Peak Consumption Research Articles

Comprehensive modeling and developing a software for salt cavern underground gas storage

• Comprehensive modeling of different elements of the underground gas storage in salt caverns was carried out. • Main parts of modeling are salt leaching process, gas injection and production process, modeling formation of hydrates and modeling of thermal behavior of the cavern. • This study presents the first integrated modeling in of the gas storage process in salt domes. • Comparison of the results of the proposed model with available data and other software in this field shows that the built software in this project can be confidently used for salt cavern gas storage purposes. Underground natural gas storage (UGS) is significant from strategic and technical points of view. Gas consumption in the cold seasons increases dramatically and makes gas supply a serious challenge. Underground natural gas storage as an effective and permanent strategy can meet the needs of different parts of the country at the peak of consumption. UGS is possible in different methods including storage of gas in depleted hydrocarbon reservoirs, aquifers, abandoned mines, and salt caverns. Because of technical and economic considerations including very low permeability and porosity of salt layers, a high delivery capacity, low surface requirements, and the presence of salt domes in different regions of the country, salt caverns are regarded as a suitable option for storage of natural gas. Due to the high cost of data acquisition in storage/production operations and difficulties of decision-making based on crude data, modeling of these processes can provide a thorough understanding before the operation. Also, a model can effectively contribute to the analysis of the available data from storage and production processes. To the best of our knowledge, this is the first modeling study conducted by integrating all main elements of the gas storage process in salt caverns. This modeling includes salt leaching, injection, and production of the gas, heat transfer effects, and hydrate formation. The most important elements of the process were modeled mathematically and the resulting equations were solved numerically using the most common programming languages including FORTRAN, Visual Basic, and MATLAB. The integrated model was then converted into a user-friendly software “UT-SCUGS”, which is believed to be the first software with the prescribed capabilities. The prediction made by UT-SCUGS was compared with the published data and the available storage/production software (SGSC and SALGAS), and a good agreement was observed in most respects.

A low-cost concurrent TSV test architecture with lossless test output compression scheme.

As the traditional IC design migrates to three-dimensional integrated circuits (3D-ICs) design, new challenges need to be considered carefully to solve its reliability and yield issues. 3D-ICs using through-silicon-vias (TSVs) can have latent defects such as resistive open and bridge defects, which are caused by the thermal stress during the fabrication process. These latent defects lead to the deterioration of the electrical performance of TSVs caused by an undesired increase in the resistance-capacitance (RC) delay. For this reason, various post-bond test methodologies have been studied to improve the reliability of 3D-ICs. Cost reduction in these TSV test architectures is also currently being studied by decreasing various factors such as hardware overhead, test time, and the peak current consumption. Usually, a single test-clock-period is required to determine whether the test result contains the defective TSV. When the test result of any TSVs fails, we use another single test-clock-period to classify its defect type. In this paper, we propose a new TSV test architecture to transfer the combined test output of the test result and the specific defect type to the pad during the single test-clock-period. Our proposed test architecture also provides a reliable block-based concurrent testing to optimize the test time by dividing the die into concurrent blocks. The experimental results showed that our proposed test architecture could reduce the test time and the hardware overhead substantially by ensuring that the reasonable peak power consumption for mass production was reasonable without the test quality being adversely affected.

Can temporal self-regulation theory and ‘sensitivity to reward’ predict binge drinking amongst university students in Australia?

