Electric Water Heater Modelling for Direct Load Control Demand Response

Home Energy Management System creates the scopes to small household electrical appliances users to participate in the demand response programs. Among several load controllable electrical household appliances water heater is more suitable. Integration of water heater is considered to manage the demand response events that can contribute to smart grid technology. This paper represents a thermodynamic load model for a water heater, which is considered as to be controlled through direct load control for demand response program. The daily electricity consumption and temperature profile of the heater is also considered, the direct load control method is activated to the heater as soon as the energy consumption reaches to 1 kW, with the effects the device is turned off for next one hour. In results, it gained a significant reduction in the electricity consumption for the users without making any discomfort as temperature does not reduce to disruption level. Real time electricity pricing is also compared which implied financial benefit to the consumers. The result exhibit that the method applied to this heater can contribute and participate in the demand response events.The present work was done and funded in the scope of the following projects: H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794); SIMOCE (ANI|P2020 17690); and UID/EEA/00760/2013 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Financial Benefit Analysis of an Electric Water Heater with Direct Load Control in Demand Response

The peak demand reduction during peak hour is a challenge to the retail energy providers. Demand response program plays a major role to fulfil this purpose. The small household appliances like electric water heater can participate in the demand response program by aggregating it in the smart building energy management system. This paper discusses demand response possibilities of a residential electric water heater, the overall consumption profile, temperature profile and the financial benefit in the consumer level. The direct load control demand response method in yearly timeframe is proposed and applied. Realtime electricity pricing with incentive-based demand response is considered and applied to the direct load control with financial benefit to the consumers. The study includes the difference between normal consumption and consumption after using DLC, normal temperature profile and temperature profiling after DLC. The results exhibit that there is significant energy consumption reduction in the consumer level without making any discomfort.The present work was done and funded in the scope of the following projects: H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794); SIMOCE (ANI|P2020 17690); and UID/EEA/00760/2013 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Specifications for modelling fuel cell and combustion-based residential cogeneration device within whole-building simulation programs

This document contains the specifications for a series of residential cogeneration device models developed within IEA/ECBCS Annex 42. The devices covered are: solid oxide and polymer exchange membrane fuel cells (SOFC and PEM), and internal combustion and Stirling engine units (ICE and SE). These models have been developed for use within whole-building simulation programs and one or more of the models described herein have been integrated into the following simulation packages: ESP-r, EnergyPlus, TRNSYS and IDA-ICE. The models have been designed to predict the energy performance of cogeneration devices when integrated into a residential building (dwelling). The models account for thermal performance (dynamic thermal performance in the case of the combustion engine models), electrochemical and combustion reactions where appropriate, along with electrical power output. All of the devices are modelled at levels of detail appropriate for whole-building simulation tools

Analysis of retrofit air source heat pump performance : results from detailed simulations and comparison to field trial data

In the UK, gas boilers are the predominant energy source for heating in housing, due primarily to the ready availability of natural gas. The take-up of heat pumps has lagged far behind Europe and North America. However, with the development of standards for low and zero-carbon housing, gas price rises and the depletion of the UK's natural gas reserves, interest in heat pump technology is growing. Heat pumps, particularly air source heat pumps (ASHP), have the potential to be a direct, low-carbon replacement for gas boiler systems in housing. In this paper, monitored data and simulations were used to assess the performance of ASHP when retro-fitted into a dwelling. This required the development and calibration of a model of an ASHP device and its integration into a whole-building, dynamic simulation environment. The predictions of the whole-building model were compared to field trial data, indicating that it provided a suitable test bed for energy performance assessment. Annual simulations indicated that the ASHP produced 12% less carbon that an equivalent condensing gas boiler system, but was around 10% more expensive to run. However, the proposed UK renewable heat incentive transforms this situation, with income from ASHP heat generation exceeding the fuel costs

Electric Water Heater Modeling, DR Approaches Analysis and Study of Consumer Comfort for Demand Response

With the smart energy management system household residential appliances is able to participate in the demand response events. To reduce peak load demand and complexities in the local infrastructure DR can play an important role now a days. This paper presents a study and analysis of several papers on residential EWH DR modeling and implementation. It shows an overview of analysis of the most used and recent DR models for EWH. It also shows the analysis of the used methods to model this and the used approach in several papers. Additionally, the discussed consumer comforts and obtainable benefits in several papers by participating in DR events is also shown here. The study and analysis in this paper will contribute to the future research and encourage the end users to participate in households DR events.The present work was done and funded in the scope of the following projects: H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794); SIMOCE (ANI|P2020 17690); and UID/EEA/00760/2019 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Aspects of autonomous demand response through frequency based control of domestic water heaters

