Monthly Electricity Bill Research Articles

TRU Energy Monitoring for Potential Cost Saving in Electricity Bills for Cathodic Protection Units: South African Case

Reducing the electricity bill in the industrial sector is an important problem worldwide. This study focuses on the awareness of industries to Cathodic Protec-tion (CP) energy conservation and on the potential of reducing electricity bills by a change of tariff or making use of renewable energy. Due to the frequent increase in energy cost at a significant rate, many indusial consumers are looking for ways to reduce the monthly electricity bill. The study aims to identify if it will be possible to use options such as renewable energy to supply CP systems, or if a change of tariff can help reduce the monthly bills. To achieve this, a real-time energy-monitoring device “Efergy E2” was installed in one of the Transformer Rectifier Units (TRU), the monitored TRU is located at Ndwedwe reservoir 2 in the areas of Durban. Among other benefits, the hourly load data analysis can provide the detailed characteristics of load demand, define the consumption patterns and can help to identify where the consumer could reduce the electricity bill. The results indicate that the load is almost constant throughout the day and changing to Time of Use (TOU) tariff does reduce the bills. However, the fixed charges amount to 11 times energy charges, hence the best way is to make use of renewable energy rather than changing a tariff.

Ingredients for growth: Examining electricity consumption and complementary infrastructure for Small and Medium Enterprises in Kenya

In Kenya, between 2010 and 2015, the number of Small and Medium Enterprises (SMEs) connected to the grid increased by over 60%. Despite this substantial increase, little is known about the behavioural patterns or conditions that contribute to increased electricity consumption among these SMEs. This study addresses the problem through a longitudinal analysis of monthly electricity bills for over 179,000 grid connected SMEs in Kenya. We then leverage multiple publicly available geospatial datasets to estimate how complementary infrastructural variables (such as access to roads, markets, financial services, and macro/micro-economic conditions) correlate with sustained electricity consumption growth by SMEs. Results from our longitudinal analysis indicate that newly electrified SMEs in urban areas have higher median consumption than their older counterparts while in rural areas, more newly connected SMEs appear to have lower median consumption. We find the effects of complementary infrastructure on SME electricity consumption to be more pronounced in rural areas than urban areas. For example, SMEs located in rural neighbourhoods with close proximity to roads, markets or financial service providers are associated with a 10% to 16% increase in electricity consumption while in urban areas, we only observe about a 2% increment in electricity consumption for SMEs within close proximity to roads. All other infrastructural variables are either statistically insignificant or negatively correlated with urban SME electricity consumption.

Virtual storage capability of residential buildings for sustainable smart city via model-based predictive control

This paper evaluates the virtual storage capability of a residential air-conditioning (AC) system by utilizing the building mass as a thermal storage to enable sustainable cities through model-based predictive control (MPC). The control-oriented building model was developed with a grey-box model structure based on the experimental data to predict the indoor air temperature. Based on the model, the operation cost-saving potential of the MPC was investigated in a single house with different comfort levels, electricity prices, and prediction horizons. The cost-saving of the MPC was approximately 10.6 % compared to the conventional control. The MPC was expanded to a residential building cluster considering the peak demand charge. In an hourly shedding and load-up scenario, the performances of the MPC and the heuristic prior-based control (PBC) are promising. When shedding was enforced all day, the peak demand saving of the MPC was 36∼38 %, whereas that of the PBC was 25.7 % compared to the baseline. In addition, the monthly electricity bill, including the operation and peak demand cost, was investigated with different demand charge rates and weather conditions. The total saving decreased with a low demand charge rate and hot conditions, and the operation cost saving was compromised with more aggressive demand shedding.

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.

