LMP triggered real time demand response events

Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

The role of demand response in future power systems

Power systems are planed and operated according to the optimization of the available resources. Traditionally these tasks were mostly undertaken in a centralized way which is no longer adequate in a competitive environment. Demand response can play a very relevant role in this context but adequate tools to negotiate this kind of resources are required. This paper presents an approach to deal with these issues, by using a multi-agent simulator able to model demand side players and simulate their strategic behavior. The paper includes an illustrative case study that considers an incident situation. The distribution company is able to reduce load curtailment due to load flexibility contracts previously established with demand side players.

Intelligent multi-player smart grid management considering distributed energy resources and demand response

The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.

Demsi - a demand response simulator in the context of intensive use of distributed generation

Demand response can play a very relevant role in future power systems in which distributed generation can help to assure service continuity in some fault situations. This paper deals with the demand response concept and discusses its use in the context of competitive electricity markets and intensive use of distributed generation. The paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes using a realistic network simulation based on PSCAD. Demand response opportunities are used in an optimized way considering flexible contracts between consumers and suppliers. A case study evidences the advantages of using flexible contracts and optimizing the available generation when there is a lack of supply.

Ancillary services market clearing simulation: a comparison between deterministic and heuristic methods

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, 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. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Drug therapy complexity: the importance of pharmacotherapeutic follow-up

Nowadays, the phenomenon of population ageing represents an worldwide problem, which assumes particular significance in Portugal. As they get older, individuals present more comorbidities and consequently consume an increasing number of drugs, which contributes to a growing drug therapy complexity. The institutionalized elders are particularly affected by this occurrence. Drug therapy complexity is defined as the conciliator of several characteristics of the pharmacotherapy and can affect patient’s safety and medication adherence. It can be measured with Medication Regimen Complexity Index (MRCI). This study aims to determine the drug therapy complexity of institutionalized elders in order to assess the need of pharmacotherapeutic follow-up.

Ética e responsabilidade social das organizações perante os Técnicos Oficiais de Contas

Mestrado em Contabilidade

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Astaxanthin production using Photobioreactors, investigation and scale up and an integrated solution for eutrophic lakes

TRANSCREA, Convertir la investigación y el conocimiento en innovación, propiedad intelectual e industrial. Terceira, 16 e 17 Fevereiro, 2011.

Start-up circuit for low-power indoor light energy harvesting applications

A start-up circuit, used in a micro-power indoor light energy harvesting system, is described. This start-up circuit achieves two goals: first, to produce a reset signal, power-on-reset (POR), for the energy harvesting system, and secondly, to temporarily shunt the output of the photovoltaic (PV) cells, to the output node of the system, which is connected to a capacitor. This capacitor is charged to a suitable value, so that a voltage step-up converter starts operating, thus increasing the output voltage to a larger value than the one provided by the PV cells. A prototype of the circuit was manufactured in a 130 nm CMOS technology, occupying an area of only 0.019 mm(2). Experimental results demonstrate the correct operation of the circuit, being able to correctly start-up the system, even when having an input as low as 390 mV using, in this case, an estimated energy of only 5.3 pJ to produce the start-up.

Demand response in future power systems management – a conceptual framework and simulation tool

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Assesing multileaf collimator effect on the build-up region using Monte Carlo method

Previous Monte Carlo studies have investigated the multileaf collimator (MLC) contribution to the build-up region for fields in which the MLC leaves were fully blocking the openings defined by the collimation jaws. In the present work, we investigate the same effect but for symmetric and asymmetric MLC defined field sizes (2×2, 4×4, 10×10 and 3×7 cm2). A Varian 2100C/D accelerator with 120-leaf MLC is accurately modeled fora6MVphoton beam using the BEAMnrc/EGSnrc code. Our results indicate that particles scattered from accelerator head and MLC are responsible for the increase of about 7% on the surface dose when comparing 2×2 and 10×10 cm2 fields. We found that the MLC contribution to the total build-up dose is about 2% for the 2×2 cm2 field and less than 1% for the largest fields.

Projecto de AVAC de um edifício com multiutilização

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica