Abstract: China’s declared transformation towards a ‘new electricity system dominated by renewable energy’ requires a cleaner electricity consumption mix with high shares of renewable energy sourced-electricity (RES-E). Unfortunately, integration of RES-E into Chinese electricity markets remains a problem pending more robust legal support, evidenced by the curtailment of wind and solar power due to integration constraints. The upcoming Energy Law of the PRC (Energy Law) is expected to provide such long-awaiting support and coordinate the existing diverse sector-specific laws to deal with the weak implementation that dampening the delivery of their desired regulatory effects. However, in the shadow of the COVID-19 crisis, it remains uncertain how this new Energy Law brings synergies to RES-E integration, mindful of the significant impacts of the pandemic. Through the theoretical lens of the interplay between China’s electricity market reform and legislative development, this paper investigates whether there is a paradigm shift in Energy Law regarding renewable energy integration compared with the existing sector-specific energy laws. It examines the 2020 Draft for Comments on the Energy Law and analyses its relationship with sector-specific energy laws focusing on RES-E integration. The comparison is drawn upon five critical aspects of the RES-E integration issue, including the status of renewables, marketisation, incentive schemes, consumption mechanisms, access to power grids and dispatching. The analysis shows that it is reasonable to expect a more open and well-organised electricity market, enabling the absorption of high shares of RES-E. The present paper concludes that a period of prosperous development of RES-E in the post-COVID-19 era can be anticipated with the legal support by the upcoming Energy Law. It contributes to understanding the signals China is sending regarding the transition towards a cleaner energy future.
Abstract: To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.
Abstract: The electricity consumption in the Japanese household sector has increased with higher rate than that of other sectors. This may be because of aging and information oriented society that requires more electrical appliances to make the life better and easier, under this circumstances, energy saving is one of the essential necessity in Japanese society. To understand the way of energy use and demand response of the residential occupants, it is important to understand the structure of energy used. Home Energy Management System (HEMS) may be used for understanding the pattern and the structure of energy used. HEMS is a visualization system of the energy usage by connecting the electrical equipment in the home and thereby automatically control the energy use in each device, so that the energy saving is achieved. Therefore, the HEMS can provide with the easiest way to understand the structure of energy use. The HEMS has entered the mainstream of the Japanese market. The objective of this study is to understand the pattern of energy saving and cost saving in different regions including Japan during HEMS use. To observe thermal comfort level of HEMS managed residential buildings in Japan, the field survey was made and altogether, 1534 votes from 37 occupants related to thermal comfort, occupants’ behaviors and clothing insulation were collected and analyzed. According to the result obtained, approximately 17.9% energy saving and 8.9% cost saving is possible if HEMS is applied effectively. We found the thermal sensation and overall comfort level of the occupants is high in the studied buildings. The occupants residing in those HEMS buildings are satisfied with the thermal environment and they have accepted it. Our study concluded that the significant reduction in Japanese residential energy use can be achieved by the proper utilization of the HEMS. Better thermal comfort is also possible with the use of HEMS if energy use is managed in a rationally effective manner.
Abstract: To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.
Abstract: In most existing buildings in hot climate, cooling
loads lead to high primary energy consumption and consequently
high CO2 emissions. These can be substantially decreased with
integrated renewable energy systems. Kuwait is characterized by its
dry hot long summer and short warm winter. Kuwait receives annual
total radiation more than 5280 MJ/m2 with approximately 3347 h of
sunshine. Solar energy systems consist of PV modules and parabolic
trough collectors are considered to satisfy electricity consumption,
domestic water heating, and cooling loads of an existing building.
This paper presents the results of an extensive program of energy
conservation and energy generation using integrated photovoltaic
(PV) modules and Parabolic Trough Collectors (PTC). The program
conducted on an existing institutional building intending to convert it
into a Net-Zero Energy Building (NZEB) or near net Zero Energy
Building (nNZEB). The program consists of two phases; the first
phase is concerned with energy auditing and energy conservation
measures at minimum cost and the second phase considers the
installation of photovoltaic modules and parabolic trough collectors.
The 2-storey building under consideration is the Applied Sciences
Department at the College of Technological Studies, Kuwait. Single
effect lithium bromide water absorption chillers are implemented to
provide air conditioning load to the building. A numerical model is
developed to evaluate the performance of parabolic trough collectors
in Kuwait climate. Transient simulation program (TRNSYS) is
adapted to simulate the performance of different solar system
components. In addition, a numerical model is developed to assess
the environmental impacts of building integrated renewable energy
systems. Results indicate that efficient energy conservation can play
an important role in converting the existing buildings into NZEBs as
it saves a significant portion of annual energy consumption of the
building. The first phase results in an energy conservation of about
28% of the building consumption. In the second phase, the integrated
PV completely covers the lighting and equipment loads of the
building. On the other hand, parabolic trough collectors of optimum
area of 765 m2 can satisfy a significant portion of the cooling load,
i.e about73% of the total building cooling load. The annual avoided
CO2 emission is evaluated at the optimum conditions to assess the
environmental impacts of renewable energy systems. The total annual
avoided CO2 emission is about 680 metric ton/year which confirms
the environmental impacts of these systems in Kuwait.