PEMASANGAN PANEL SOLAR BAGI MENAMPUNG BEKALAN ELEKTRIK TAMBAHAN UNTUK INSTITUSI PENDIDIKAN AGAMA PERSENDIRIAN DI LUAR BANDAR: MELALUI PENDEKATAN PROGRAM KEMASYARAKATAN KOMUNITI

The installation of solar panels in rural community Malaysia are still preliminarily explored due to the excessive cost and limited access to the technology. This limitation has also led to dissemination delays especially in public-funded buildings such as mosques, public halls, hospitals and schools. Meanwhile, the existing subsidy of electricity supply rate to the society has led the community to become highly dependent and demanded on the power supply from Tenaga Nasional Berhad (TNB). Therefore, the increase of electricity tariff since 2014, has subsequently resulted in the increasing charge of monthly electricity bills. Without awareness, the electricity usage and charges will keep on increasing and may affect the monthly expenses especially to the public and private institutions. This situation may become worst to the self-funded institutions in rural areas including the ‘tahfiz’, international and conventional religious schools. The concern of this excessive charges on electricity tariff may influence these institutions to outsource funds such as through collecting donations from the community in which are not sustainably sufficient. Therefore, this research investigates an alternative supply of electricity that may reduce the cost and will benefit the institutions through bill-savings. The objective is to determine whether solar panel installation through a community-service programme can help the institutions to not only becoming electricity-sufficient but could also save the energy by generating power from solar energy. A case study was conducted at the ‘tahfiz’ school in Perak Tengah to determine the effectiveness of how this institution could reduce electricity bills besides establishing the green energy initiative. Remarkably, through the installation of a 2 kW solar power system, this research has discovered that the institutions have successfully saved 70% of the existing monthly electricity expenses. Therefore, this finding acknowledged solar energy through community-service as sufficient green initiative programme towards achieving sustainable living.

Annualized Electricity Cost of Residential Solar PV System under Malaysia’s NEM Scheme

Net energy metering (NEM) is a financial scheme that allows a consumer to generate, use and sell their excess energy to the grid. The main purpose of NEM is for self-consumption to reduce demand from the grid. It will allow customer to avoid being charged with expensive electricity tariff and hence reducing their monthly electricity bill. In other words, the annualized electricity cost could be reduced. NEM is commonly offered to residential solar photovoltaic (PV) system. Different PV size will determine the amount of energy that can be generated. This paper compares the annualized electricity cost of different residential customer types (large, medium and small) for different PV size under Malaysia’s net energy metering (NEM) scheme. This paper utilizes the load profile and solar irradiation data for Malaysia. The results show that high PV size does not guarantee reduction in annualized electricity cost especially for medium customers as the excess PV generation can only be accumulated for 24 months. Large customers may have benefited the most with lower annualized cost with larger PV system, while small customers may not have benefited at all.

Multiple influencing factors analysis of household energy consumption in high-rise residential buildings: Evidence from Hong Kong

Buildings account for more than 90% of total electricity consumption in Hong Kong, one third of which comes from the residential sector. High-rise buildings dominate Hong Kong, but energy use in high-rise buildings has been insufficiently examined in previous studies, especially at the household or occupant level. This paper aims to explore the multiple factors that influence energy consumption in high-rise residential buildings, including the impact of occupant behaviours. The research was conducted through a questionnaire and face-to-face interviews with 135 households of a typical forty-floor residential building in Hong Kong. The survey examined technical and physical factors, human-influenced factors and social factors of energy consumption, including building information, social demographics, energy-related occupant behaviour modes and the residents’ energy-saving attitudes. The results show that the monthly electricity bills of households at the twentieth floor or lower were 26% higher than those of households at higher floors during spring, summer and autumn, but similar during winter. This difference was attributed to various occupant behaviours, such as operating air-conditioners and opening windows. These findings expand the knowledge of occupant behaviour in high-rise residential buildings and inform building energy conservation policy-making in Hong Kong.

Practical Considerations For Customer-sited Energy Storage Dispatch On Multiple Applications Using Model Predictive Control

Government subsidies for energy storage and renewable generation have led to the cost of energy storage come down during recent years. This has motivated people to deploy behind-the-meter energy storage units, to reduce their monthly electricity bill. For optimal control of the battery to incorporate maximum photovoltaic energy generation as well as demand charge reduction, data-driven and advanced Battery Energy Storage System (BESS) control strategies are required. This paper explores different use cases where customers could deploy energy storage systems for demand charge reduction as well as when customers could deploy energy storage systems for demand charge reduction while satisfying a utility set objective. From historical load and PV data, different use cases are simulated using a Model Predictive Control (MPC) based BESS control model. MPC requires machine-learning (ML) based forecasts of photovoltaic (PV) as well as load as inputs. A sensitivity analysis on the effect of different energy forecasts on the performance of MPC is presented in the paper. A degradation analysis with as a function of charge/discharge cycles is also presented in the paper to evaluate the trade-off between economic objectives and battery health.

