Peak Load Events Research Articles

Modelling the recovery time from peak loads in a full-scale horizontal flow wetland in Sicily

The aim of this study was to simulate the water flow and reactive transport of pollutants in a horizontal flow (HF) wetland to better understand the recovery time of the treatment performance for peak load events. For the simulation, the processes-based model HYDRUS and its Wetland Module is used. The system under investigation is the first stage of the 9-years old hybrid treatment wetland of a large retail store, located in Catania, Italy. For the calibration of the hydraulic model, the data of a tracer test was used. The data set of the systems is available for a seven year period including organic matter and ammonia nitrogen. The data was split into a standard event representing low loading conditions and determined peak load events with high loadings. The results show that the response time of the model correlates with the hydraulic retention time from the tracer experiment and indicates that higher peak load concentrations at the inlet of the system lead to a longer recovery time of the wetland.

Load distributions in the ice-structure interaction process in shallow water

Model-scale experiments were performed to explore the process of level ice interacting with a, in model-scale, ten-meter-wide inclined structure in shallow water. During each experiment, an initially intact ice sheet was pushed against the sloping structure, failed against it and accumulated into a grounded rubble pile in front of it. The strength of the model ice used in the experiments was varied. The spatial and temporal ice load distributions were measured at two scales: the structure was divided into ten identical segments along its waterline with the horizontal load on each segment measured, while the local pressure distributions were simultaneously measured with tactile sensors from two of the segments. This paper focuses on the relationships between the loads on different segments and the correlation between global and local loads. The load records of the individual segments during the whole experiment correlated with each other. The Pearson correlation coefficient for the load records of two neighboring segments was about 0.8, and for segments having a distance of 5 m or more, about 0.4. The magnitudes of both the maximum and the mean load on each segment were approximately equal. Even if the segment loads correlated during the whole experiment, the load records of the individual segments showed also transient ice load peaks, which did not correlate. These were used to define local peak load events and related local line loads, defined by dividing the magnitude of a peak load by its width in space. Roughly 2/3 of the local peak load events concentrated on one segment and only about 5% of them covered more than three segments. Narrow local peak load events caused the local line loads of the highest magnitude, with the magnitude and the relative frequency of the events increasing with the ice strength. Narrow events resulted in local line loads up to four times higher than the global line load, which was defined by dividing the total load on the structure by its width. The investigation of the local peak load events also showed that an inclined structure having a width of approximately 5 m (the ice thickness to structure width ratio of 1:100) appeared infinitely wide and gave similar results as a wider structure. Ice pressure measurements showed a line-like pressure distribution at the waterline of the structure with the weakest ice, whereas with stronger ice, zones of high ice pressure were observed at upper parts of the segments.

Optimal sizing of an AC‐coupled hybrid power system considering incentive‐based demand response

This study investigates the impact of incentive-based demand response on the optimal economic sizing of hybrid power systems for a remote area in South Australia. The hybrid power systems are modelled as AC-coupled system with various power generation and energy storage systems including diesel generators, solar photovoltaics, wind turbines, battery storages and flywheels. Operating reserve requirements are introduced to ensure a specified reliability with variable renewable energy generation and consumer loads. Incentive-based demand response is introduced to allow a reduction in customer loads, up to a maximum value, during peak load events. Customers receive a financial benefit as an incentive for the total demand response energy reduction. Active power operation of four different power system configurations is modelled over one year in hourly time steps. The study uses real data for customer demand, wind speed, solar insolation and ambient temperature profiles in a specific location. The hybrid power systems with demand response are optimised to minimise the system net present cost in project lifetime (20 years) using a particle swarm optimisation algorithm. Sensitivity analysis of levellised cost of energy for various values of the maximum demand response power and the incentive payments are also carried out.

Limit mechanisms for ice loads on inclined structures: Local crushing

This paper focuses on mechanisms that limit the sea ice loads on offshore structures. It introduces a probabilistic limit load model, which can be used to analyze peak ice load events and to estimate the maximum peak ice load values on a wide, inclined, offshore structure. The model is based on simple mechanical principles, and it accounts for a mixed-mode ice failure process that includes buckling and local crushing of ice. The model development is based on observations on two-dimensional combined finite-discrete element method simulations on the ice-structure interaction process. The paper also presents a numerical limit load algorithm, which is an extension of the probabilistic limit load model and capable of yielding a large number of stochastic peak ice load values. The algorithm is compared to simulation-based and full-scale observations. Analyzing peak ice load events is challenging as sea ice goes through a complex mixed-mode failure process during such events. The algorithm is an effective tool for this analysis, and it shows that distinguishing between the buckling and local crushing failure is virtually impossible if the only data available from a peak load event is the value of the peak ice load. The algorithm shows potential in improving estimates of maximum peak ice load values on offshore structures.