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering in the School of Electrical and Information Engineering, July 2017This dissertation presents the design and testing of controllers intended to provide au- tonomous demand response, through the use of water heater loads and grid frequency measurements. The controllers use measured frequency as an indication of the strain on a utility grid, which allows demand side management to be isolated from any form of central control. Water heaters can operate as exible loads because their power consump- tion can be dispatched or deferred without directly impacting users. These properties make it possible to control individual water heaters based on the functioning of the grid, rather than end user input. The purpose of this research is to ultimately provide a low- cost alternative to a traditional Smart Grid, that will improve the resilience of a grid without negatively impacting users. The controllers presented here focus on ensuring that users receive hot water, while attempting to reduce any imbalance between power generated and power consumed on the grid. Simulations of these controllers in various situations highlight that while the controllers developed respond suitably to variations in the grid frequency and adequately ensure end users receive hot water, the practical bene t of the controllers depends largely on the intrinsic characteristics of the grid.CK201

Load Management in a Smart House

Since a couple years ago, studies have been done in order to minimize the energy consumption at home. With that in mind, algorithms were developed to predict the energy consumption at the house and study the behaviour of the loads with the goal of minimizing the energy costs. In this dissertation, the objective was to create a model for the space heating and water heating and study their behaviour and adjust their load model to reduce the energy consumption and energy bill, and find the best energy tariffs for each case.The models consider physical parameters of the house , so the model can be a better approximation from reality.However, the problem is not only, a Energy and bill reduction, but the algorithm has to focus on the comfort of the house habitants too.Since a couple years ago, studies have been done in order to minimize the energy consumption at home. With that in mind, algorithms were developed to predict the energy consumption at the house and study the behaviour of the loads with the goal of minimizing the energy costs. In this dissertation, the objective was to create a model for the space heating and water heating and study their behaviour and adjust their load model to reduce the energy consumption and energy bill, and find the best energy tariffs for each case.The models consider physical parameters of the house , so the model can be a better approximation from reality.However, the problem is not only, a Energy and bill reduction, but the algorithm has to focus on the comfort of the house habitants too

Agent-based control for decentralised demand side management in the smart grid

Central to the vision of the smart grid is the deployment of smart meters that will allow autonomous software agents, representing the consumers, to optimise their use of devices and heating in the smart home while interacting with the grid. However, without some form of coordination, the population of agents may end up with overly-homogeneous optimised consumption patterns that may generate significant peaks in demand in the grid. These peaks, in turn, reduce the efficiency of the overall system, increase carbon emissions, and may even, in the worst case, cause blackouts. Hence, in this paper, we introduce a novel model of a Decentralised Demand Side Management (DDSM) mechanism that allows agents, by adapting the deferment of their loads based on grid prices, to coordinate in a decentralised manner. Specifically, using average UK consumption profiles for 26M homes, we demonstrate that, through an emergent coordination of the agents, the peak demand of domestic consumers in the grid can be reduced by up to 17% and carbon emissions by up to 6%. We also show that our DDSM mechanism is robust to the increasing electrification of heating in UK homes (i.e. it exhibits a similar efficiency)

Comparative Study Between Direct Load Control and Fuzzy Logic Control Based Demand Response

Demand response (DR), as part of Demand side management (DSM), is a method that modifies consumer side energy consumption. By actively controlling the time associated with electricity consumption, both energy and economic efficiencies are increased. There is however, depending on the algorithm employed, potential for consumer comfort levels to be adversely affected. Generally direct load (Boolean logic) control is employed, which solely considers demand reduction and not customer comfort. In comparison, fuzzy logic based programs can consider non-deterministic inputs such as consumer comfort level with ease and simplicity. This paper considers the evolution of DR through a comparison of the classical (direct load method) and modern (fuzzy method) methods, with particular attention on the advantages provided by the latter. The impact on consumer comfort in fuzzy DR implementation is further explored through the effect of temperature deviation. In this regard, the consequences for fuzzy DR are considered in respect to three temperature profiles. Finally, temporal availability and the consequences for DR are considered in the context of a household