Gestão de Sistemas de Água.

Caracterização do potencial eólico urbano: o caso de Lisboa

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Edificações

Fuzzy Monte Carlo model for transmission power systems reliability based decision making

This thesis presents the Fuzzy Monte Carlo Model for Transmission Power Systems Reliability based studies (FMC-TRel) methodology, which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states. This is followed by a remedial action algorithm, based on Optimal Power Flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. For the system states that cause load curtailment, an optimization approach is applied to reduce the probability of occurrence of these states while minimizing the costs to achieve that reduction. This methodology is of most importance for supporting the transmission system operator decision making, namely in the identification of critical components and in the planning of future investments in the transmission power system. A case study based on Reliability Test System (RTS) 1996 IEEE 24 Bus is presented to illustrate with detail the application of the proposed methodology.

Risk Analysis and Behavior of Electricity Portfolio Aggregator

The scope of this paper is to adapt the standard mean-variance model of Henry Markowitz theory, creating a simulation tool to find the optimal configuration of the portfolio aggregator, calculate its profitability and risk. Currently, there is a deep discussion going on among the power system society about the structure and architecture of the future electric system. In this environment, policy makers and electric utilities find new approaches to access the electricity market; this configures new challenging positions in order to find innovative strategies and methodologies. Decentralized power generation is gaining relevance in liberalized markets, and small and medium size electricity consumers are also become producers (“prosumers”). In this scenario an electric aggregator is an entity that joins a group of electric clients, customers, producers, “prosumers” together as a single purchasing unit to negotiate the purchase and sale of electricity. The aggregator conducts research on electricity prices, contract terms and conditions in order to promote better energy prices for their clients and allows small and medium customers to benefit improved market prices.

Neural networks for condition monitoring of wind turbines gearbox

Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.

Wind resource modelling in complex terrain using different mesoscale–microscale coupling techniques

Wind resource evaluation in two sites located in Portugal was performed using the mesoscale modelling system Weather Research and Forecasting (WRF) and the wind resource analysis tool commonly used within the wind power industry, the Wind Atlas Analysis and Application Program (WAsP) microscale model. Wind measurement campaigns were conducted in the selected sites, allowing for a comparison between in situ measurements and simulated wind, in terms of flow characteristics and energy yields estimates. Three different methodologies were tested, aiming to provide an overview of the benefits and limitations of these methodologies for wind resource estimation. In the first methodology the mesoscale model acts like “virtual” wind measuring stations, where wind data was computed by WRF for both sites and inserted directly as input in WAsP. In the second approach, the same procedure was followed but here the terrain influences induced by the mesoscale model low resolution terrain data were removed from the simulated wind data. In the third methodology, the simulated wind data is extracted at the top of the planetary boundary layer height for both sites, aiming to assess if the use of geostrophic winds (which, by definition, are not influenced by the local terrain) can bring any improvement in the models performance. The obtained results for the abovementioned methodologies were compared with those resulting from in situ measurements, in terms of mean wind speed, Weibull probability density function parameters and production estimates, considering the installation of one wind turbine in each site. Results showed that the second tested approach is the one that produces values closest to the measured ones, and fairly acceptable deviations were found using this coupling technique in terms of estimated annual production. However, mesoscale output should not be used directly in wind farm sitting projects, mainly due to the mesoscale model terrain data poor resolution. Instead, the use of mesoscale output in microscale models should be seen as a valid alternative to in situ data mainly for preliminary wind resource assessments, although the application of mesoscale and microscale coupling in areas with complex topography should be done with extreme caution.