ObjectivesMany university students consume more alcohol than their non-student peers, engaging in binge drinking episodes that increase the likelihood of experiencing both mental and physical harm. The aim of the current study was to test the predictive utility of temporal self-regulation theory (TST), and the additional construct of ‘sensitivity to reward’, in accounting for variance in binge drinking behavior amongst Australian university students. DesignA prospective correlational design with two time points one week apart. MethodsA convenience sample of 491 university students were recruited to an online survey. At time one, participants completed self-report measures assessing TST constructs (intention, behavior prepotency, self-regulation), as well as ‘sensitivity to reward’. One week later at time two, 392 participants (18–62 years, 76.8% female) completed an online account of their alcohol use over the previous seven days. ResultsUsing hierarchical multiple regression analyses, TST significantly predicted binge drinking behaviors (binge drinking episodes: R2 = 0.41, p < .001; peak consumption: R2 = 0.41, p < .001), with equally large effect sizes for both, f2 = 0.69. ‘Sensitivity to reward’ did not account for significant variance. Intention and behavioral prepotency independently predicted binge drinking behaviors with different components of behavioral prepotency predicting different behaviors. There were no moderation effects. ConclusionsResults indicated TST, incorporating deliberate and automatic processes, provided a good understanding of behavior. Behavior prepotency (habit, cues to action, past behavior) also impacted the two binge drinking behaviors differently. Finally, this study offers direction into future research regarding interventions surrounding habitual drinking behaviors whilst studying at university.

Are Aerobic Programs Similar in Design to Cardiac Rehabilitation Beneficial for Survivors of Stroke? A Systematic Review and Meta-Analysis.

BackgroundSurvivors of stroke face movement disability and increased cardiovascular disease and stroke risk. Treatment includes rehabilitation focused on functional movement with less emphasis on aerobic capacity. After rehabilitation, survivors of stroke must self‐manage activity with limited appropriate community programs. Lack of structured activity contributes to sedentary behavior. The objective of this systematic review and meta‐analysis is to review aerobic programs for stroke survivors similar in activity and dosage to cardiac rehabilitation programs to determine their efficacy for improving aerobic and walking capacity.Methods and ResultsPreferred Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines were used to review 5 databases. Group interventions for survivors of stroke with a primary aerobic component and dosage from 18 to 36 visits over 8 to 18 weeks (matching cardiac rehabilitation requirements in the United States) were included. The 6‐minute walk test, maximal oxygen consumption (VO2) peak, and walking speed were included as measures of aerobic capacity. Summary effect sizes and outcome measure mean differences were calculated for preintervention to postintervention, and summary effect sizes were calculated for preintervention to follow‐up. Activity type and initial 6‐minute walk test moderator analyses were performed. Nineteen studies with 23 eligible groups were selected. Survivors of stroke improved their composite aerobic capacity with an effect size of 0.38 (95% CI, 0.27–0.49). Studies including 6‐minute walk test demonstrated a pooled difference in means of 53.3 m (95% CI, 36.8–69.8 m). Follow‐up data were inconclusive.ConclusionsSurvivors of stroke benefit from aerobic programs with similar dosing to cardiac rehabilitation in the United States. The potential integration into existing programs could expand the community exercise options.

Aerobic Capacity of Preterm Children with Very Low Birth Weight at School Age and its Associated Factors

IntroductionRespiratory morbidities of preterm infants can cause significant ventilatory impairment thus compromising the aerobic capacity in childhood and adolescence. Therefore, the present study was conducted to evaluate the aerobic capacity in school age preterm children with VLBW and its associated factors. MethodsA cross-sectional study was conducted among preterm born with VLBW and term children, both aged 6–9 years. An individualized symptom-limited treadmill testing protocol performed aerobic capacity. Measured variables: oxygen pulse (PuO2), percentage of maximum heart rate for age (%HR max), tidal volume/inspiratory capacity ratio (TV/IC), oxygen consumption (VO2) peak, and the ratio of the anaerobic threshold of gas exchange to the predicted percentage of maximum VO2 (VO2@LA/%VO2 max.pred.) were compared between groups. Univariate and multiple linear regression analyses were used to determine the factors associated with aerobic capacity. ResultsThirty-four preterm and 32 term children were included. Similar VO2 peak and the other variables were observed. The development of bronchopulmonary dysplasia (BPD) and being obese/overweight was positively associated with %HR max. The Z-score for height/age and birth weight <1000g was positively associated with PuO2 and peak VO2, and negatively associated with overweight/obesity and female sex. ConclusionsAerobic capacity was similar in both groups. Sex, development of BPD, birth weight <1000g and factors related to body growth, such as Z-score for height/age and overweight/obesity, were associated with aerobic capacity in preterm children with VLBW.

