Demand side management—A simulation of household behavior under variable prices

Within the next years, consumer households will be increasingly equipped with smart metering and intelligent appliances. These technologies are the basis for households to better monitor electricity consumption and to actively control loads in private homes. Demand side management (DSM) can be adopted to private households. We present a simulation model that generates household load profiles under flat tariffs and simulates changes in these profiles when households are equipped with smart appliances and face time-based electricity prices.     

Internet of things and cloud computing‐based energy management system for demand side management in smart grid

A smart grid is an electricity network, which deals with electronic power conditioning and control of production, transmission, and distribution of electrical power by employing digital communication technologies to monitor and manage local changes in electricity usage. In the traditional power grid, energy consumers remain oblivious to their power consumption patterns, resulting in wasted energy as well as money. This issue is severely pronounced in the developing countries where there is a huge gap between demand and supply, resulting in frequent power outages and load‐shedding. For electrical energy savings, the smart grid employs demand side management (DSM), which refers to adaptation in consumer's demand for energy through various approaches such as financial incentives and awareness. The DSM in future smart grid must exploit automated energy management systems (EMS) built upon the state‐of‐the‐art technologies such as the internet of things (IoT) and cloud and/or fog computing. In this paper, we present the architecture framework, design, and implementation of an IoT and cloud computing‐based EMS, which generates load profile of consumer to be accessed remotely by utility company or by the consumer. The consumers' load profiles enable utility companies to regulate and disseminate their incentives and incite the consumers to adapt their energy consumption. Our designed EMS is implemented on a Project Circuit Board (PCB) to be easily installed at the consumer premises where it performs the following tasks: (a) monitors energy consumption of electrical appliances by means of our designed current and voltage sensors, (b) uploads sensed data to Google Firebase cloud over many‐to‐many IoT communication protocol Message Queuing Telemetry Transport (MQTT) where consumer's load profile is generated, which can be accessed via a web portal. These load profiles serve as input for implementing the various DSM approaches. Our results demonstrate generated load profiles of consumer load in terms of current, voltage, energy, and power accessible via a web portal.     

Blade load mitigation control design for a wind turbine operating in the path of vortices

As wind turbine rotor size continues to increase, load mitigation becomes an important control objective. Turbines with hub heights of nearly 100m operate in the stable, nocturnal boundary layer where coherent turbulence can be generated by atmospheric phenomena outside the surface layer. These coherent turbulent structures may contribute to blade fatigue loads that can be mitigated with advanced control algorithms. Disturbance accommodating control (DAC) methods were implemented in a wind turbine structural dynamics simulation code to mitigate transient blade load response induced by a simple, Rankine vortex in the inflow. As a best‐case scenario, a full‐state feedback controller (which included a very detailed disturbance model) showed that blade flap damage equivalent load caused by the vortex passing through the rotor could be reduced by 30% compared to one that resulted from simulation of a typical proportional‐integral (PI) controller. A realizable DAC controller that incorporates only the vertical shear component of the vortex reduced loads by 9% compared to that resulting from simulation of a PI controller. The load reduction was even greater when the vortex was superimposed over full‐field, homogeneous turbulence. DAC methods have the flexibility to incorporate properties of coherent turbulent inflow structures in the controller design to mitigate blade fatigue loads. Further work must be done to develop disturbance models as more details about the turbulent structures are identified. Copyright © 2007 John Wiley & Sons, Ltd.     

Design clustering of offshore wind turbines using probabilistic fatigue load estimation

In large offshore wind farms fatigue loads on support structures can vary significantly due to differences and uncertainties in site conditions, making it necessary to optimize design clustering. An efficient probabilistic fatigue load estimation method for monopile foundations was implemented using Monte-Carlo simulations. Verification of frequency domain analysis for wave loads and scaling approaches for wind loads with time domain aero-elastic simulations lead to 95% accuracy on equivalent bending moments at mudline and tower bottom. The computational speed is in the order of 100 times faster than typical time domain tools. The model is applied to calculate location specific fatigue loads that can be used in deterministic and probabilistic design clustering. Results for an example wind farm with 150 turbines in 30–40 m water depth show a maximum load difference of 25%. Smart clustering using discrete optimization algorithms leads to a design load reduction of up to 13% compared to designs based on only the highest loaded turbine position. The proposed tool improves industry-standard clustering and provides a basis for design optimization and uncertainty analysis in large wind farms.     

