Electricity Bill Savings Research Articles

Electricity Bill Savings from Reduced Household Energy Consumption in Apartment Complexes

Apartments account for 64.6% of all housing units in the Republic of Korea, and most of them receive electricity under a contract, which includes a progressive rate plan. Recently, due to the electrification of energy used in homes and the growing adoption of electric vehicles, electricity consumption in apartment complexes has been gradually increasing. Given the characteristics of the progressive rate system, an increase in electricity usage results in a significant higher rise in electricity bills. Thus, an effective alternative is required to reduce electricity bills for each household. In this paper, the savings in electricity bills achieved by reducing household electricity usage are analyzed from both apartment complex and individual household perspectives, using metering data from 13,332 households. When households are sorted by the amount of savings in descending order, the resulting values are found to follow a negative exponential curve. This indicates that the benefits from reducing electricity usage in households with higher saving are significantly larger compared to other ones. We analyzed bill savings when electricity usage reductions were selectively applied to the top 10%, 20%, and 30% of households with the largest savings. From the results, it is found that the largest savings in electricity bills for households are achieved when usage reductions are applied to the top 10% of households. It is expected that this amount of savings would encourage these households to reduce their electricity consumption. Additionally, it is found that the savings for apartment complexes and the total savings for selected households are not the same, resulting in changes in the bills for households that do not reduce their usage. From the results, it was observed that when the usage reduction of selected households is small or the proportion of households reducing usage is low, the common area charges for non-reducing households tend to increase, leading to higher electricity bills. On the contrary, when the usage reduction of selected households is large or the proportion of households reducing usage is high, the common area charges for non-reducing households tend to decrease, resulting in lower electricity bills.

Techno-economic impact of electricity price mechanism and demand response on residential rooftop photovoltaic integration

Rooftop distributed photovoltaics show great potential for deep decarbonisation in the residential sector. However, the intermittency and undispatchability of photovoltaic output are urgent problems in the large-scale deployment of rooftop distributed photovoltaics. This study develops a techno-economic evaluation framework for rooftop distributed photovoltaics by comprehensively considering and exploring the uncertain effects of electricity price mechanisms, battery energy storage, demand response for residential flexible loads, and residential electricity demand difference to increase self-consumption and the economic benefits of rooftop distributed photovoltaics. The results show that electricity price mechanisms are the main factors affecting the economic benefits of rooftop distributed photovoltaics, which are more economical under time-of-use prices than under flat prices. Installing battery energy storage and participating in demand response for residential flexible loads can significantly improve self-consumption and self-sufficiency rates, and bring more electricity bill savings and less feed-in revenue. Specifically, the relative economic benefits of installing battery energy storage and demand response were greater at lower feed-in tariffs. Moreover, the greater the ratio of annual residential electricity demand to photovoltaic power generation, the greater the self-consumption rate. Further, only when battery energy storage is installed, the smaller the ratio, the greater the self-sufficiency rate. Consequently, the energy sector can design more efficient time-of-use pricing mechanisms and adopt lower feed-in tariffs to encourage residential consumers to deploy both rooftop distributed photovoltaics and battery energy storage and to participate in demand response.

Evaluating the Technical, Economic, and Environmental Performance of Solar Water Heating System for Residential Applications–Comparison of Two Different Working Fluids (Water and Glycol)

The use of solar water heaters (SWH) in both residential and commercial facilities is one of the possible ways to reduce electricity bills and the release of greenhouse gases (GHG). This study assessed the technical, economic, and environmental performance of a SWH system at six different locations in China (i.e., Lhasa, Lauchang, Wuhan, Kashi, Yumen, and Harbin). A comparison between two different working fluids (i.e., water and glycol) were modeled in the System Advisor Model in all six cities. A sensitivity analysis was conducted on some key technical and economic parameters to assess the impact of such parameters on the performance of SWH systems in the country. According to the results, Lhasa recorded the highest capacity factor of 11% and 10.70% using water and glycol as the working fluid, respectively. Lhasa was identified as the best location among the studied locations due to its high solar irradiation. The optimization study indicates that the optimum azimuth for China is 190°. It was also found that a 25% reduction in the outlet set temperature of the water can reduce the capacity factor from 11% to about 9.2%. Using the SWH as simulated in this study can reduce carbon dioxide emissions from 1252.87–2014.85 kg per year to 138.20–330.23 kg per year; the extent of reduction depends on the location of the SWHS, and the solar energy available at the area. Net electricity bill savings of $156–296 could be obtained if SWH systems were installed and used at the studied locations.