Day-ahead electricity consumption optimization algorithms for smart homes

The electricity consumption optimization and the advanced tariff schemes are some of the key factors in the demand response programs, which target several aspects such as the minimization of the consumption peak, a reduced electricity bill, the reduction of the consumption, etc. By various incentives, the electricity consumers become more and more active, thus being able to change their consumption behavior as a consequence of the tremendous progress of IT&C and sensor technologies. In this paper, we propose four novel algorithms that are able to minimize the consumption peak for eleven complex smart homes with over three hundred appliances and eight roof-PhotoVoltaic (PV) systems connected to the Internet and smart meters which allow different resolutions for the consumption records. The four algorithms are executed in parallel and the best option is chosen for the day-ahead electricity consumption optimization, while the electricity generated by the PV systems is shared at the community level, further improving the results of the optimization algorithms. In addition, several Time-of-Use (ToU) tariffs are implemented to assess the electricity payment and verify the efficiency of the proposed algorithms.

AEROBIC FITNESS AND TYPE OF RECOVERY INFLUENCE POST-EXERCISE HEART RATE RECOVERY IN YOUNG WOMEN

This study aimed to analyze both influence of aerobic fitness and active recovery in heart rate (HR) reduction after maximum exercise (i.e. maximum incremental test) in untrained young women. Seventeen women were evaluated (23.88 ± 4.85 years), divided by the medium of peak of consumption of oxygen (30.80 mL.kg-1.min-1), in higher or lower aerobic fitness obtained during a maximum incremental test performed on a cycle ergometer. The post-exercise recovery was performed actively and passively, on two randomly non-consecutive days. It was noticed that HR at 6th and from the 6th to 10th min after the passive and active recovery, respectively, was lower in the higher aerobic fitness group, beyond that, the values of %HR reduction from the 6th to 10th min at 6th min after passive and active recovery, respectively, were higher in the higher aerobic fitness group. After active recovery, HR in 8th and 9th min and %HR reduction of the 8th to 10th min were lower and higher, respectively (p<0.05) than passive recovery in the lower aerobic fitness group. In short, the aerobic fitness influenced HR reduction after maximum exercise in untrained young women, mainly, after passive recovery. Besides that, the active recovery showed benefits in HR reduction in lower aerobic fitness group.

Domestic load management based on integration of MODE and AHP-TOPSIS decision making methods

The increasing in energy demand leads to wide range of blackout crises around the worldwide. Load management is represented as one of the most important solutions to balance the energy demand with the available generation resource. Dynamic and adaptive method is required to sort all multi-objective sets of optimal solutions of customer load scheduling. A multi-objective optimization differential evolution (MODE) algorithm in this paper is used to obtain a set of optimal customer load management by minimizing the energy cost and customer’s inconvenience simultaneously. The obtained optimal set of solutions are sorted from the best to the worst using multi-criteria decision making (MCDM) methods. An integration of analytic hierarchy process (AHP) and technique for order preferences by similarity to ideal solution (TOPSIS) are used as MCDM methods. The effect of different time slots on the given optimal solutions are addressed for real customer’s data of a typical household. Results of simulation indicate that the proposed method manages to realize energy cost saving of 44%, 44% and 32% for 1, 5 and 10 min time slots, respectively. Moreover, the peak load savings are 42%, 31% and 41% for 1, 5 and 10 min time slots, respectively. Furthermore, the results are validated by other approaches presented earlier in literature to support the findings of the proposed method. The proposed method provides superior saving for energy cost and peak consumption as well as maintains an acceptable range of customer inconvenience.