Towards sustainable developing cities: A simplified forecasting model for sizing grid-tied PV using monthly electricity bills

The recent reductions in PV costs and the convenient concurrence of insolation and schools’ energy usage have resulted in increased interest in augmenting supply with solar PV to save on energy costs and unburden the grid in developing countries. However, optimal sizing of PV solutions requires a detailed analysis and hourly simulation to match demand, council tariff structures (incl. import vs. export rates) and geography. This complexity exposes already resource-constrained authorities to abuse by overzealous and unwitting suppliers, and currently impedes large-scale deployment of solar PV in a sunshiny cities depraved of its requisite energy. We present a novel approach to forecast schools’ hourly demand using only monthly utility bills and a trained forecasting model. We also propose an iterative solar sizing technique to assess the economic viability of using PV at schools to support government and city council officials. The results show that the method is able to forecast annual energy usage and monthly demand to within 5% and 6% respectively, while accurately determining the potential return on investment.

The Relationship of Awareness and Satisfaction to Consumer Motivation in Energy Consumption Behavior

In supporting United Nation Sustainable Development Goal (SDG), the government of Malaysia has implemented policy and initiative to improve energy efficiency. In spite of these initiates, the electricity consumption has increased yearly as reported by Malaysia Energy Commission (MEC). Hence, this study aims to (1) investigate factor on awareness in energy consumption and efficiency of residential users and their motivation to change their consumption behavior, and (2) examine the relationship between satisfaction of residential users as the moderating factor to their motivation to change user consumption behavior. A total of 400 residential energy users have participated in the survey and data was analyzed using Smart PLS. Results indicated that consumer awareness of monthly electrical bill and satisfaction towards energy efficient product has positive effect on consumer motivation about current energy issue. This may indicate that the increase in monthly electricity bill has an effect on consumer awareness on their electrical consumption. In addition, consumer satisfaction towards energy efficient product leads to higher motivation level of users to modify their energy consumption behavior.

The South Korean public’s evaluation of the mix of power generation sources: A choice experiment study

The South Korean government is pursuing an energy transition, which means a reduction in nuclear power and coal-fired power generation, and an expansion into renewable energy. This study seeks to evaluate the South Korean public’s preference for a mix of power generation sources. For this purpose, 1000 households throughout the country were randomly selected and a choice experiment survey of them was undertaken in March 2018. We considered four attributes: the ratio of nuclear power, the ratio of coal-fired generation, the ratio of natural gas-fired generation, and the ratio of renewable energy. An increase in the monthly electric bill was also considered as an attribute. The results of applying the choice experiment approach show that households were willing to accept an increase in their monthly electric bill by KRW 192 (USD 0.17) and KRW 165 (USD 0.15) for reducing the proportion of nuclear power and coal, respectively, by 1%p. They were willing to pay KRW 159 (USD 0.14) and KRW 409 (USD 0.38) for raising the ratio of natural gas and renewable energy, respectively, through an increase in the monthly electricity bill. The findings reveal that the government’s energy transition has overall support from the public.

Optimal Design of a Residential Photovoltaic Renewable System in South Korea

An optimal design model for residential photovoltaic (PV) systems in South Korea was proposed. In the optimization formulation, the objective function is composed of three costs, including the monthly electricity bill, the PV system construction cost (including the government’s subsidy), and the PV system maintenance cost. Here, because the monthly electricity bill is not differentiable (it is a stepped piecewise linear function), it cannot be solved by using traditional gradient-based approaches. For details considering the residential electric consumption in a typical Korean household, consumption was broken down into four types (year-round electric appliances, seasonal electric appliances, lighting appliances, and stand-by power). For details considering the degree of PV generation, a monthly generation dataset with different PV tilt angles was analyzed. The optimal design model was able to obtain a global design solution (PV tilt angle and PV size) without being trapped in local optima. We hope that this kind of practical approach will be more frequently applied to real-world designs in residential PV systems in South Korea and other countries.