Clean heating using mid–deep-groundwater heat pumps in Mei County, China

With the promotion of rural revitalization in China, mid-deep-groundwater heat pump systems have played a significant role in the efficient utilization of geothermal energy. Restricted by the pressure threshold of the old municipal heating network and the amount of construction investment, the advantages of geothermal energy are often greatly limited, and there is a lack of combined system development and analysis of actual engineering cases. In this study, we constructed and operated a mid–deep-groundwater heat pump system in Mei County. Based on an analysis of the geothermal resource endowment and building energy demand, a preliminary geophysical exploration was conducted to determine the drilling locations of heat source wells. Drilling was completed and tracer experiments were conducted to determine the connectivity between wells. The existing operation strategy of the new heat source and old pipe network geothermal energy heating system was analyzed by testing the operation during the heating season. The results indicate that the current operating scheme of the heat pump unit group presents a step distribution in terms of power consumption and heating capacity. Based on an optimized operation plan, electricity bill savings of at least 392000 RMB can be achieved per heating season.

Quantifying the benefits of PV module shading for building heat gain reduction: A machine learning approach

This study investigates the indirect benefit due to the shading effect from PV rooftop systems installed on building envelopes by proposing a new method based on a machine-learning algorithm. The study gathered a year of data from a 25 kWp PV rooftop system installed on a metal sheet roofing. It classifies the dataset into four categories based on solar irradiance and ambient temperature to represent Thailand's climate. There evaluated the RTTV and case study from implemented projects with metal sheet roofing in Thailand to estimate the potential electricity bill savings from the PV module shade effect. The results reveal an inverse relationship between the percentage of heat reduction and heat gain reduction, with the most significant reduction occurring under high solar irradiance and ambient temperature conditions. The shading effect caused by the PV modules provides an indirect benefit of approximately 38 kWh/kWp/year from electricity bill savings. In contrast, the PV system production yields around 1401 kWh/kWp/year based on radiation of about 1839 kWh/m2/year. The study estimates that energy-saving possibilities range from 0.038 to 0.052 kWh/m2/day, depending on the weather conditions, equivalent to an electricity saving of approximately 6.33 kWh/m2/year from air conditioner use.

Analysis of Residential Electricity Usage Characteristics and the Effects of Shifting Home Appliance Usage Time under a Time-of-Use Rate Plan

Carbon reduction programs are being introduced for carbon neutrality and energy transition to clean energy sources in various sectors, such as energy, buildings, transportation, and agriculture. In the residential electricity energy of the energy sector, the time-of-use (TOU) rate plan, which employs dynamic rates depending on energy usage times based on the advanced metering infrastructure (AMI), is being implemented for efficient electricity energy consumption. For broad expansion of the TOU rate plan, customers need information about its benefits, such as potential savings on electricity bills. In this paper, we first analyze the statistical characteristics of electricity energy usage using the metering data collected from 10 apartment complexes through AMI and develop a model to calculate the electricity bill savings. We next introduce examples of major home appliances, of which usage times can be shifted, and offer projected bill savings from the developed model. We analyze the examples from both the perspectives of households and apartment complexes. The information from this analysis is helpful in practically investigating customers’ willingness to shift the usage time for a successful implementation of the demand response program.

Impacts of COVID-19 on educational buildings energy consumption: case study of the university of Jordan

The global lockdowns adopted by many countries to combat the outbreak of the COVID-19 pandemic led to a significant transformation in the teaching methods adopted in higher education institutions toward dependence on online learning systems. Although this pandemic has placed a technical and financial burden on academic institutions to facilitate the successful transition to online learning, it provides opportunities to understand the impacts of adopting new policies and strategies to improve the efficient utilization of resources and thus reduce operational costs. The detailed analyses of the changes in energy consumption can support assessing the potential savings in electricity bills with the wide-scale adoption of online learning methods in the future as a business as usual to improve and modernize the education systems. This paper provides a detailed analysis of the electrical energy consumption of the buildings within the campus of the University of Jordan. The diversity of building types on the campus (e.g., university hospital, humanities schools, scientific schools) supports the provision of more general and robust recommendations to extend the results to other institutions, particularly in developing countries. The Energy Use Intensity (EUI) per unit area and EUI per student are employed for the first time for benchmarking the energy usage in educational buildings in Jordan. Overall, the analyses show that the total electricity consumption in 2020 was significantly lower than in 2019, with a decrease of 20.8% from 27.7 GWh in 2019 to 21.9 GWh in 2020. It is also found that the most significant reduction occurred in the humanities buildings (i.e., a 39% drop in energy consumption). However, this volume of energy reduction is still relatively low, considering the absence of students. Furthermore, the hospital has an extremely high EUI value (161 kWh/m2/year) compared to the other categories (e.g., the EUI for humanities schools is 32.5 kWh//m2/year). To conclude, the electrical energy consumption data suggests that there may be significant opportunities for energy conservation in all building categories, especially in the hospital.