A comparison of four methods to evaluate the effect of a utility residential air-conditioner load control program on peak electricity use

We analyzed the peak load reductions due to a residential direct load control program for air-conditioners in southern Ontario in 2008. In this program, participant thermostats were increased by 2 °C for four hours on five event days. We used hourly, whole-house data for 195 participant households and 268 non-participant households, and four different methods of analysis ranging from simple spreadsheet-based comparisons of average loads on event days, to complex time-series regression. Average peak load reductions were 0.2–0.9 kWh/h per household, or 10–35%. However, there were large differences between event days and across event hours, and in results for the same event day/hour, with different analysis methods. There was also a wide range of load reductions between individual households, and only a minority of households contributed to any given event. Policy makers should be aware of how the choice of an analysis method may affect decisions regarding which demand-side management programs to support, and how they might be incentivized. We recommend greater use of time-series methods, although it might take time to become comfortable with their complexity. Further investigation of what type of households contribute most to aggregate load reductions would also help policy makers better target programs.     

Planetary gear load sharing of wind turbine drivetrains subjected to non‐torque loads

An analytical formulation was developed to estimate the load‐sharing and planetary loads of a three‐point suspension wind turbine drivetrain considering the effects of non‐torque loads, gravity and bearing clearance. A three‐dimensional dynamic drivetrain model that includes mesh stiffness variation, tooth modifications and gearbox housing flexibility was also established to investigate gear tooth load distribution and non‐linear tooth and bearing contact of the planetary gears. These models were validated with experimental data from the National Renewable Energy Laboratory's Gearbox Reliability Collaborative. Non‐torque loads and gravity induce fundamental excitations in the rotating carrier frame, which can increase gearbox loads and disturb load sharing. Clearance in the carrier bearings reduces the bearing stiffness significantly. This increases the amount of pitching moment transmitted from the rotor to the gear meshes and disturbs the planetary load share, thereby resulting in edge loading. Edge loading increases the likelihood of tooth pitting and planet‐bearing fatigue, leading to reduced gearbox life. Additionally, at low‐input torque, the planet‐bearing loads are often less than the minimum recommended load and thus susceptible to skidding. Copyright © 2014 John Wiley & Sons, Ltd.     

如何应对当前我国电力供应不足的问题

2003年我国经济增长速度将7.8～8.3%,全社会用电量需求增长也将达11～13%。本文分析了当前我国电力供需紧张的主要原因,电网负荷率降低使得可发电量有余、可供电力不足。为了解决当前电力供应不足的问题,本文提出采用需求侧管理的办法,通过拉大峰谷电价,推出尖峰电价及可中断负荷等措施,降低1000万kW的高峰负荷,缓解电力供应紧张的局面。     

Platform stabilization and load reduction of floating offshore wind turbines with tension‐leg platform using dynamic vibration absorbers