Modeling an Alternate Operational Ground Source Heat Pump for Combined Space Heating and Domestic Hot Water Power Sizing

This study developed an alternate operational control system for ground source heat pumps (GSHP), which was applied to determine combined space heating and domestic hot water (DHW) power equations at design temperature. A domestic GSHP with an alternate control system was implemented in a whole building simulation model following the heat deficiency for space heating based on degree minute counting. A simulated GSHP system with 200 L storage tank resulted in 13%–26% power reduction compared to the calculation of the same system with existing European standards, which required separate space heating and DHW power calculation. The periodic operation utilized the thermal mass of the building with the same effect in the case of light and heavy-weight building because of the very short cycle of 30 min. Room temperatures dropped during the DHW heating cycle but kept within comfort range. The developed equations predict the total power as a function of occupancy, peak and average DHW consumption with variations of 0%–2.2% compared to the simulated results. DHW heating added the total power in modern low energy buildings by 21%–41% and 13%–26% at design temperatures of −15 °C and −26 °C, respectively. Internal heat gains reduced the power so that the reduction effect compensated the effect of DHW heating in the case of a house occupied by three people. The equations could be used for power sizing of any heat pump types, which has alternate operation principle and hydronic heating system.

Involvement of Cardiorespiratory Capacity on the Acute Effects of Caffeine on Autonomic Recovery.

Background and objectives: As a result of ergogenic properties, caffeine has been increasingly taken prior to physical exercise, yet its effects on post-exercise recovery, considering the differences in the cardiorespiratory capacity of the individuals, has not yet been studied or fully elucidated. Optimizing the post-exercise recovery can convey advantages to physical activity practitioners. We evaluated the acute effects of caffeine on heart rate (HR) autonomic control recovery following moderate aerobic exercise in males with different cardiorespiratory capacities. Materials and Methods: We split young adult men into two groups based on their various oxygen consumption peaks (VO2 peak): (1) Higher VO2 (HO): Sixteen volunteers, peak VO2 > 42.46 mL/kg/min and (2) Low VO2 (LO): Sixteen individuals, VO2 < 42.46 mL/kg/min). The volunteers were submitted to placebo and caffeine protocols, which entailed 300 mg of caffeine or placebo (starch) in capsules, followed by 15 min of rest, 30 min of moderate exercise on a treadmill at 60% of the VO2 peak, followed by 60 min of supine recovery. Heart rate variability (HRV) indexes in the time and frequency domains were examined. Results: Effect of time for RMSSD (square root of the average of the square of the differences between normal adjacent RR intervals) and SDNN (standard deviation of all normal RR intervals recorded in a time interval) was achieved (p < 0.001). Significant adjustments were observed (rest versus recovery) at the 0 to 5th min of recovery from exercise for the LO during the placebo protocol and at the 5th at 10th min of recovery for the caffeine protocol. For the HO in both procedures we found significant alterations only at the 0 to 5th min of recovery. Conclusion: Caffeine delayed parasympathetic recovery from exercise in individuals with lower cardiorespiratory capacity.

Predictive Energy Control Strategy for Peak Shaving and Shifting Using BESS and PV Generation Applied to the Retail Sector

As is known, a reduction in CO 2 emissions is closely related to the improvement of energy efficiency and the increasing use of renewable energy sources in building stock due to its high contribution to worldwide energy consumption. The retail sector has become particularly interesting in this sense, because commercial buildings are no longer just places where a variety of services are offered to customers. In fact, they can be beacons of energy efficiency. In this paper, we propose a predictive energy control strategy that, through the combination of production and demand forecasting, can effectively shave and shift the peak consumption of shopping malls equipped with battery energy storage systems (BESS). The adopted optimization strategy takes into account the variability of electricity tariffs over time, as is customary in some European countries. The performed energy and economic simulations based on the experimental data collected in an Italian shopping mall clearly highlight the benefits in terms of energy and economic savings. Moreover, the reported results lead to the conclusion that BESS management, photovoltaic (PV) generation, and peak switch strategies can have a reasonable pay-back investment time even for buildings with a large energy demand.

