scholarly journals Which Strategy Saves the Most Energy for Stratified Water Heaters?

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4859
Author(s):  
Michael J. Ritchie ◽  
Jacobus A. A. Engelbrecht ◽  
M. J. (Thinus) Booysen
Keyword(s):  
Energy Supply ◽  
Energy Demand ◽  
Energy Savings ◽  
Electricity Consumption ◽  
Hot Water ◽  
Water Usage ◽  
Point Temperature ◽  
Water Heaters ◽  
Heating Schedule ◽  
Reducing Energy

The operation of water heating uses a substantial amount of energy and is responsible for 30% of a household’s overall electricity consumption. Determining methods of reducing energy demand is crucial for countries such as South Africa, where energy supply is almost exclusively electrical, 88% of it is generated by coal, and energy deficits cause frequent blackouts. Decreasing the energy consumption of tanked water heaters can be achieved by reducing the standing losses and thermal energy of the hot water used. In this paper, we evaluate various energy-saving strategies that have commonly been used and determine which strategy is best. These strategies include optimising the heating schedule, lowering the set-point temperature, reducing the volume of hot water used, and installing additional thermal insulation. The results show that the best strategy was providing optimal control of the heating element, and savings of 16.3% were achieved. This study also determined that the magnitude of energy savings is heavily dependent on a household’s water usage intensity and seasonality.

scholarly journals Practically-Achievable Energy Savings with the Optimal Control of Stratified Water Heaters with Predicted Usage

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1963
Author(s):  
Michael J. Ritchie ◽  
Jacobus A.A. Engelbrecht ◽  
Marthinus J. Booysen
Keyword(s):  
Optimal Control ◽  
Fossil Fuels ◽  
Energy Savings ◽  
Electrical Energy ◽  
Hot Water ◽  
Prediction Errors ◽  
Water Usage ◽  
Energy Usage ◽  
Water Heaters ◽  
The Ideal

Residential water heaters use a substantial amount of electrical energy and contribute to 25% of the energy usage in the residential sector. This raises concern for users in countries with flat rate electricity fees and where fossil fuels are used for electricity generation. Demand side management of tanked water heaters is well suited for energy-focused load reduction strategies. We propose a strategy for providing an electric water heater (EWH) with the optimal temperature planning to reduce the overall electrical energy usage while satisfying the comfort of the user. A probabilistic hot water usage model is used to predict the hot water usage behaviour for the A*-based optimisation algorithm, which accounts for water stratification in the tank. A temperature feedback controller with novel temperature and energy-correcting capabilities provides robustness to prediction errors. Three optimal control strategies are presented and compared to a baseline strategy with the thermostat always on: The first ensures temperature-matched water usages, the second ensures energy-matched water usages, and the third is a variation of the second that provides Legionella prevention. Results were obtained for 77 water heaters, each one simulated for four weeks. The median energy savings for predicted usage were 2.2% for the temperature-matched strategy, and 9.6% for both of the energy-matched strategies. We also compare the practical energy savings to the ideal scenario where the optimal scheduling has perfect foreknowledge of hot water usages, and the temperature and energy-matched strategies had a 4.1 and 11.0 percentage point decrease from the ideal energy savings.

scholarly journals Non-Invasive Estimation of Domestic Hot Water Usage with Temperature and Vibration Sensors

2019 ◽  
Author(s):  
MJ Booysen
Keyword(s):  
Water Flow ◽  
Flow Rate ◽  
Water Consumption ◽  
Flow Measurement ◽  
Hot Water ◽  
Water Usage ◽  
Flow Rates ◽  
Domestic Hot Water ◽  
Non Invasive ◽  
Water Heaters

Electric water heaters are responsible for a large portion of electricity consumption and water usage in the domestic sector. Smart water heaters alleviate the strain on the electricity supply grid and reduce water consumption through behavioural change, but the installation of in-line flow meters is inconvenient and expensive. A non-invasive water flow meter is proposed as an alternative. Non-invasive flow measurement is more common for high flow rates in the industrial sector than for domestic applications. Various non-invasive water measurement methods are investigated in the context of domestic hot water, and a combination of thermal- and vibration-sensing is proposed. The proposed solution uses inexpensive, easily installable, non-invasive sensors and a novel algorithm to provide the same flow measurement accuracy as existing in-line meters. The algorithm detects the beginning and end of water consumption events with an accuracy of 95.6%. Quantitative flow rate estimation was possible for flow rates greater than 5 L min⁻¹ with an accuracy of 89%, while volumetric usage estimation had an accuracy of more than 93%. The algorithm limitations were applied to field data, revealing that water consumption could be detected with an error of less than 12% within the limitations of the proposed algorithm. The paper presents a successful proof of concept for a non-invasive alternative to domestic hot water flow rate measurement.