Floating offshore wind turbines (FOWT) are subject to significant increases in structural loads due to the platform motion under turbulent wind and wave. The under‐actuation challenge in FOWT control demands for development of extra actuators for platform stabilization. For FOWT with tension‐leg platform (TLP), this paper presents a comprehensive study on design and control simulation for realizing active mooring line control via the deployment of vertically operated dynamic vibration absorbers (DVAs) at the spokes of TLP structure. The DVA is designed based on the suppression of the primary modes of platform pitch and roll motion. In addition to the enhancement of FAST‐based simulation module, an 11 degrees‐of‐freedom (DOFs) control‐oriented model is derived for the TLP‐FOWT‐DVA system. Based on the control‐oriented model, a linear quadratic regulator (LQR) controller is designed. Simulations are performed for 9 m/s and 18 m/s turbulent winds with different wind and wave directions. The wind turbine performance, platform motions, and structural fatigue loads are evaluated. The results show that the platform motion and tower loads in the lateral direction are significantly reduced, while the tower load in the fore‐aft direction can be moderately reduced. Also, significant reduction in the mooring line tension loads is observed. For achieving the performance in platform motion stabilization and load reduction, the average power consumption of the DVA actuators is less than 0.27% of the wind turbine power generated during the simulated periods. The figures of merits promise significant potential for the feasibility of DVA based control for TLP‐FOWT.     

Smart metering for residential energy efficiency: The use of community based social marketing for behavioural change and smart grid introduction

Community-based social marketing (CBSM) has shown to be very effective at inducing behavioural change due to its pragmatic approach. It has been found that nonintegrated intensive approaches towards changing individual's behaviour, such as education and economic self-interest are not successful.This paper will explain how a large urban electricity meter replacement program can achieve a reduction in peak demand and overall energy consumption through the use of advanced metering infrastructure (AMI or ‘smart meters’) coupled with CBSM, which in turn enables the progression towards a ‘smart grid’. In order to measure success the following targets were set:

• •Peak demand reduction (peak lopping) of 20% from the households participating in the Behaviour Change Programs (BCPs).
• •Peak demand shifting (load shifting) to reduce energy consumption during ‘super peak’ by 10% in BCP participating households.
• •Average total energy use reduction of 10% in BCP participating households.

The energy efficiency actions discussed with householders during eco-coaching, and other feedback communications, are identified by utilising the information regarding barriers and benefits generated from the research phase prior to coaching. These actions can include referral to other initiatives such as the provision of reduced cost solar PV power systems, direct load control devices for domestic air-conditioners, the time-of-use pricing product, the provision of in-home-displays (IHD) and other devices necessary for development of a ‘smart grid’.     

年最大负荷的包络灰预测模型研究

根据北京地区年最大负荷发生的特点，以1997～2002年年最大负荷数据为基础，采用包络灰预测的方法，建立了北京市年最大负荷的包络灰预测模型。通过与其他预测模型的比较，发现所建包络灰预测模型更具合理性和可行性，可以满足现场的实际需要。     

基于分区建模的大空间分层空调负荷随分层高度变化的研究

以某坡屋顶大空间建筑为研究对象,利用eQUEST软件,提出了空调区和非空调区分区的建模方法,依据所建模型分析全室空调和不同分层高度时夏季分层空调峰值冷负荷特性.模拟结果表明,分层空调形式的负荷比全室空调的减少30%以上,夏季空调峰值负荷随分层高度增加近似线性增加.比较模拟负荷与常规分层空调负荷计算结果发现,两者相对误差小于3%,说明基于动态能耗模拟软件分区模拟大空间分层空调负荷的方法合理.     

Direct load control of residential water heaters

In Norway there is a growing concern that electricity production and transmission may not meet the demand in peak-load situations. It is therefore important to evaluate the potential of different demand-side measures that may contribute to reduce peak load. This paper analyses data from an experiment where residential water heaters were automatically disconnected during peak periods of the day. A model of hourly electricity consumption is used to evaluate the effects on the load of the disconnections. The results indicate an average consumption reduction per household of approximately 0.5 kWh/h during disconnection, and an additional average increase in consumption the following hour, due to the payback effect, that may reach up to 0.28 kWh/h per household.     