Abstract: The causality between energy consumption and
economic growth has been an important issue in the economic
literature. This paper studies the causal relationship between
electricity consumption and economic growth in Mexico for the
period of 1971-2011. In so doing, unit root and causality tests are
applied. The results show that energy consumption and economic
growth series are stationary and there is also a causality relationship
running from economic growth to electricity consumption. Therefore,
any energy conservation policy would have little or no impact at all
on economic growth in México.
Abstract: This study addresses a concept of the Sustainable Building Environmental Model (SBEM) developed to optimize energy consumption in air conditioning and ventilation (ACV) systems without any deterioration of indoor environmental quality (IEQ). The SBEM incorporates two main components: an adaptive comfort temperature control module (ACT) and a new carbon dioxide demand control module (nDCV). These two modules take an innovative approach to maintain satisfaction of the Indoor Environmental Quality (IEQ) with optimum energy consumption; they provide a rational basis of effective control. A total of 2133 sets of measurement data of indoor air temperature (Ta), relative humidity (Rh) and carbon dioxide concentration (CO2) were conducted in some Hong Kong offices to investigate the potential of integrating the SBEM. A simulation was used to evaluate the dynamic performance of the energy and air conditioning system with the integration of the SBEM in an air-conditioned building. It allows us make a clear picture of the control strategies and performed any pre-tuned of controllers before utilized in real systems. With the integration of SBEM, it was able to save up to 12.3% in simulation of overall electricity consumption, and maintain the average carbon dioxide concentration within 1000ppm and occupant dissatisfaction in 20%.
Abstract: This paper presents a detailed description of evaporative cooling systems used for space cooling in Mina Valley, Saudi Arabia. The thermal performance and environmental impact of the evaporative coolers were evaluated. It was found that the evaporative cooling systems used for space cooling in pilgrims’ accommodations and in the train stations could reduce energy consumption by as much as 75% and cut carbon dioxide emission by 78% compared to traditional vapour compression systems.
Abstract: As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 period. Unlike previous studies on Malaysia, the current study focuses on the residential sector, a sector that is important for the contemplation of energy policy. The Phillips-Perron (P-P) unit root test is employed to infer the stationarity of each variable while the bound test is executed to determine the existence of co-integration relationship among the variables, modelled in an Autoregressive Distributed Lag (ARDL) framework. The CUSUM and CUSUM of squares tests are applied to ensure the stability of the model. The results suggest the existence of long-run equilibrium relationship and bidirectional Granger causality between EC and the macroeconomic variables. The empirical findings will help policy makers of Malaysia in developing new monitoring standards of energy consumption. As it is the major contributing factor in economic growth and CO2 emission, there is a need for more proper planning in Malaysia to attain future targets in order to cut emissions.
Abstract: Hospitals represent approximately 6% of total energy consumption in the utility buildings sector. Heating, Ventilation and Air Conditioning (HVAC) systems are the major part of electrical energy consumption at the hospitals. The air-conditioning system is responsible for around 70% of total electricity consumption. Electric motors and lighting systems in a hospital represent approximately 19% and 21% of the total energy consumption, respectively. In this paper, profiles of hospital energy end-use consumption and an overview of energy saving areas at the hospitals are presented.
Abstract: So much energy is used in high rise buildings to fulfill
the basic needs of users such as lighting and thermal comfort.
Malaysia has hot and humid climate, buildings especially high rise
buildings receive unnecessary solar radiation that cause more solar
heat gain. Energy use specially electricity consumption in high rise
buildings has increased. There have been growing concerns about
energy consumption and its effect on environment. Building, energy
and the environment are important issues that the designers should
consider to them. Self protected form is one of possible ways against
the impact of solar radiation in high rise buildings. The Energy
performance of building envelopes was investigated in term of the
Overall Thermal Transfer Value (OTTV ).In this paper, the amount
of OTTV reduction was calculated through OTTV Equations to
clear the effectiveness of self shading strategy on minimizing energy
consumption for cooling interior spaces in high rise buildings which
has considerable envelope areas against solar radiation. Also increasing
the optimum window area was investigated using self-shading
strategy in designing high rise buildings. As result, the significant
reduction in OTTV was shown based on WWR.In addition slight
increase was demonstrated in WWR that can influence on visible
comfort interior spaces.