Community Solar Operation Strategy for Smart Energy Communities Considering Resource Fairness

This study proposes a community solar operation strategy for smart energy communities (SECs), which comprise members of an energy consumption group, to minimize the electricity bill of its members. When sharing resources within a group, resource distribution is a critical problem, and fairness in resource sharing is the main constraint for operation. The proposed community solar operation is formulated as a mixed-integer liner problem that can be optimally solved using centralized control and future time information. However, obtaining information of a future time is not causal. By decomposing the problem into individual problems that are solved by each member at each decision time, the proposed strategy operates the community solar in a distributed manner with partial information. The simulation results using the real dataset recorded in Korea show that the use of the proposed operation strategy results in a fair distribution of electricity bill savings with a marginal benefit reduction of 10% compared to the optimal operation that requires a centralized control and information on the future time. Moreover, a discussion on the tradeoff between the benefits of electricity bill savings and guarantee of fairness is provided. Based on the results, this study can serve as a reference for the design of community solar operations for SECs.

Evaluating Electricity Bill Savings of Self-Consumption Pv in Italian Residential Sector

Evaluating Electricity Bill Savings of Self-Consumption Pv in Italian Residential Sector

Zero lost profit principle for solar compensation and its impact on bill savings

Several utilities and regulators are replacing net metering, the status quo policy that credits solar owners the retail electric price for each kilowatt-hour of excess solar power. So far avoided costs, the value of solar, and buy-all, sell-all models are implemented in place of net metering. This study proposes a zero lost profit principle for the design of solar compensation policies and evaluates impacts on electricity bill savings relative to other principles. A zero lost profit principle is defined as a solar compensation rate that leaves the utility indifferent between serving a solar and a non-solar household. Using constant average cost and extra-normal utility profit assumptions, we find that the zero lost profit principle (gross and net) does not lead to significant reductions in electricity bill savings. However, a net purchasing model based on the avoided cost principle leads to a 23% reduction in monthly bill savings relative to net metering. The framework proposed in this study provides utilities and regulators with additional principles for evaluating alternative solar compensation policies.

Adoption of renewable home heating systems: An agent-based model of heat pumps in Ireland

Consumer adoption of renewable energy technologies such as heat pumps for home heating is crucial in reducing greenhouse gas emissions and reliance on imported fossil fuels. In recognition of their potential, policymakers in several countries have introduced various financial incentives to encourage the uptake of renewable energy technologies. However, consumers' purchasing decisions and choice of a particular technology is a complex process that goes beyond financial aspects. In this paper, we examine the adoption decisions and diffusion of heat pumps for residential home heating using an agent-based modeling and simulation approach. In particular, we model the influence of three factors: economic, psychological, and social networks, on the future uptake of heat pumps. We utilize recent nationally representative Irish household survey data and historical heat pump uptake data to derive model parameters for decision rules based on empirical data and simulate the adoption of heat pumps in existing Irish homes until 2030. We further analyze the implications of those future uptakes on electricity demand, bill savings, and reduction in CO2 emissions. The findings of this research based on the case study of Ireland should be useful to policymakers and companies in devising monetary and non-monetary interventions aimed at increasing future actual uptake of heat pumps and other renewable energy technologies.

Integration of PCM as an external wall layer in reducing excessive heat of building walls

Innovative building approaches, which take advantage of heat energy in buildings, have recently appeared as part of a global effort to save energy. Incorporating phase change material (PCM) into the building envelope helps in reducing energy consumption and regulating energy demand by managing the thermal inertia of designed PCM thermal characteristics. A study was conducted to assess the performance benefits provided by the latent heat of the concrete wall combined with PCM. This study focuses on developing and testing heat barrier performance by incorporating PCM into wall external finishing, i.e. cement plaster and gloss paint. The effect of PCM inclusion in building wall were investigated by experimental work. The results indicate that incorporating PCM into the building wall reduced the surface temperature by up to 9 °C. Furthermore, the application of the PCM in the plaster layer is more reliable in reducing the internal wall surface temperature by a value of 8.1 °C when compared to the PCM in a painted coating. Painted wall panels experienced more significant temperature reduction differences than other wall panels, i.e. 9.2 °C and 9.5 °C, respectively. However, painted wall panels experienced higher internal surface temperatures than external surface temperatures compared to plastered wall panel at night. This could be due to the paint reactions, which are ineffective at releasing internal heat from the building at night. The yearly energy demand is decreased by 64.3% by incorporating PCM to the building wall, with a total annual electricity bill savings of 42.3% (8695.8 kWh yr−1). Therefore, it was concluded that wrapped PCM integrated into plaster layers on external surface building walls could decrease the indoor building temperature and thus contribute to conserving the energy required for an air conditioning system.

