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In this study a two-stage stochastic programming joint day-ahead energy and reserve scheduling model to address uncertainty in wind power generation is developed. Apart from the generation side, the demand side is also eligible as a reserve resource and is modeled through responsive load aggregations, as well as large industrial loads that directly participate in the scheduling procedure. The main contribution of this paper is the inclusion of a risk metric, namely the Conditional Value-at-Risk (CVaR), which renders a conceptually different resource scheduling framework. The proposed model is employed in order to analyze the behavior of energy and reserve scheduling by both generation and demand for a risk-averse Independent System Operator (ISO). To reach practical conclusions, the proposed methodology is tested on the real non-interconnected insular power system of Crete, Greece, which is characterized by a significant penetration of wind power generation.

Abstract This paper presents a new candidate method for on-line transient security assessment and enhancement based on Pattern Recognition techniques. Transient state variables are used as primary features and the classifier is obtained in two phases, through the combination of an optimum discriminant transformation together with a probabilistic procedure. The proposed security functions can be further refined by means of a second level classifier based on an optimal discriminant plane and using a weighted K nearest neighbour rule. Finally it is shown that this method provides also an efficient and simple tool for on-line preventive control. Extensive results obtained for several contingencies in the CIGRE test system are presented and discussed.

The motivation for this work is the study and prediction of wind ramp events occurring in a large-scale wind farm located in the US Midwest. In this paper we introduce the SHRED framework, a stream-based model that continuously learns a discrete HMM model from wind power and wind speed measurements. We use a supervised learning algorithm to learn HMM parameters from discretized data, where ramp events are HMM states and discretized wind speed data are HMM observations. The discretization of the historical data is obtained by running the SAX algorithm over the first order variations in the original signal. SHRED updates the HMM using the most recent historical data and includes a forgetting mechanism to model natural time dependence in wind patterns. To forecast ramp events we use recent wind speed forecasts and the Viterbi algorithm, that incrementally finds the most probable ramp event to occur.

Abstract The European Union (EU) performed a comprehensive evaluation of nature conservation directives (the so-called “Fitness check”), including public consultations which provided an opportunity to characterize the perspectives of different stakeholders on the links between biodiversity conservation and energy policy. Through content analysis, all the information related to the energy sector produced during the Fitness check was screened. The overall perception was that, compared to other policies, the EU energy policy generally did not support the objectives of the Nature Directives, with identified threats for biodiversity coming from specific activities and policy initiatives. Respondents from the energy sector recognized that the implementation of the Directives brought some improvements (e.g. improved planning of grid developments, collaboration between the energy sector and NGOs) but a number of issues requiring improvement were identified, including (a) lack of coherence with energy policies, (b) need for cost-effective implementation, (c) need for more scientific knowledge and capacity building, and (d) need for clarifications over impact evaluation and compensatory measures. As a follow up of the Fitness check, the European Commission produced an Action Plan. From my perspective, this document should be closely scrutinized by the energy sector, as it provides opportunities to engage in different activities aiming towards a better use of scientific knowledge in decision-making, clarification of rules for procedures in the scope of impact assessment, effective mitigation of impacts on biodiversity, contribution to biodiversity gains, and higher social acceptance of the sector.

Abstract The building sector currently accounts for approximately 40 % of final energy consumption. In the near future, renewable energy driven heat pump systems will play an important role in the thermal management of buildings. The work described here deals with the effect of weather conditions as well as operational characteristics on the energy and economic performances of a solar PV powered air conditioning unit (ACU) with a battery system (PBAS) based on numerical and experimental investigations. The experiments were carried out to test the developed TRNSYS model. In the assessment, various performance indicators were used while a novel performance indicator, the so-called annual grid independence ratio, was also proposed. The simulated studies revealed that annual energy performance indicators (self-consumption, self-sufficiency, grid independence and energy conversion ratios) are greatly affected by climatic conditions and operational characteristics. Besides, the economic analysis has shown that the net present value and the energy consumption profiles or diverging values for state of charges are directly proportional for the hottest (Seville) climate. However, they are inversely proportional for the coldest (Stockholm) climate for the considered PBAS configuration (PV-2.5 kWp, ACU-2.52 kW cooling and 2.84 kW heating, batteries-9.6 kW h) under the selected economic status of the sites.

Exposure to cold spells is associated with mortality. However, little is known about the global mortality burden of cold spells.A three-stage meta-analytical method was used to estimate the global mortality burden associated with cold spells by means of a time series dataset of 1960 locations across 59 countries (or regions). First, we fitted the location-specific, cold spell-related mortality associations using a quasi-Poisson regression with a distributed lag non-linear model with a lag period of up to 21 days. Second, we built a multivariate meta-regression model between location-specific associations and seven predictors. Finally, we predicted the global grid-specific cold spell-related mortality associations during 2000-19 using the fitted meta-regression model and the yearly grid-specific meta-predictors. We calculated the annual excess deaths, excess death ratio (excess deaths per 1000 deaths), and excess death rate (excess deaths per 100 000 population) due to cold spells for each grid across the world.Globally, 205 932 (95% empirical CI [eCI] 162 692-250 337) excess deaths, representing 3·81 (95% eCI 2·93-4·71) excess deaths per 1000 deaths (excess death ratio), and 3·03 (2·33-3·75) excess deaths per 100 000 population (excess death rate) were associated with cold spells per year between 2000 and 2019. The annual average global excess death ratio in 2016-19 increased by 0·12 percentage points and the excess death rate in 2016-19 increased by 0·18 percentage points, compared with those in 2000-03. The mortality burden varied geographically. The excess death ratio and rate were highest in Europe, whereas these indicators were lowest in Africa. Temperate climates had higher excess death ratio and rate associated with cold spells than other climate zones.Cold spells are associated with substantial mortality burden around the world with geographically varying patterns. Although the number of cold spells has on average been decreasing since year 2000, the public health threat of cold spells remains substantial. The findings indicate an urgency of taking local and regional measures to protect the public from the mortality burdens of cold spells.Australian Research Council, Australian National Health and Medical Research Council, EU's Horizon 2020 Project Exhaustion.

ScopeThis study was designed to evaluate the influence of ethanol on the bioavailability of blackberry anthocyanins.Methods and resultsA total of 18 participants were recruited to consume 250 mL of a blackberry puree (650 mg of anthocyanins) without (BBP) or with 12% ethanol (BBP 12%). Venous blood was collected from participants at baseline and at 15, 30, 60, and 120 min after puree ingestion. Urine samples were collected at baseline and at 120 min. Plasma and urine concentration of anthocyanins and anthocyanin conjugates were quantified by HPLC‐DAD. Methyl‐cyanidin‐glucuronide (Me‐Cy‐Glucr) and 3′‐methyl‐cyanidin‐3‐glucoside (3′‐Me‐Cy3glc) were the main anthocyanin conjugates detected in all plasma and urine samples. Urinary concentration of these anthocyanin conjugates were positively correlated with their plasma concentration. Ethanol increased plasma Cmax of Me‐Cy‐Glucr and 3′‐Me‐Cy3glc. Participants were then stratified according to their body mass index (BMI) and body fat mass. After BBP consumption, plasma Cmax of Me‐Cy‐Glucr and 3′‐Me‐Cy3glc tended to be decreased in overweight/obese participants, in comparison to normal weight participants. The increase on plasma Cmax of Me‐Cy‐Glucr and 3′‐Me‐Cy3glc induced by ethanol was more pronounced in the group of overweight/obese participants.ConclusionsEthanol seems to enhance Cy3glc metabolism that appears to be compromised in overweight and obese individuals.