Abstract: The heat storage capacity of concrete in building shells is a major reason for excessively large electricity consumption induced by indoor air conditioning. In this research, the previously developed Smart Temperature Information Material (STIM) is embedded in two groups of exterior wall specimens (the control group contains reinforced concrete exterior walls and the experimental group consists of tiled exterior walls). Long term temperature measurements within the concrete are taken by the embedded STIM. Temperature differences between the control group and the experimental group in walls facing the four cardinal directions (east, west, south, and north) are evaluated. This study aims to provide a basic reference for the design of exterior walls and the selection of heat insulation materials.
Abstract: ZnO nanocrystals with mean diameter size 14 nm
have been prepared by precipitation method, and examined as
photocatalyst for the UV-induced degradation of insecticide diazinon
as deputy of organic pollutant in aqueous solution. The effects of
various parameters, such as illumination time, the amount of
photocatalyst, initial pH values and initial concentration of
insecticide on the photocatalytic degradation diazinon were
investigated to find desired conditions. In this case, the desired
parameters were also tested for the treatment of real water containing
the insecticide. Photodegradation efficiency of diazinon was
compared between commercial and prepared ZnO nanocrystals. The
results indicated that UV/ZnO process applying prepared
nanocrystalline ZnO offered electrical energy efficiency and
quantum yield better than commercial ZnO. The present study, on the
base of Langmuir-Hinshelwood mechanism, illustrated a pseudo
first-order kinetic model with rate constant of surface reaction equal
to 0.209 mg l-1 min-1 and adsorption equilibrium constant of 0.124 l
mg-1.
Abstract: 98% of the energy needed in Taiwan has been
imported. The prices of petroleum and electricity have been
increasing. In addition, facility capacity, amount of electricity
generation, amount of electricity consumption and number of Taiwan
Power Company customers have continued to increase. For these
reasons energy conservation has become an important topic. In the
past linear regression was used to establish the power consumption
models for chillers. In this study, grey prediction is used to evaluate
the power consumption of a chiller so as to lower the total power
consumption at peak-load (so that the relevant power providers do not
need to keep on increasing their power generation capacity and facility
capacity).
In grey prediction, only several numerical values (at least four
numerical values) are needed to establish the power consumption
models for chillers. If PLR, the temperatures of supply chilled-water
and return chilled-water, and the temperatures of supply cooling-water
and return cooling-water are taken into consideration, quite accurate
results (with the accuracy close to 99% for short-term predictions)
may be obtained. Through such methods, we can predict whether the
power consumption at peak-load will exceed the contract power
capacity signed by the corresponding entity and Taiwan Power
Company. If the power consumption at peak-load exceeds the power
demand, the temperature of the supply chilled-water may be adjusted
so as to reduce the PLR and hence lower the power consumption.
Abstract: The top-heavy demographic of low birth-rate and longer lifespan is a growing social problem, and one of its expected effects will be a shortage of young workers and a growing reliance on a workforce of middle-aged and older people. However, the environment of today's industrial workplace is not particularly suited to middle-aged and older workers, one notable problem being temperature control. Higher temperatures can cause health problems such as heat stroke, and the number of cases increases sharply in people over 65. Moreover, in conditions above 33°C, older people can develop circulatory system disorders, and also have a higher chance of suffering a fatal heart attack. We therefore propose a new method for controlling temperature in the indoor workplace. In this study two different verification experiments were conducted, with the proposed temperature control method being tested in cargo containers and conventional houses. The method's effectiveness was apparent in measurements of temperature and electricity consumption
Abstract: Over half of the total electricity consumption is used in buildings. Air-conditioning and electric lighting are the two main resources of electricity consumption in high rise buildings. One way to reduce electricity consumption would be to limit heat gain into buildings, therefore reduce the demand for air-conditioning during hot summer months especially in hot regions. On the other hand natural daylight can be used to reduce the use of electricity for artificial lighting. In this paper effective factors on minimizing heat gain and achieving required day light were reviewed .As daylight always accompanied by solar heat gain. Also interactions between heat gain and daylight were discussed through previous studies and equations which are related to heat gain and day lighting especially in high rise buildings. As a result importance of building-s form and its component on energy consumption in buildings were clarified.
Abstract: In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.
Abstract: An integrated Artificial Neural Network- Particle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world-s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World-s population, Gross domestic product (GDP), oil trade movement and natural gas trade movement are used as socio-economic indicators in this study. For each socio-economic indicator, a feed-forward back propagation artificial neural network is trained and projected for future time domain. STEP 2: in the second step, global electricity consumption is projected based on the oil, natural gas, coal and primary energy consumption using PSO. global electricity consumption is forecasted up to year 2040.