Further load reductions with individual pitch control

Previous work has demonstrated that significant reductions in fatigue loading on a wind turbine can be achieved by using individual pitch control, in which the pitch of each blade is adjusted individually, in response to measured loads. The asymmetrical out‐of‐plane rotor load is measured and an additional pitch action (dominated by the rotational frequency of the rotor) is calculated for each blade in order to minimize this load. This results in the near‐elimination of the dominant once‐per‐revolution (‘1P’) peak in the out‐of‐plane load spectrum seen by the rotating components, and fatigue loads can be reduced by 20%–40%. The load reduction is also transferred to the nacelle and tower, but here it is the low‐frequency loads which are removed, resulting in a load reduction of a few per cent at best, since the fatigue on the fixed components is dominated by the peak at the blade passing frequency (‘3P’ for a three‐bladed turbine), which is largely unaffected by the individual pitch control action. This article demonstrates a relatively straightforward addition to the individual pitch control algorithm which is capable of reducing the dominant load peak on the fixed components, resulting in significant fatigue load reductions on the whole structure. Copyright © 2005 John Wiley & Sons, Ltd.     

The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review

Peak demand for electricity in North America is expected to grow, challenging electrical utilities to supply this demand in a cost-effective, reliable manner. Therefore, there is growing interest in strategies to reduce peak demand by eliminating electricity use, or shifting it to non-peak times. This strategy is commonly called “demand response”. In households, common strategies are time-varying pricing, which charge more for energy use on peak, or direct load control, which allows utilities to curtail certain loads during high demand periods. We reviewed recent North American studies of these strategies. The data suggest that the most effective strategy is a critical peak price (CPP) program with enabling technology to automatically curtail loads on event days. There is little evidence that this causes substantial hardship for occupants, particularly if they have input into which loads are controlled and how, and have an override option. In such cases, a peak load reduction of at least 30% is a reasonable expectation. It might be possible to attain such load reductions without enabling technology by focusing on household types more likely to respond, and providing them with excellent support. A simple time-of-use (TOU) program can only expect to realise on-peak reductions of 5%.     

A generic demand‐side management model for smart grid

The demand‐side management (DSM) is one of the most important aspects in future smart grids: towards electricity generation cost by minimizing the expensive thermal peak power plants. The DSM greatly affects the individual users' cost and per unit cost. The main objective of this research article is to develop a generic demand‐side management (G‐DSM) model for residential users to reduce peak‐to‐average ratio (PAR), total energy cost, and waiting time of appliances (WTA) along with fast execution of the proposed algorithm. We propose a system architecture and mathematical formulation for total energy cost minimization, PAR reduction, and WTA. The G‐DSM model is based on genetic algorithm (GA) for appliances scheduling and considers 20 users having a combination of appliances with different operational characteristics. Simulation results show the effectiveness of G‐DSM model for both single and multiple user scenarios. Copyright © 2015 John Wiley & Sons, Ltd.     

Application of simulated lidar scanning patterns to constrained Gaussian turbulence fields for load validation

We demonstrate a method for incorporating wind velocity measurements from multiple‐point scanning lidars into three‐dimensional wind turbulence time series serving as input to wind turbine load simulations. Simulated lidar scanning patterns are implemented by imposing constraints on randomly generated Gaussian turbulence fields in compliance with the Mann model for neutral stability. The expected efficiency of various scanning patterns is estimated by means of the explained variance associated with the constrained field. A numerical study is made using the hawc2 aeroelastic software, whereby the constrained turbulence wind time series serves as input to load simulations on a 10 MW wind turbine model using scanning patterns simulating different lidar technologies—pulsed lidar with one or multiple beams—and continuous‐wave lidars scanning in three different revolving patterns. Based on the results of this study, we assess the influence of the proposed method on the statistical uncertainty in wind turbine extreme and fatigue loads. The main conclusion is that introducing lidar measurements as turbulence constraints in load simulations may bring significant reduction in load and energy production uncertainty, not accounting for any additional uncertainty from real measurements. The constrained turbulence method is most efficient for prediction of energy production and loads governed by the turbulence intensity and the thrust force, while for other load components such as tower base side‐to‐side moment, the achieved reduction in uncertainty is minimal. Copyright © 2016 John Wiley & Sons, Ltd.     