Residential demand response program: Predictive analytics, virtual storage model and its optimization

Abstract Demand response programs are becoming an integral part of the power system, helping create a closer alignment between the electrical service providers and customers. The research described in this paper uses the residential demand response (DR) program during a peak demand event to determine the demand reduction capacity as a virtual storage (VS). As in the marketing business, identifying target customers is vital in the DR program, thus making it more efficient and productive. Additionally, peak load events are very critical in the power system; therefore, it is essential to model an effective demand response program. This paper uses predictive analytics to estimate the level of residential participation in a DR program, and thus the load reduction capacity available, during peak load events. Also derives the mathematical modeling of the demand reduction capacity of a demand response program as a virtual storage system and optimizes it using genetic algorithm technique.

Testing for crowd out in social nudges: Evidence from a natural field experiment in the market for electricity

This study considers the response of household electricity consumption to social nudges during peak load events. Our investigation considers two social nudges. The first targets conservation during peak load events, while the second promotes aggregate conservation. Using data from a natural field experiment with 42,100 households, we find that both social nudges reduce peak load electricity consumption by 2 to 4% when implemented in isolation and by nearly 7% when implemented in combination. These findings suggest an important role for social nudges in the regulation of electricity markets and a limited role for crowd out effects.

Soft-sensing with qualitative trend analysis for wastewater treatment plant control

Ammonia control in municipal wastewater treatment plants typically requires maintenance-intensive instrumentation. A low maintenance alternative is sought for small- to medium-scale applications. To this end, a pH-based soft-sensor is proposed to detect ammonia peak load events. This soft-sensor is based on a newly developed technique for qualitative trend analysis and is combined with a rule-based controller. The use of qualitative trend analysis makes this soft-sensor tolerant towards sensor drifts and thereby reduces the maintenance effort. The method allows controlling any process in which relative changes in the measured output are informative about the system output.

Pressure distributions and force chains during simulated ice rubbling against sloped structures

Abstract Vertical pressure distributions on a wide sloping structure during simulated ice rubbling processes have been investigated. The simulations were done with a two-dimensional combined finite-discrete element method. The results indicated that pressures during peak load events were local and mainly located at the waterline, even when a loose rubble pile was present. The force from the pushing ice sheet was transmitted to the structure through a loose rubble pile with highly loaded ice blocks forming chain-like groups, referred as force chains. Major load drops on the structure were caused by the buckling of these force chains. To be able to predict the forces on a sloping structure with a loose rubble pile in front of it, these force chains and their buckling behavior should be understood.

2D numerical simulations of ice rubble formation process against an inclined structure

Abstract This paper examines ice sheet failure and rubble pile formation process against a wide inclined structure by simulating the process with a two dimensional combined finite–discrete element method. In particular, rubble pile formation and deformation, as well as extreme ice load events are addressed. In the method used, the level ice sheet and its fracture are modeled by using a finite element scheme, while the contact forces between the colliding ice blocks are calculated by using the discrete element method. A total of 28 peak load cases are analyzed in detail and the phenomena during these peak load events are described. Peak loads are noticed to occur in the cases of ice ride-up, formation of a sail in front or away from the structure, and loading through a rubble pile. The common phenomenon in these four peak load situations was the loading of the rubble pile in a manner that a part of the pile is pushed upwards.

Dynamics of ice forces on booms

This paper presents the results of measured ice forces on three booms along the St. Lawrence River downstream of Montreal. We analyse (i) structural rupture events of various members, (ii) 44 recorded peak load events at 10 sites and (iii) 22 time series at five sites occurring over a 6-year period. The three booms (totalling 5 km in length), consist primarily of 61-cm diameter cylindrical pontoons. Time series data show that, during the consolidation period as the ice grows in area, thickness and strength, the load on the booms rise to a peak. Event analyses show that peak loads during a mid-winter thaw or during spring break-up are usually less severe. Fourier analyses show that the flexibility of the ice boom structure filters out high frequency loads. Even though most annual peak loads correspond to the theoretical value of the boom's normal retention capacity (5 kN/m), they often correspond to theoretical peak values possible during non-stable boundary conditions (10 to 15 kN/m). Finally, we propose formulae to assess the annual risk of exceeding a load value as a function of boom length.