Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

ANN based day-ahead spinning reserve forecast for electricity market simulation

Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Efeito da manipulação lombar em pacientes com dor lombar aguda

Introdução: A manipulação vertebral é um procedimento de terapia manual realizada em alta velocidade, pequena amplitude e normalmente no final de movimento. Estudos recentes sugerem a manipulação da coluna lombar com efeitos directos nos mecanismos neurofisiológicos da dor assim como na funcionalidade. Objectivo: Avaliar os efeitos, na dor e na funcionalidade, da manipulação lombar, em pacientes com dor lombar aguda de origem mecânica, no dia seguinte à manipulação. Materiais e Métodos: Participaram neste estudo três pacientes de ambos os sexos, com idades compreendidas entre os 31 e 35 anos, com queixas de dor lombar há menos de oito dias e que apresentavam restrição e dor nos movimentos de flexão lombar. Foi utilizado o teste de Mitchell para identificar as vértebras lombares disfuncionais. Os instrumentos utilizados foram a escala numérica da dor (END) para avaliar a dor e o questionário de incapacidade lombar Roland Morris (QIRM) para avaliar a funcionalidade. Os utentes foram avaliados antes da manipulação e no dia seguinte à sua aplicação. Em cada paciente foi realizada apenas uma manipulação lombar. Resultados: No dia seguinte à intervenção os pacientes apresentaram diminuição da dor (6/10 vs 0/10; 5/10 vs 3/10; 4/10vs 1/10) e melhoria da funcionalidade (7/24 vs 1/24; 16/24 vs 9/24; 8/24 vs3/24). Conclusão: Com base nos resultados obtidos pode concluir-se que, nestes três casos, a manipulação lombar utilizada, teve efeitos positivos na redução da dor e no aumento da funcionalidade.

Monitorização da fibrose quística na pediatria: estado basal e impacto da agudização respiratória

Introdução: O envolvimento respiratório é a principal causa de morbilidade e mortalidade na Fibrose Quística (FQ). Dados pediátricos sobre atividade física (AF), saturação periférica da oxi-hemoglobina (SpO2) e pico do fluxo da tosse (PFT) são escassos e não padronizados. Objetivos: Avaliar a função pulmonar (FP), AF, SpO2 e PFT, em crianças e adolescentes com FQ, no estado basal e em agudização (AR) e, na fase estável, avaliar a correlação entre as variáveis. Métodos: Realizou-se um estudo observacional prospetivo, com análise de espirometria, podometria, oximetria noturna e PFT, em condições basais. Na AR reavaliaram-se os mesmos parâmetros às 24-48 horas, 7, 15 e 30 dias, excetuando a AF aos 7 dias. Resultados: Avaliaram-se 8 doentes dos quais dois apresentaram um comprometimento ligeiro da FP e um moderado. A SpO2 foi de 96,2% [95,6; 96,6] e o número médio de passos/dia (NMP) foi de 6369 [4431; 10588]. Todos apresentaram valores do PFT inferiores ao percentil 5 para o género e idade (265 L/min [210; 290]). Apesar de não estatisticamente significativa, a correlação foi moderada entre FEV1 e SpO2 nocturna (rs =0,61; p=0,11); entre PFT e idade (rs=0,69; p=0,06); e entre PFT e capacidade vital forçada (CVF) (rs=0,54; p=0,17). Não se verificou correlação entre FEV1 e idade, NMP e PFT; e entre NMP e idade. No único caso de AR, à exceção da frequência respiratória, verificou-se a diminuição das variáveis às 24-48h; após 1 mês, a maioria das variáveis aproximou-se ou igualou os valores basais. Conclusão: Os resultados sugerem uma tendência para melhores valores de FEV1 corresponderem a melhores SpO2 noturnas e que, quanto maior a idade e a CVF, maior é o PFT. Não foi possível avaliar o impacto da AR por ter ocorrido apenas um caso.

Alright: a distinctive pathway of change from the 18th century to the present day

The origins of the vast majority of the words we use in contemporary English go back as far as Old or Middle English. In contrast, alright and all right in their present-day application appear to be the result of a more recent evolution, as there is no evidence of their use, not even in the two-word form, in the published fiction before the 18th century. Furthermore, there are not in the research literature, at least to my knowledge, any previous linguistic studies on this specific subject matter. The present article is simply an attempt to describe the various processes of diachronic change that brought about the emergence of alright.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

Otimização da Amostragem e Estudo de Viabilidade da Monitorização de Sondas na ETAR de Rabada

Mestrado em Engenharia Química - Tecnologias de Protecção Ambiental

Virtual Power Player Using Demand Response to Deal with Unexpected Low Wind Power Generation

Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

Energy resources management in three distinct time horizons considering a large variation in wind power

The intensive use of distributed generation based on renewable resources increases the complexity of power systems management, particularly the short-term scheduling. Demand response, storage units and electric and plug-in hybrid vehicles also pose new challenges to the short-term scheduling. However, these distributed energy resources can contribute significantly to turn the shortterm scheduling more efficient and effective improving the power system reliability. This paper proposes a short-term scheduling methodology based on two distinct time horizons: hour-ahead scheduling, and real-time scheduling considering the point of view of one aggregator agent. In each scheduling process, it is necessary to update the generation and consumption operation, and the storage and electric vehicles status. Besides the new operation condition, more accurate forecast values of wind generation and consumption are available, for the resulting of short-term and very short-term methods. In this paper, the aggregator has the main goal of maximizing his profits while, fulfilling the established contracts with the aggregated and external players.