Wind energy and the historic environment: A business-driven symbiosis approach

2021 ◽  
pp. 0958305X2110148
Author(s):  
George A Xydis ◽  
Katerina Kremastioti ◽  
Maria Panagiotidou
Keyword(s):  
Energy Efficiency ◽  
Wind Energy ◽  
Heat Pump ◽  
Energy Demand ◽  
Energy Savings ◽  
Model Building ◽  
Electricity Consumption ◽  
Historic Buildings ◽  
Building Stock ◽  
Optimum Energy

The present study discusses alternative ways of achieving optimum energy efficiency for historic buildings in areas where sustainable energy projects are planned. About 25% of Europe’s building stock was constructed before the mid-20th century and despite EU’s strenuous efforts for the protection and conservation of historic buildings and complexes, achieving energy efficiency with the minimum or preferably no intervention remains as a requirement. The settlement of Monemvasia, has been selected as our case study. A model building was chosen, its special characteristics are presented, and four solutions to the energy efficiency upgrade of the building were tested: (a) the application of internal insulation, (b) a heat pump installation, (c) the application of roof insulation, and (d) the replacement of the internal doorframes. The four scenarios were simulated via the TEE-KENAK software and the percentage of the annual energy saved through the application of each one of the mentioned measures was estimated. The results proved that installing a heat pump and internal insulation would maximise energy savings. Coupling the energy demand of the settlement in correlation with a wind energy project in the wider area, and the available curtailment was explored. The results showed that if 300 houses decide on acquiring their electricity consumption from the local wind independent power producer, at a price of EUR 35/MWh, the possible profit from the market could reach EUR100,000 per year. Such a business-driven concept could be extrapolated and evolve into a holistic wind energy and historic environment symbiosis setting.

scholarly journals Deep Reinforcement Learning for Autonomous Water Heater Control

Buildings ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 548
Author(s):  
Kadir Amasyali ◽  
Jeffrey Munk ◽  
Kuldeep Kurte ◽  
Teja Kuruganti ◽  
Helia Zandi
Keyword(s):  
Reinforcement Learning ◽  
Residential Buildings ◽  
Electricity Consumption ◽  
The United States ◽  
Hot Water ◽  
Water Heater ◽  
Pricing Policy ◽  
Electricity Cost ◽  
Water Heaters ◽  
Model Free

Electric water heaters represent 14% of the electricity consumption in residential buildings. An average household in the United States (U.S.) spends about USD 400–600 (0.45 ¢/L–0.68 ¢/L) on water heating every year. In this context, water heaters are often considered as a valuable asset for Demand Response (DR) and building energy management system (BEMS) applications. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity cost of a water heater under a time-of-use (TOU) electricity pricing policy by only using standard DR commands. In this approach, a set of RL agents, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on an unseen pair of price and hot water usage profiles. The testing results showed that the RL agents can help save electricity cost in the range of 19% to 35% compared to the baseline operation without causing any discomfort to end users. Additionally, the RL agents outperformed rule-based and model predictive control (MPC)-based controllers and achieved comparable performance to optimization-based control.

scholarly journals Penghematan Listrik Rumah Tangga dalam Menunjang Kestabilan Energi Nasional dan Kelestarian Lingkungan

2019 ◽  
Vol 20 (2) ◽  
pp. 263
Author(s):  
Arif Dwi Santoso ◽  
Muhammad Agus Salim
Keyword(s):  
Energy Saving ◽  
Energy Supply ◽  
Energy Savings ◽  
Electricity Consumption ◽  
Electrical Energy ◽  
Research Data ◽  
Electricity Supply ◽  
Air Conditioners ◽  
Great Saving ◽  
Electrical Devices