Application of a systematic approach to improving the efficiency of power supply modes of the Republic of Crimea

The structure of the region’s energy supply is considered, the characteristics of all the major groups of electricity producers in the region, including thermal power plants, mobile gas turbine power plants, renewable energy sources, backup power sources, are presented. As tariffs in the transport problem under consideration, depending on the purpose of the calculations, it is proposed to use the averaged actual values in a given period of time according to the energy supplying organizations (the purpose of the calculations is to reduce the cost of production and transportation of electricity), and also conditional qualitative assessments - “fines” (The goal is to improve the environmental and reliability of the system as a whole). The influence of the generated power of solar power plants on the operation modes of the power system of the Crimea is investigated. A methodology has been developed to optimize the production of solar power plants that affect the reliability and quality of power supply. The calculation of different scenarios of energy supply of the Crimea carried out, including at peak and average modes of power consumption, with different variants of solar activity, the time of year, taking into account and without taking into account the energy sources under construction, repair works of sources in the off-season. Based on the results of the calculations, conclusions are made about the reliability of the power system in the region under different scenarios of power supply, as well as the need to use the power bridge for the flow of electricity from the mainland in both directions.

Dynamic Pricing in Smart Grids Under Thresholding Policies

Our ever-increasing reliance on electricity coupled with inefficient consumption has resulted in several economical and environmental threats. To curb these threats, smart grids are emerging. These improved power systems could potentially reduce the peak consumption and better match demand to supply, to produce both economical and environmental advantages. In this work, we consider two pricing problems in the smart grid, under a dynamic pricing model, where consumers follow threshold policies to schedule their power consumption. The first problem is to set the prices during the different time periods such that the peak demand is minimized. The second problem is to set the prices such that the power demand matches the supply. Firstly, we propose generic heuristics called GREEDY and SLIDING-WINDOW that are able to solve the two studied problems in addition to any other optimization problem, under the same model. Secondly, we provide theoretical analysis for the uniform-pricing approach in the context of peak-demand minimization. In addition, we propose optimal algorithms for the two optimization problems that can be used when the maximum deadline period of the power jobs is relatively small. Moreover, we conduct several experiments to evaluate the proposed algorithms and the uniform pricing approach on real data. Our experimental results showed that our proposed heuristics have a relatively low approximation ratio, and have the potential to provide a significant energy saving in many cases compared to the Time-of-Use (ToU) pricing. Furthermore, the experiments showed that while the uniform pricing has an acceptable approximation ratio in the average case, it leads to energy loss compared to the ToU pricing. Finally, the experiments demonstrated a tradeoff between optimality and speed.

Simulation of a solar absorption cooling system in Dohuk city of the Northern Iraq

ABSTRACTSince the last decade, the demand on electrical power has been increased rapidly in the Northern Iraq. This was due to the rapid development of the cities of the region after 2003. The power supply in this region only depends on fossil fuel and natural gas which in turn causes an increase in CO2 emissions, global warming, and other environmental problems. The peak of the electricity consumption in the Northern Iraq is during the end of spring until October owing to the hot weather conditions in this period. The aim of this work is to examine the feasibility of an absorption cooling system in a hot and dry region. For this purpose, this study was carried out using the climate conditions of Duhok city located in the North of Iraq by using the TRNSYS17 programs. The system consisted of single-effect solar-powered lithium bromide–water chiller absorption with 35.17 kW cooling capacity, which comprises an evacuated tube solar collector with an aperture space of 95 m2, collectors slope 30° from the horizontal. The capacity storage hot water storage tank is 3 m3. The air conditioning provided system supplied floor space of 270 m2. The average coefficient of performance of absorption chiller was found as 0.63.