넷 제로에너지주택 실증사례 분석에 관한 연구

Purpose: This study analyzed and evaluated the NZEB (Net Zero Energy Building) on energy and cost based an electricity data from KEPCO (Korean Electric Power Corporation). Method: The experiment was conducted in three houses with different location and size. The experimental houses were constructed with high thermal insulation and air tightness, and also designed as all-electric houses where all the energy supplies (including heating and cooking) are made of electricity which reduces the maintenance cost and makes maintenance easier. 6kWp of Grid connected Photovoltaic System and air source heat pump for heating and hot water were applied to all houses, and one of them had an additional of solar domestic-hot water system with 5m² of collector. Result: For two years, all energy (including plug load, heating, cooling, lighting, how water supply and ventilation) was supplied by PV system and consequentially zero energy was achieved in two houses except A. Monthly electricity bill by the amount of used were not charged, however, additional fees by domestic electricity charging system were charged such as basic electricity fee, VAT on receiving electricity and development fund; average $123 were paid per household.

Accelerating power generation with solar panels. Case in Latvia

The main aim of the research is to determine the conditions under which it would be possible to increasingly cover as much electricity demand of Latvia as possible by the electricity generated by solar panels. A Microsoft Excel model was developed with an assumption that it would be efficient to install solar panels if the investments returned in a five-year period or sooner. A restriction was set that only household users with solar panels would be taken into account. The model included data from 15 case studies. Based on the collected data, the average monthly electricity bill was calculated before and after installing the solar panels and subsequently the return of investments period in years was calculated. Several model’s positions were variated – the solar panels’ efficiency rate, the price of the solar panels, etc. – to find out which combination of changes would result in a five-year return of investments period.

Perceived and Reported Reliability of the Electricity Supply at Three Urban Locations in Indonesia

This paper focuses on the reliability of electricity supply at three different locations in Indonesia, namely in Sumatra, Timor, and Papua, through a comparison of reported indices of power reliability (SAIFI and SAIDI) and experimental results from user surveys and power measurements. The reason for this study is the lack of information about the actual, quantified reliability of power supplied by the main grid in Indonesia, while narratives of end-users indicate the reliability might be unsatisfactory. The study was executed using data from 114 randomly-selected respondents in the city of Pekanbaru in Sumatra, 65 in the city of Kupang in Timor and 26 in the city of Jayapura in Papua, totaling 205 respondents. These users experienced a higher unavailability of power delivered by the grid than expressed by the utility-reported SAIDI and SAIFI. Therefore, for this study, new indices are introduced, namely the Perceived (P) SAIDI and SAIFI, which are based on the frequency and duration of blackouts experienced by the users. It is concluded that the reported reliability indices do not always demonstrate the experience of the grid users. P-SAIFIs were 1.3 to 4.6 times higher in Pekanbaru and Kupang, respectively than the utility-reported SAIFIs for the same provinces. Also, P-SAIDIs were 2.6 to 3.9 times higher in Pekanbaru and Kupang, respectively, than the utilities’ SAIDIs. It is therefore not surprising that depending on the location, 14% to 65% of the users own a backup generator and that households are willing to pay $3 to $8 extra per monthly electricity bill or $1c–$3c per kWh for improved reliability.

Digital Household Energy Meter with GSM Communication for Home Energy Management

This design is developed with the main aim of assisting energy consumers and utility service providers with an enhanced feature for better home energy management. Automatic generation of the monthly electricity bill avoids the prevailing drawbacks of the current energy measuring system such as time wastage, accuracy issues, human errors and possibility for fraud activities. This system can be effectively used for real time measuring and analyzing of the household energy usage. The device utilizes GSM technology to alert the consumers with energy readings in Kilo Watt hours (kWh). Any individual or an organization with an approved electricity connection by the standard utility service provider can use this device. Crucial parameters of energy appliances such as Power Factor, Rated Power and Root Mean Square (RMS) Current were analyzed with the design obtaining results appropriately. Demand charge can be effectively controlled avoiding the overall household demand exceeding a preset demand value. As evident from the specifications and results this study fulfills a prudent requirement in the home energy management sector.

