A simulation tool for demand response programs implementation

The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

Using demand response to deal with unexpected low wind power generation in the context of smart grid

Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. 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 aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

Energy and reserve provision dispatch considering distributed generation and demand response

In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

Particle swarm optimization applied to integrated demand response resources scheduling

The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

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.

Cellular uptake of BCG-loaded chitosan microparticles and in vivo evaluation of immune response following intranasal immunisation

Attenuated Mycobacterium bovis bacillus Calmette-Guérin (BCG) is the only currently available vaccine against tuberculosis. It is highly effective in pre-exposure immunisation against TB in children when administered by subcutaneous route to newborns. However, it does not provide permanent protection in adults. In this work, polymeric chitosan-alginate microparticles have been evaluated as potential nasal delivery systems and mucosal adjuvants for live attenuated BCG. Chitosan (CS) has been employed as adjuvant and mucosal permeation-enhancer, and, together with alginate (ALG), as additive to enhance BCG-loaded microparticles (MPs) cellular uptake in a human monocyte cell line, by particle surface modification. The most suitable particles were used for vaccine formulation and evaluation of immune response following intranasal immunisation of BALB/c mice.

Influence of environmental temperature and humidity on the acute ventilatory response to exercise in asthmatic adolescents

Asthma is a chronic inflammatory disorder of the respiratory airways affecting people of all ages, and constitutes a serious public health problem worldwide (6). Such a chronic inflammation is invariably associated with injury and repair of the bronchial epithelium known as remodelling (11). Inflammation, remodelling, and altered neural control of the airways are responsible for both recurrent exacerbations of asthma and increasingly permanent airflow obstruction (11, 29, 34). Excessive airway narrowing is caused by altered smooth muscle behaviour, in close interaction with swelling of the airway walls, parenchyma retractile forces, and enhanced intraluminal secretions (29, 38). All these functional and structural changes are associated with the characteristic symptoms of asthma – cough, chest tightness, and wheezing –and have a significant impact on patients’ daily lives, on their families and also on society (1, 24, 29). Recent epidemiological studies show an increase in the prevalence of asthma, mainly in industrial countries (12, 25, 37). The reasons for this increase may depend on host factors (e.g., genetic disposition) or on environmental factors like air pollution or contact with allergens (6, 22, 29). Physical exercise is probably the most common trigger for brief episodes of symptoms, and is assumed to induce airflow limitations in most asthmatic children and young adults (16, 24, 29, 33). Exercise-induced asthma (EIA) is defined as an intermittent narrowing of the airways, generally associated with respiratory symptoms (chest tightness, cough, wheezing and dyspnoea), occurring after 3 to 10 minutes of vigorous exercise with a maximal severity during 5 to 15 minutes after the end of the exercise (9, 14, 16, 24, 33). The definitive diagnosis of EIA is confirmed by the measurement of pre- and post-exercise expiratory flows documenting either a 15% fall in the forced expiratory volume in 1 second (FEV1), or a ≥15 to 20% fall in peak expiratory flow (PEF) (9, 24, 29). Some types of physical exercise have been associated with the occurrence of bronchial symptoms and asthma (5, 15, 17). For instance, demanding activities such as basketball or soccer could cause more severe attacks than less vigorous ones such as baseball or jogging (33). The mechanisms of exercise-induced airflow limitations seem to be related to changes in the respiratory mucosa induced by hyperventilation (9, 29). The heat loss from the airways during exercise, and possibly its post-exercise rewarming may contribute to the exercise-induced bronchoconstriction (EIB) (27). Additionally, the concomitant dehydration from the respiratory mucosa during exercise leads to an increased interstitial osmolarity, which may also contribute to bronchoconstriction (4, 36). So, the risk of EIB in asthmatically predisposed subjects seems to be higher with greater ventilation rates and the cooler and drier the inspired air is (23). The incidence of EIA in physically demanding coldweather sports like competitive figure skating and ice hockey has been found to occur in up to 30 to 35% of the participants (32). In contrast, swimming is often recommended to asthmatic individuals, because it improves the functionality of respiratory muscles and, moreover, it seems to have a concomitant beneficial effect on the prevalence of asthma exacerbations (14, 26), supporting the idea that the risk of EIB would be smaller in warm and humid environments. This topic, however, remains controversial since the chlorified water of swimming pools has been suspected as a potential trigger factor for some asthmatic patients (7, 8, 20, 21). In fact, the higher asthma incidence observed in industrialised countries has recently been linked to the exposition to chloride (7, 8, 30). Although clinical and epidemiological data suggest an influence of humidity and temperature of the inspired air on the bronchial response of asthmatic subjects during exercise, some of those studies did not accurately control the intensity of the exercise (2, 13), raising speculation of whether the experienced exercise overload was comparable for all subjects. Additionally, most of the studies did not include a control group (2, 10, 19, 39), which may lead to doubts about whether asthma per se has conditioned the observed results. Moreover, since the main targeted age group of these studies has been adults (10, 19, 39), any extrapolation to childhood/adolescence might be questionable regarding the different lung maturation. Considering the higher incidence of asthma in youngsters (30) and the fact that only the works of Amirav and coworkers (2, 3) have focused on this age group, a scarcity of scientific data can be identified. Additionally, since the main environmental trigger factors, i.e., temperature and humidity, were tested separately (10, 28, 39) it would be useful to analyse these two variables simultaneously because of their synergic effect on water and heat loss by the airways (31, 33). It also appears important to estimate the airway responsiveness to exercise within moderate environmental ranges of temperature and humidity, trying to avoid extreme temperatures and humidity conditions used by others (2, 3). So, the aim of this study was to analyse the influence of moderate changes in air temperature and humidity simultaneously on the acute ventilatory response to exercise in asthmatic children. To overcome the above referred to methodological limitations, we used a 15 minute progressive exercise trial on a cycle ergometer at 3 different workload intensities, and we collected data related to heart rate, respiratory quotient, minute ventilation and oxygen uptake in order to ensure that physiological exercise repercussions were the same in both environments. The tests were done in a “normal” climatic environment (in a gymnasium) and in a hot and humid environment (swimming pool); for the latter, direct chloride exposition was avoided.