ABSTRACTThe government efforts to maintain national energy stability program through the increase energy supply and saving must be supported by all levels of society. Several energy observers and experts stated that the contribution of the domestic or household sector in the activities of energy saving program is quite significant because the percentage of household customers are relatively high. This paper analyzes the potential of providing research data on the percentage of electricity savings in the domestic or household sectors towards saving electricity nationally. The results of the study show that electrical devices commonly used in households still have the potential to be saved. Electrical devices that are often used at households and have great saving potentials are air conditioners and refrigerators. If each household customer saves 30% of electricity consumption, then the national electricity supply that can be saved will be around 5,679 GW, equivalent to 83.3 trillion rupiah. The saving program resulted in savings of electricity consumption of around 6% of all household consumers or around 2.9% of total national electricity consumption.Keywords: electrical energy, savings, households ABSTRAKUpaya pemerintah dalam menjaga kestabilan energi nasional melalui program peningkatan pasokan dan penghematan energi harus didukung oleh seluruh lapisan masyarakat. Para pengamat dan pakar energi menyatakan bahwa kontribusi sektor domestik atau rumah tangga dalam program penghematan konsumsi energi listrik cukup signifikan karena persentase jumlah pelanggan rumah tangga yang relatif tinggi. Penelitian ini menganalisis tentang potensi persentase penghematan energi listrik sektor domestik atau rumah tangga terhadap  penghematan listrik secara nasional. Hasil penelitian menunjukkan bahwa piranti listrik yang biasa digunakan pada rumah tangga masih memiliki potensi untuk dilakukan penghematan. Piranti listrik yang sering digunakan pada rumah tangga dan memiliki potensi penghematan yang besar adalah alat pendingin ruangan (AC) dan kulkas. Bila setiap pelanggan rumah tangga melakukan penghematan konsumsi energi listriknya sebesar 30%, maka pasokan listrik nasional yang dapat dihemat adalah sekitar 5.679 GW atau setara dengan 83,3 Trilyun rupiah. Upaya ini menghasilkan penghematan konsumsi listrik sekitar 6% dari seluruh konsumen rumah tangga atau sekitar 2,9 % dari total konsumsi energi listrik nasional.Kata kunci: energi listrik, penghematan, rumah tangga

scholarly journals Feasibility of Grey Water Heat Recovery in Indoor Swimming Pools

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4221
Author(s):  
Joanna Liebersbach ◽  
Alina Żabnieńska-Góra ◽  
Iwona Polarczyk ◽  
Marderos Ara Sayegh
Keyword(s):  
Energy Demand ◽  
Heat Recovery ◽  
Energy Savings ◽  
Water Flow Rate ◽  
Hot Water ◽  
Swimming Pool ◽  
Swimming Pools ◽  
Grey Water ◽  
Indoor Swimming Pool ◽  
Reduction Of Co2

Swimming pools are used around the world for recreational, rehabilitation and physical activity. From an energy and environmental standpoint, grey water as a waste thermal potential of swimming pools is a valuable heat source produced continuously in extensive, measurable and large quantities. The main objective of this article is to analyse the feasibility of proposed grey water heat recovery (GWHR) system from the showers and backwater from swimming pool filters for an indoor pool located in recreation centre in Poland. Analysis, calculations and results were obtained and discussions of water and energy consumption were carried out for the mentioned indoor swimming pool on the basis of real measurements case study for water flow rate, water temperature in swimming pools and showers. The results ensure a significant potential of energy savings by using the proposed GWHR system, which allows to reduce the energy demand by 34% up to 67% for pool water preheating and domestic hot water (DHW). The environmental impact of proposed GWHR system was analysed and calculated by using Common Air Quality Index. Environmental results are illustrated and discussed specially for the reduction of CO2, NOX, SOX emissions and dust and ensure a significant reduction of these pollutants in range of 34% to 48%.

scholarly journals Energy Efficiency for Social Buildings in Morocco, Comparative (2E) Study: Active VS. Passive Solutions Via TRNsys

Inventions ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 4
Author(s):  
Fatima Zohra Gargab ◽  
Amine Allouhi ◽  
Tarik Kousksou ◽  
Haytham El-Houari ◽  
Abdelmajid Jamil ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Savings ◽  
Building Envelope ◽  
Hot Water ◽  
Solar Water Heater ◽  
Water Heater ◽  
Climatic Zones ◽  
Solar Water ◽  
Water Heaters ◽  
Solar Water Heaters

This paper aims to highlight the potential of solar water heater installations in Morocco. The project involves the comparison of active and passive solutions for energy efficiency in buildings. To this end, a numerical simulation model of solar water heater installations is created under TRNsys. Three hot water demand scenarios (Low, Standard, and High) were taken into account for the six climatic zones defined in the Moroccan thermal regulation of constructions. The same software (TRNsys) is used to model a pilot building consisting of 16 flats. Energy efficiency actions have been applied to the building envelope (insulation and glazing) and simulations are made for the six areas. The simulation results comparing energy and financial savings show the influence of subsidized gas prices on solar water heaters’ relevance despite significant energy savings. This work proves that solar water heaters will be a primary obligation for Morocco, taking into account changes in butane gas prices.

scholarly journals How much energy can optimal control of domestic water heating save?