Residential Electricity Rate Plans and Their Selections Based on Statistical Learning

Demand response (DR) is one of the major benefits that utility companies can derive from the advanced metering infrastructure (AMI). In particular, the dynamic rate plan with DR is attracting attention as an electricity rate system suitable for the future power environment. In order for electricity consumers to select an appropriate electricity rate plan, it is necessary to provide information such as whether electricity bills are reduced by the plan and the estimated amount of electricity bill savings. In this paper, we first comparatively analyze the current progressive rate plan and a dynamic rate plan of the time-of-use (TOU). We next propose several prediction methods for households to provide information on whether the electricity bill amount can be reduced in advance when changing to the TOU rate plan from the progressive rate plan by using only the current monthly electricity usages and bills. In order to develop three different prediction methods based on statistical learning, we use the support vector machine, linear regression, and deep neural network techniques. As a ground truth training sequence, we use hourly electricity usages and bills obtained from ten apartment complexes through AMI, and an apartment complex is used for testing the designed methods. The decision accuracy for the test complex was more than 0.98 and the root mean square error of the saving prediction was 1.7%.

Peak Shaving with Battery Energy Storage Systems in Distribution Grids: A Novel Approach to Reduce Local and Global Peak Loads

The growing global electricity demand and the upcoming integration of charging options for electric vehicles is creating challenges for power grids, such as line over loading. With continuously falling costs for lithium-ion batteries, storage systems represent an alternative to conventional grid reinforcement. This paper proposes an operation strategy for battery energy storage systems, targeted at industrial consumers to achieve both an improvement in the distribution grid and electricity bill savings for the industrial consumer. The objective is to reduce the peak power at the point of common coupling in existing distribution grids by adapting the control of the battery energy storage system at individual industrial consumer sites. An open-source simulation tool, which enables a realistic simulation of the effects of storage systems in different operating modes on the distribution grid, has been adapted as part of this work. Further information on the additional stress on the storage system is derived from a detailed analysis based on six key characteristics. The results show that, with the combined approach, both the local peak load and the global peak load can be reduced, while the stress on the energy storage is not significantly increased. The peak load at the point of common coupling is reduced by 5.6 kVA to 56.7 kVA and the additional stress for the storage system is, on average, for a six month simulation, period only 1.2 full equivalent cycles higher.

Framework of transactive energy market pool for community energy trading and demand response management using an auction-theoretic approach

This paper presents a transactive energy market pool framework for facilitating energy trading, with demand response consideration, among a group of participants in a community microgrid using an auction-theoretic approach. The auction theory is used to design the pricing mechanism in the market pool. In the market, the self-interested participants (consumers and prosumers) directly trade their net demand to the neighborhood with a transactive energy market pool operator using the existing infrastructure of the distribution utility. The market operator determines the pool market-clearing price & quantity by optimizing the received power bids and offers from the participants using a periodic iterative double auction pricing mechanism. The optimally traded price & quantity are broadcast to all the participants to perform demand response management and optimize their electricity bill. The optimal positions of schedulable loads in the market time-line are achieved using a binary genetic algorithm while minimizing the electricity bill. A comparative analysis between different pricing mechanisms is provided in terms of performance indices namely self-sufficiency and self-consumption through various case studies. It is found that the proposed auction-theoretic approach improves the rate of community self-sufficiency, rate of community self-consumption, and savings in electricity bills for the market participants compared to previously proposed pricing methods in the literature.

Performance gaps of sustainability features in green award-winning university buildings

Sustainability certifications like BREEAM, LEED, and China's sustainable green building award certification scheme encourage installation of technologies that save mains water and grid electricity. Among these are rainwater harvesting systems, ultralow water use appliances, photovoltaic panel systems, and intelligent building management systems. In reviewing the performance of two award-winning university buildings over respective periods of sixteen and four years, we found that such systems delivered only 28–71% of their potential resource savings. These performance gaps arose from various technical and social issues (pump failures, tank leakages, poor alignment of demand and supply with limited storage, low photovoltaic panel efficiency, poor user acceptance, etc.), but the consequences were exacerbated by inadequate asset management that resulted in long system downtimes, in some cases for 2–5 years. Repair, maintenance, and upgrading expenses then combined with lower than anticipated water and electricity bill savings that ultimately meant that, for the most part, there was no prospect of earning a return on capital expenditures. Continuous monitoring of building water consumption by an external service provider was the most effective resource and cost saving solution in this study, as it required no capital expenditure, and revealed a 1640 l/h leakage, without putting high demands on the building management. In contrast, little value was obtained from 25 water-related sensors installed as part of a “building-as-a-lab” project because of inadequate post hand-over support. Robust post-commissioning operation should become a key criterion for sustainable building innovation, and this should be reflected in green awards and rating systems.