Achieving energy resilience through smart storage of solar electricity at dwelling and community level

This paper empirically evaluates the extent of energy resilience achieved in a socially-deprived community in Oxford, through deployment of solar photovoltaic (PV) systems and smart batteries (internet enabled and controllable) across a cluster of 82 dwellings (households). The methodological approach comprised dwelling and household surveys, along with high frequency monitoring of household electricity consumption, solar PV generation, battery charge and discharge data. In the monitored households, average daily electricity consumption was found to be positively related with dwelling size, number of occupants and number of appliances used. Although 117 MWh of PV electricity was generated within a year across 74 dwellings, peak generation did not match peak consumption, demonstrating the need for battery storage. Home batteries were found to increase self-consumption of PV electricity and offset grid demand through discharge of stored PV electricity marginally at an average of 6%, depending on the size of the PV system, surplus PV electricity available and size of the battery. Aggregating solar generation and storage at a community level showed that peak grid electricity demand between 17:00 and 19:00 was reduced by 8% through the use of smart batteries across 74 dwellings. In future, a local energy sharing scheme could be developed, wherein not all dwellings would need to have solar PV systems, but rather have internet enabled batteries that could be monitored and controlled virtually.

Multi-Agent Recommendation System for Electrical Energy Optimization and Cost Saving in Smart Homes

The European Union Establishes that for the next few years, a cleaner and more efficient energy system should be used. In order to achieve this, this work proposes an energy optimization method that facilitates the achievement of these objectives. Existing technologies allow us to create a system that optimizes the use of energy in homes and offers some type of benefit to its residents. Specifically, this study has developed a recommendation system based on a multiagent system that allows to obtain consumption data from electronic devices in a home, obtain information on electricity prices from the Internet, and provide recommendations based on consumption patterns of users and electricity prices. In this way, the system recommends new hours in which to use the appliances, offering the economic benefit that it would propose recommendations for the user. In this way, it is possible to distribute and optimize the use of energy in homes and reduce the peaks in electricity consumption. The system provides encouraging results in order to resolve the problem proposed by the European Union by optimizing the use of energy among different hours of the day and saving money for the customer.

Temperature-induced aerobic scope and Hsp70 expression in the sea cucumber Holothuria scabra.

The Aerobic Scope (AS), which reflects the functional capacity for biological fitness, is a highly relevant proxy to determine thermal tolerance in various taxa. Despite the importance of this method, its implementation is often hindered, due to lacking techniques to accurately measure standard- (SMR) and maximal- (MMR) metabolic rates, especially in sluggish marine invertebrates with low oxygen consumption rates, such as sea cucumbers. In this study the AS concept was modified to define a Temperature-induced Aerobic Scope (TAS), based on metabolic rate changes due to temperature adjustments rather than traditionally used physical activity patterns. Consequentially, temperature dependent peak and bottom O2 consumption rates, defined as Temperature-induced Maximal- (TMMR) and Standard Metabolic Rates (TSMR), respectively, served as MMR and SMR alternatives for the sea cucumber Holothuria scabra. TMMR and TSMR were induced through acute temperature change (2°C per hour; 17–41°C) until critical warm (WTcrit) and cold (CTcrit) temperatures were reached, respectively. In addition, Hsp70 gene expression linked to respiration rates served as synergistic markers to confirm critical threshold temperatures. O2 consumption of H. scabra peaked distinctly at WTcrit of 38°C (TMMR = 33.2 ± 4.7 μgO2 g-1 h-1). A clear metabolic bottom line was reached at CTcrit of 22°C (TSMR = 2.2 ± 1.4 μgO2 g-1 h-1). Within the thermal window of 22–38°C H. scabra sustained positive aerobic capacity, with assumed optimal performance range between 29–31.5°C (13.85–18.7 μgO2 g-1 h-1). Between 39–41°C H. scabra decreased respiration progressively, while gene expression levels of Hsp70 increased significantly at 41°C, indicating prioritization of heat shock response (HSR) and homeostatic disruption. At the cold end (17–22°C) homeostatic disruption was visible through incrementally increasing energetic expenses to fuel basal maintenance costs, but no Hsp70 overexpression occurred. TMMR, TSMR and TAS proved to be reliable metrics, similar to the traditional energetic key parameters MMR, SMR and AS, to determine a specific aerobic performance window for the sluggish bottom dwelling species H. scabra. In addition, the linkage between respiration physiology and molecular defense mechanisms showed valuable analytical synergies in terms of mechanistic prioritization as response to thermal stress. Overall, this study will help to define lethal temperatures for aquaculture and to predict the effects of environmental stress, such as ocean warming, in H. scabra.