Measuring public understanding on Tenaga Nasional Berhad (TNB) electricity bills using ordered probit model

In 2016, Tenaga Nasional Berhad (TNB) had introduced an upgrade in its Billing and Customer Relationship Management (BCRM) as part of its long-term initiative to provide its customers with greater access to billing information. This includes information on real and suggested power consumption by the customers and further details in their billing charges. This information is useful to help TNB customers to gain better understanding on their electricity usage patterns and items involved in their billing charges. Up to date, there are not many studies done to measure public understanding on current electricity bills and whether this understanding could contribute towards positive impacts. The purpose of this paper is to measure public understanding on current TNB electricity bills and whether their satisfaction towards energy-related services, electricity utility services, and their awareness on the amount of electricity consumed by various appliances and equipment in their home could improve this understanding on the electricity bills. Both qualitative and quantitative research methods are used to achieve these objectives. A total of 160 respondents from local universities in Malaysia participated in a survey used to collect relevant information. Using Ordered Probit model, this paper finds respondents that are highly satisfied with the electricity utility services tend to understand their electricity bills better. The electric utility services include management of electricity bills and the information obtained from utility or non-utility supplier to help consumers manage their energy usage or bills. Based on the results, this paper concludes that the probability to understand the components in the monthly electricity bill increases as respondents are more satisfied with their electric utility services and are more capable to value the energy-related services.

Residential electricity cost minimization model through open well-pico turbine pumped storage system

A residential electricity cost minimization model is proposed which can be implemented in a suburban setup where open wells are present for domestic needs. Here, a solar photo voltaic (SPV) system with pico hydro turbines (PHTs) and pump are used for minimizing the monthly electricity bill in a dynamic electricity pricing environment. Also, the available water in the open well is optimally used in order to minimize the residential electricity cost. In situations when either the price of the energy from the grid is low or when the available energy from the SPV system is in excess of the demand, the proposed model stores the energy in the form of gravitational potential energy of water in a reservoir. The stored energy is then retrieved using PHTs which feeds the load at the time when the energy price is high. The depth of the well is used as the working head for the operation of turbines and are optimally scheduled in order to minimize the water flow rate (WFR). The two fold objectives, i.e., minimizing the electricity cost and minimizing the WFR, is converted into a single objective function and is solved using particle swarm optimization (PSO). The payback period for the proposed system, if implemented, is also investigated as a case study in India.

Development of a real-time non-intrusive appliance load monitoring system: An application level model

The research “Behavior Change and Energy Use” (US Department of Energy and Climate Change, 2011) [1] shows that with better information in the monthly electricity bill, the Energy Performance Certificate (EPC) can encourage people to reduce their energy usage. That is why smart meters - the emerging technology to help people to know their monthly energy consumption, are gradually replacing mechanical power meters. In this paper, we investigate a special energy monitoring process named Non-Intrusive Appliance Load Monitoring (NIALM), which is potentially the best method to give consumers pertinent information with respect to power consumption. However, real-time feedback feature in a low cost NIALM system is still a big challenge in such technology because of the complication in NIALM’s algorithms. System on Chip (SoC) technology can solve this challenge. Besides including high-speed interconnection and multi-processors, integrating Field-Programmable Gate Array (FPGA) into SoCs may be the most important evolution, which provides developers a powerful tool to develop a low cost but high performance system. Therefore, in this paper we proposed a development of a real-time NIALM system based on the SoC with FPGA acceleration.

Optimal household appliance scheduling considering consumer's electricity bill target

This paper presents an optimization algorithm that schedules the operations of household appliances to minimize the monthly electricity bill and maintain comfort for electricity consumers through the interaction between a home energy management system (HEMS) and consumers. In comparison with existing HEMS optimization algorithms over a single day time horizon without considering the monthly electricity bill, the novelty of the proposed method is that the monthly bill target preferred by the consumer is achieved through the optimal operation of appliances over a multi-day time horizon. A key part of the proposed approach is to relax the multi-day optimization problem by adding a penalty on the range of consumer preferred indoor temperature related to operation of the air conditioner, consequently leading to calculation of the desired monthly electricity bill. Simulation studies are illustrated with a single household and four households equipped with smart home appliances in time of use (TOU) and inclining block rate (IBR) pricing tariffs. The results demonstrate that the proposed method enables the total electricity cost and cumulative electricity consumption to successfully converge to each consumer’s target. Furthermore, the impacts of the penalty variable for the relaxed consumer thermal condition and the energy trade between households on the performance of the proposed algorithm are investigated.