Bundling residential rooftop photovoltaics with energy efficiency upgrades: does it really pay off?

Using data from a survey of solar adopters in the USA, the present paper examines the effect of adding insulation on electricity bill savings. We identify whether solar adopters added insulation to their house close to the time of rooftop photovoltaics (PV) installation as a bundling strategy, and examine whether such decisions are correlated with higher electricity bill savings. We find that only 7% of solar adopters in the sample ended up bundling their PV installation with additional insulation. About 58% of solar adopters in the sample have not added insulation at all. The evidence in the present study suggests that solar adopters who choose the bundling strategy have larger, older houses, located in counties with higher electricity prices than those adopters who did not add insulation at all. Results show that while all solar adopters who choose the bundling strategy have a higher average dollar amount of savings, only those with high initial bills end up with a higher percentage of savings. The results of the present study provide some insights into the energy decision-making of households and provide some input for policies focused on combining renewable energy with efficiency standards.

An Actor-Critic approach for control of Residential Photovoltaic-Battery Systems

Abstract The rationale of shifting towards green energy, along with the cost reduction and the increasing capacity of lithium-ion batteries, has motivated the end-users to go for energy storage systems integrated with solar technology solutions. Such systems provide the end-users with greater flexibility, thereby enhancing their role as prosumers in a range of grid-management programs. In this regard, we consider a residential household equipped with a battery and photovoltaic panels, collectively known as the photovoltaic-battery (PV-B) system. We further learn (off-line) a deterministic sub-optimal policy for charging/discharging of the residential battery using an actor-critic reinforcement learning based method. Such proposed approach, named polynomial deterministic policy gradient (PDPG), does not require any model of the system and uses polynomials as function approximator, as opposed to conventional neural networks. The usefulness of the proposed approach is tested on real power data (demand and PV generation) of a residential household in Australia. Numerical simulations indicate that the proposed PDPG algorithm outperforms the OFFON control approach in terms of electricity bill savings and the model-based receding horizon control in terms of computation time.

Digital Twin for Operation of Microgrid: Optimal Scheduling in Virtual Space of Digital Twin

Due to the recent development of information and communication technology (ICT), various studies using real-time data are now being conducted. The microgrid research field is also evolving to enable intelligent operation of energy management through digitalization. Problems occur when operating the actual microgrid, causing issues such as difficulty in decision making and system abnormalities. Using digital twin technology, which is one of the technologies representing the fourth industrial revolution, it is possible to overcome these problems by changing the microgrid configuration and operating algorithms of virtual space in various ways and testing them in real time. In this study, we proposed an energy storage system (ESS) operation scheduling model to be applied to virtual space when constructing a microgrid using digital twin technology. An ESS optimal charging/discharging scheduling was established to minimize electricity bills and was implemented using supervised learning techniques such as the decision tree, NARX, and MARS models instead of existing optimization techniques. NARX and decision trees are machine learning techniques. MARS is a nonparametric regression model, and its application has been increasing. Its performance was analyzed by deriving performance evaluation indicators for each model. Using the proposed model, it was found in a case study that the amount of electricity bill savings when operating the ESS is greater than that incurred in the actual ESS operation. The suitability of the model was evaluated by a comparative analysis with the optimization-based ESS charging/discharging scheduling pattern.

Do Star Ratings Matter?

Increasing environmental concerns have resulted in consumers indulging in conserving energy by curtailing energy usage rather than switching to energy efficient practices. Energy efficient appliances (EEAs) offer the dual advantages of appliance usage with reduced energy consumption. Research suggests that use of such appliances, in residences is limited. This study was thus undertaken to understand individual resident's awareness towards EEAs and factors influencing their purchase. A qualitative approach consisting of 31 personal interviews were conducted with individuals from socio-economic categories A1, A2 and B1. While awareness of EEAs was present among respondents; benefits of using such appliances were neither widely known nor easily quantifiable. Purchase decisions were ruled by appliance price but did not deter adoption, the availability of appliances in desired aesthetics and family involvement in purchase decision. Higher penetration of such appliances can be ensured if consumers can estimate exact savings in monthly electricity bills due to EEAs at the time of purchase.