Escalonamento de geradores térmicos com integração de produção eólica: uma abordagem baseada em programação inteira mista

A alta e crescente participação da energia eólica na matriz da produção traz grandes desafios aos operadores do sistema na gestão da rede e planeamento da produção. A incerteza associada à produção eólica condiciona os processos de escalonamento e despacho económico dos geradores térmicos, uma vez que a produção eólica efetiva pode ser muito diferente da produção prevista. O presente trabalho propõe duas metodologias de otimização do escalonamento de geradores térmicos baseadas em Programação Inteira Mista. Pretende-se encontrar soluções de escalonamento que minimizem as influências negativas da integração de energia eólica no sistema elétrico. Inicialmente o problema de escalonamento de geradores é formulado sem considerar a integração da energia eólica. Posteriormente foi considerada a penetração da energia eólica no sistema elétrico. No primeiro modelo proposto, o problema é formulado como um problema de otimização estocástico. Nesta formulação todos os cenários de produção eólica são levados em consideração no processo de otimização. No segundo modelo, o problema é formulado como um problema de otimização determinística. Nesta formulação, o escalonamento é feito para cada cenário de produção eólica e no fim determina-se a melhor solução por meio de indicadores de avaliação. Foram feitas simulações para diferentes níveis de reserva girante e os resultados obtidos mostraram que a alta participação da energia eólica na matriz da produção põe em causa a segurança e garantia de produção devido às características volátil e intermitente da produção eólica e para manter os mesmos níveis de segurança é preciso dispor no sistema de capacidade reserva girante suficiente capaz de compensar os erros de previsão.

Protection of interconnected wind turbines against lightning effects: overvoltages and electromagnetic transientes study

This paper is concerned with direct or indirect lightning strokes on wind turbines, studying overvoltages and electromagnetic transients. As wind power generation undergoes rapid growth, lightning damages involving wind turbines have come to be regarded with more attention. With the aim of providing further insights into the lightning protection of wind turbines, describing the transient behavior in an accurate way, the restructured version (RV) of the electromagnetic transients program (EMTP) is used in this paper. A new case study is presented with two interconnected wind turbines, considering a direct lightning stroke to the blade or considering that lightning strikes the soil near a tower. Comprehensive computer simulations with EMTP-RV are presented and conclusions are duly drawn.

Simulation of a-Si PV system grid connected by boost and inverter

This paper is about a PV system connected to the electric grid by power electronic converters, using classical PI controller. The modelling for the converters emulates the association of a DC-DC boost with a two-level power inverter (TwLI) or three-level power inverter (ThLI) in order to follow the performance of a testing experimental system. Pulse width modulation (PWMo) by sliding mode control (SMCo) associated with space vector modulation (SVMo) is applied to the boost and the inverter. The PV system is described by the five parameters equivalent circuit. Parameter identification and simulation studies are performed for comparison with the testing experimental system.

Simulation of a-Si PV system linked to the grid by DC boost and three-level inverter under cloud scope

This paper is about a PV system linked to the electric grid through power converters under cloud scope. The PV system is modeled by the five parameters equivalent circuit and a MPPT procedure is integrated into the modeling. The modeling for the converters models the association of a DC-DC boost with a three-level inverter. PI controllers are used with PWM by sliding mode control associated with space vector modulation controlling the booster and the inverter. A case study addresses a simulation to assess the performance of a PV system linked to the electric grid. Conclusions regarding the integration of the PV system into the electric grid are presented. © IFIP International Federation for Information Processing 2015.

A method to correct the flow distortion of offshore wind data using CFD simulation and experimental wind tunnel tests

The assessment of wind energy resource for the development of deep offshore wind plants requires the use of every possible source of data and, in many cases, includes data gathered at meteorological stations installed at islands, islets or even oil platforms—all structures that interfere with, and change, the flow characteristics. This work aims to contribute to the evaluation of such changes in the flow by developing a correction methodology and applying it to the case of Berlenga island, Portugal. The study is performed using computational fluid dynamic simulations (CFD) validated by wind tunnel tests. In order to simulate the incoming offshore flow with CFD models a wind profile, unknown a priori, was established using observations from two coastal wind stations and a power law wind profile was fitted to the existing data (a=0.165). The results show that the resulting horizontal wind speed at 80 m above sea level is 16% lower than the wind speed at 80 m above the island for the dominant wind direction sector.