Peak loads and network investments in sustainable energy transitions

Current energy distribution networks are often not equipped for facilitating expected sustainable transitions. Major concerns for future electricity networks are the possibility of peak load increases and the expected growth of decentralized energy generation. In this article, we focus on peak load increases; the effects of possible future developments on peak loads are studied, together with the consequences for the network. The city of Eindhoven (the Netherlands) is used as reference city, for which a scenario is developed in which the assumed future developments adversely influence the maximum peak loads on the network. In this scenario, the total electricity peak load in Eindhoven is expected to increase from 198 MVA in 2009 to 591–633 MVA in 2040. The necessary investments for facilitating the expected increased peak loads are estimated at 305–375 million Euros. Based upon these projections, it is advocated that – contrary to current Dutch policy – choices regarding sustainable transitions should be made from the viewpoint of integral energy systems, evaluating economic implications of changes to generation, grid development, and consumption. Recently applied and finished policies on energy demand reduction showed to be effective; however, additional and connecting policies on energy generation and distribution should be considered on short term.     

A transient ventilation demand model for air-conditioned offices

Ventilation to supply fresh air in an air-conditioned office consumes a considerable portion of energy in an air-conditioning system and affects the indoor-air quality (IAQ). The ventilation demand is primarily related to the occupant load. In this study, the ventilation demands due to occupant load variations were examined against certain IAQ objectives using the mass balance of carbon dioxide (CO₂) volume fractions in an air-conditioned office. In particular, this study proposed a transient ventilation demand model for occupant load, with the parameters determined from a year-round occupant load survey in Hong Kong. This model was applied to evaluate the performance of energy saving in different operating schedules of ventilation systems for typical office buildings in Hong Kong. The results showed that the energy consumption of a ventilation system would be correlated with the transient occupant load and its variations in the air-conditioned office. The ventilation system, with schedules taking account of the transient occupant loads, would offer a reduction in energy consumption up to 19% as compared with an operating schedule that assumed a steady occupant-load in the office during working hours. In both cases, the same IAQ objective was achieved.     

An analysis of a demand charge electricity grid tariff in the residential sector

This paper analyzes the demand response from residential electricity consumers to a demand charge grid tariff. The tariff charges the maximum hourly peak consumption in each of the winter months Dec, Jan, and Feb, thus giving incentives to reduce peak consumption. We use hourly electricity consumption data from 443 households, as well as data on their grid and power prices, the local temperature, wind speed, and hours of daylight. The panel data set is analyzed with a fixed effects regression model. The estimates indicate average demand reductions up to 0.37 kWh/h per household in response to the tariff. This is on average a 5% reduction, with a maximum reduction of 12% in hour 8 in Dec. The consumers did not receive any information on their continuous consumption or any reminders when the tariff was in effect. It is likely that the consumption reductions would have been even higher with more information to the consumers.     

A novel peak load shaving algorithm via real‐time battery scheduling for residential distributed energy storage systems

As population grows and energy consumption increases, generation, transmission, and energy distribution costs also increase. Sudden and unpredicted demand increase at peak periods might lead to failure and even damage the power grid. This is a challenge for stability and reliability of the grid. Peak load shaving is considered as an effective approach while transition from peak load periods. In this paper, peak load shaving is modeled mathematically through storing energy on demand side and solved using optimization method. Using the results obtained from solving the optimization problem, a simple effective algorithm is proposed for peak load shaving via real‐time scheduling of distributed battery storage systems without complicated calculations. All characteristics required for systemic design of peak load shaving for residential, commercial, and industrial loads are presented. This method can be used in the presence of photovoltaic arrays or other renewable or nonrenewable distributed energy resources simultaneously, and it can be adapted to different conditions and demands. Here, real measured data of a residential state, an office building with photovoltaics, a hotel, and a small office are used for simulation, and GAMS is used for analysis.