2019 ◽  
Author(s):  
MJ Booysen ◽  
J.A.A. Engelbrecht ◽  
Michael Ritchie ◽  
Mark Apperley ◽  
Andrew Cloete
Keyword(s):  
Optimal Control ◽  
Fossil Fuels ◽  
Energy Use ◽  
Hot Water ◽  
Water Usage ◽  
Water Heating ◽  
Domestic Water ◽  
Water Heaters ◽  
Point Of Use ◽  
The Impact

Scheduled control of domestic electric water heaters, designed to cut energy use while minimising the impact on users' comfort and convenience, has been fairly common for some time in a number of countries. The aim is usually load-shifting (by heating water at off-peak times) and/or maximising time-of-use pricing benefits for users. The scheduling tends not to be linked to actual hot water usage and depends largely on stored thermal energy. Heat losses therefore tend to be greater than if the heater ran without a break. The effect of such a control strategy is thus to worsen the energy loss and in most cases increase greenhouse gas emissions. Many developing countries have flat-pricing (no time-of-use incentives) and rely heavily on energy from fossil fuels, making these considerations even more pressing. We explore three strategies for optimal control of domestic water heating that do not use thermostat control: matching the delivery temperature in the hot water, matching the energy delivered in the hot water, and a variation of the second strategy which provides for Legionella sterilisation. For each of these strategies we examine the energy used in heating, the energy delivered at the tank outlet, and issues of convenience to the user. The study differs from most previous work in that it uses real daily hot-water usage profiles, ensures like-for-like comparison in delivered energy at the point of use, and includes a daily Legionella avoidance strategy. We tackled this as an optimal control problem using dynamic programming. Our results demonstrate a median energy saving of between 8\ and 18% for the three strategies. Even more savings would be realised if intended and unintended usage events are correctly classified, and the optimal control only plans for intended usage events.

scholarly journals Impact of node count on energy-optimal control of stratified vertical water heaters in smart grid applications

2021 ◽  
Author(s):  
MJ Ritchie ◽  
J.A.A. Engelbrecht ◽  
MJ Booysen
Keyword(s):  
Optimal Control ◽  
Energy Savings ◽  
Variable Number ◽  
Hot Water ◽  
Water Heater ◽  
Total Energy Consumption ◽  
Water Heaters ◽  
Greenhouse Gases Emissions ◽  
Four Seasons ◽  
Grid Applications

The energy requirements for an Electric Water Heater (EWH) accounts for 40% of a household's total energy consumption and 30% of greenhouse gases emissions. The flexibility of the device to store thermal energy for long periods highlights how the intensity of the grid demand can be alleviated by implementing demand-side management (DSM) strategies. In this paper, we evaluate energy savings that can be achieved by modelling the EWH as a variable number of multiple nodes and providing it with optimal control with perfect foreknowledge of the hot water usage profile. We simulated 77 household's for all four seasons and determined that an average daily energy saving of 6.2% for temperature-matching and 16.3% for energy-matching can be achieved for a 20-node EWH. We also evaluated how increasing the number of nodes of the EWH when determining the optimal planning affects energy savings. It was concluded that using more than four nodes produced diminishing returns.

scholarly journals A probabilistic hot water usage model and simulator for use in residential energy management

2020 ◽  
Author(s):  
MJ Ritchie ◽  
J.A.A. Engelbrecht ◽  
MJ Booysen
Keyword(s):  
Energy Management ◽  
Temporal Variations ◽  
Measured Data ◽  
Hot Water ◽  
Inlet Temperature ◽  
Water Usage ◽  
Electricity Grid ◽  
Water Heaters ◽  
Main Determinants ◽  
The Individual

Water heating contributes up to 40% of a household's total electricity usage and places a substantial burden on the electricity grid due to high power ratings and users' largely simultaneous hot water usage. The main determinants of its electricity draw are physical properties such as set temperature, insulation, and plumbing configuration; environmental conditions such as ambient temperature and inlet temperature; and the hot water usage profiles. These profiles include the usage volumes, the times of usage and the outlet temperatures. The efficacy of energy management techniques that model water heaters and the accuracy of their simulation results therefore rely on representative hot water usage profiles. Existing models for household hot water usage neglect differences between users, and temporal variations such as the season and the day of the week, and are not fully autonomous. We propose a probabilistic data-driven model for modelling individualised hot water profiles and an accompanying hot water usage simulator that includes all these factors. We gathered data from 77 residential households over a period of one year to train and evaluate the model for all four seasons. The results show that the simulated hot water usage profiles match the statistical properties of the measured data. Moreover, the individual hot water usage modelling and the resulting aggregated energy load on the grid closely match the measured data, improving on the existing hot water usage by halving the modelling error.

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