Behavior of the Two-Phase Gas-Liquid Flow at the Inlet of a Catalytic Reactor

The work was aimed at studying the behavior of the two-phase gas-liquid flow at the inlet pipe of a catalytic reactor. Apart from the classical approach using literature flow diagrams, methods of computational hydrodynamics were used for 3D simulation of the space propagation of phases in the pipeline. The results obtained demonstrated non-uniform distribution of the liquid phase through the outlet section of the pipeline and the time-unsteady mass consumption of the liquid phase. The maximal peak consumptions were ca. 3 times as high as the average values. With the data on the flow diagrams, the CFD simulation demonstrated that variations in the gas consumption within the range under study do not cause changes in the behavior of the two-phase flow but an increase in the gas consumption results in smoothening of the non-uniform distribution of the liquid phase at the outlet pipe. The data on the flow behavior are necessary for designing catalytic reactors to provide uniform propagation of the two-phase flow over the catalyst bed, for example, hydrotreatment reactors used in refineries.

Bottom-up modelling methodology for urban-scale analysis of residential space heating demand response

Several studies have indicated a potential to exploit the thermal inertia of individual residential buildings for demand response purposes using model predictive control and time-varying prices. However, studies that investigate the response obtained from applying these techniques to larger groups of buildings, and how this response affects the aggregated load profile, are needed. To enable such analysis, this paper presents a modelling methodology that enables bottom-up modelling of large groups of residential buildings using data from public building registers, weather measurements, and hourly smart-meter consumption data. The methodology is based on describing district heating consumption using a modified version of the building energy model described in ISO 13790 in combination with a model of the domestic hot water consumption, both of which are calibrated in a Bayesian statistical framework. To evaluate the performance of the methodology, it was used to establish models of 159 single-family houses within a residential neighbourhood located in the city of Aarhus, Denmark. The obtained bottom-up model of the neighbourhood was capable of predicting the aggregated district heating consumption in a previously unseen validation period with high accuracy: CVRMSE of 5.58% and NMBE of −1.39%. The model was then used to investigate the effectiveness of a simple price-based DR scheme with the objective of reducing fluctuations in district heating consumption caused by domestic hot water consumption peaks. The outcome of this investigation illustrates the usefulness of the modelling methodology for urban-scale analysis on demand response.

Optimal Design of Hybrid PV-Battery System in Residential Buildings: End-User Economics, and PV Penetration

This paper proposes an optimal design for hybrid grid-connected Photovoltaic (PV) Battery Energy Storage Systems (BESSs). A smart grid consisting of PV generation units, stationary Energy Storage Systems (ESSs), and domestic loads develops a multi-objective optimization algorithm. The optimization aims at minimizing the Total Cost of Ownership (TCO) and the Voltage Deviation (VD) while considering the direct and indirect costs for the prosumer, and the system stability with regard to intermittent PV generation. The optimal solution for the optimization of the PV-battery system sizing with regard to economic viability and the stability of operation is found while using the Genetic Algorithm (GA) with the Pareto front. In addition, a fuzzy logic-based controller is developed to schedule the charging and discharging of batteries while considering the technical and economic aspects, such as battery State of Charge (SoC), voltage profile, and on/off-peak times to shave the consumption peaks. Thus, a hybrid approach that combines a Fuzzy Logic Controller (FLC) and the GA is developed for the optimal sizing of the combined Renewable Energy Sources (RESs) and ESSs, resulting in reductions of approximately 4% and 17% for the TCO and the VD, respectively. Furthermore, a sensitivity cost-effectiveness analysis of the complete system is conducted to highlight and assess the profitability and the high dependency of the optimal system configuration on battery prices.