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

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

A hybrid MLS technique for room impulse response estimation

The measurement of room impulse response (RIR) when there are high background noise levels frequently means one must deal with very low signal-to-noise ratios (SNR). if such is the case, the measurement might yield unreliable results, even when synchronous averaging techniques are used. Furthermore, if there are non-linearities in the apparatus or system time variances, the final SNR can be severely degraded. The test signals used in RIR measurement are often disturbed by non-stationary ambient noise components. A novel approach based on the energy analysis of ambient noise - both in the time and in frequency - was considered. A modified maximum length sequence (MLS) measurement technique. referred to herein as the hybrid MLS technique, was developed for use in room acoustics. The technique consists of reducing the noise energy of the captured sequences before applying the averaging technique in order to improve the overall SNRs and frequency response accuracy. Experiments were conducted under real conditions with different types of underlying ambient noises. Results are shown and discussed. Advantages and disadvantages of the hybrid MLS technique over standard MLS technique are evaluated and discussed. Our findings show that the new technique leads to a significant increase in the overall SNR. (C) 2008 Elsevier Ltd. All rights reserved.

FASL polymorphism is associated with response to bacillus Calmette-Guérin immunotherapy in bladder cancer

Objective Deregulation of FAS/FASL system may lead to immune escape and influence bacillus Calmette-Guérin (BCG) immunotherapy outcome, which is currently the gold standard adjuvant treatment for high-risk non–muscle invasive bladder tumors. Among other events, functional promoter polymorphisms of FAS and FASL genes may alter their transcriptional activity. Therefore, we aim to evaluate the role of FAS and FASL polymorphisms in the context of BCG therapy, envisaging the validation of these biomarkers to predict response. Patients and methods DNA extracted from peripheral blood from 125 patients with bladder cancer treated with BCG therapy was analyzed by Polymerase Chain Reaction—Restriction Fragment Length Polymorphism for FAS-670 A/G and FASL-844 T/C polymorphisms. FASL mRNA expression was analyzed by real-time Polymerase Chain Reaction. Results Carriers of FASL-844 CC genotype present a decreased recurrence-free survival after BCG treatment when compared with FASL-844 T allele carriers (mean 71.5 vs. 97.8 months, P = 0.030) and have an increased risk of BCG treatment failure (Hazard Ratio = 1.922; 95% Confidence Interval: [1.064–3.471]; P = 0.030). Multivariate analysis shows that FASL-844 T/C and therapeutics scheme are independent predictive markers of recurrence after treatment. The evaluation of FASL gene mRNA levels demonstrated that patients carrying FASL-844 CC genotype had higher FASL expression in bladder tumors (P = 0.0027). Higher FASL levels were also associated with an increased risk of recurrence after BCG treatment (Hazard Ratio = 2.833; 95% Confidence Interval: [1.012–7.929]; P = 0.047). FAS-670 A/G polymorphism analysis did not reveal any association with BCG therapy outcome. Conclusions Our results suggest that analysis of FASL-844 T/C, but not FAS-670 A/G polymorphisms, may be used as a predictive marker of response to BCG immunotherapy.