A Novel of Energy Consumption Profile of a Shopping Center

Energy conservation in Indonesia is the primary choice made by the government of the Republic of Indonesia. It is undeniable that the highest consumption of a building is air conditioning energy, especially in a tropical environment like Indonesia. Air conditioning consumes between 40% and 80% of power in a high-rise building. The problem is how to find out the electricity usage profile and energy consumption index in a building that has been in operation for more than 20 years. This research aims to find the energy profile and calculate the energy consumption of a shopping center building. The method used is an Energy Audit according to SNI 6196. The energy consumption profile is an anomaly where the energy consumption for the air conditioning system is only 48%, while the average value in shopping centers in Indonesia is 62.9%. Meanwhile, the GFA energy consumption index is 23.11 kWh/m2/month or 277.3 kWh/m2/year. According to SNI 03-0196, the result is classified as an energy-intensive building. This value is close to the SNI 03-0196 standard for very energy-intensive building levels, which has values between 23.75 and 37.5 kWh/m2/month. Energy-saving opportunities are calculated by calculating the difference in the ECI value with the target ECI value. To increase the efficiency of energy consumption, this can be done by replacing the chiller unit which still uses a step type compressor. Apart from that, improving air conditioning insulation is very significant to overcome energy consumption problems. Adding green plants around buildings can also increase electrical efficiency

Defining and developing an energy retrofitting approach

This paper identifies the dilemma faced by the stakeholders of existing buildings in regards to a decision making process for energy retrofitting. This paper also identifies the missing stage viewed as the “integrity audit “which can lead to substantial savings in the area of building operation. The methodology is centered on identifying energy waste first, reducing the overall peak electrical demand and then retrofitting for energy-efficiency. A proposed “integrity audit” leads to the classification of three main energy culprits: the identification of waste, missed opportunities, and rescheduling the operation of equipment use. A case study indicating the financial advantages of applying this methodology for a commercial building are presented. The energy retrofitting strategy is divided into two main categories, namely building control improvements and building component implementation. The payback periods are often within months if not immediate

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science

Enhancing the Potential of Smart Building for General Hospital: A Case Study in Malaysian Hospital.

Hospital Pulau Pinang is the general hospital in Malaysia which targeting energy savings of 10% within five years from 2015 and other sustainability targets such as 3-star Energy Management Gold Standard and Green Building Certification. The targets are beneficial for the hospital itself to establish the Smart Building Program to improve its energy efficiency concurrent with the green policy of the Ministry of Health Malaysia and Sustainable Development Goals by the United Nations. This paper reviews the background of Hospital Pulau Pinang energy data , energy consumption trending, energy-saving trending, and energy conservation measures taken for the hospital from 2015 to December 2021.The yearly energy consumption baseline taken in 2016 was 27,496,731.00 kWh. It reduced significantly to 21,356,063 kWh in 2021 due to energy conservation measures. As a result, Hospital Pulau Pinang has achieved energy-saving about 16% at approximately RM7.3 million reduction in operational expenditure. The main objective of this paper is to provide further potential energy savings by studying the energy reduction by implementing solar photovoltaics using the simulation method. The simulation method can predict that Hospital Pulau Pinang can achieve another 5,130,000 kWh energy savings annually. This type of simulation has never been done before at a public hospital, and it will give further enhancing strategies to the Smart Building Program itself. Furthermore, the potential of smart building can be maximized to the next level by simulation, which helps the hospital energy committee make the potential decision on the energy-saving investment

Management model for energy efficiency - Intelligent System module

The power consumption in buildings represents a 30-40% of the final energy usage, hence it is necessary to minimize the power consumption by optimizing the operation of several loads without impacting in the customer’s comfort. According to the above in this work an intelligent approach framing in a management model is presented for the power consumption management of devices taking into account some variables as indoor temperature, outdoor temperature, illuminance and presence. Furthermore, in this research the integration of several Demand Side Management (DSM) criteria with one criterion based on neural networks and other inspired on differential tariff is carried out through dynamic and intelligent selections according to variables performance and customer´s preferences, e.g. priority list of criteria, operation based on comfort or consumption, in addition to other preferences as temperature. Likewise, a previous diagnosis analysis through energy audit is carried out to evaluate devices performance and customer habits. Experimental testing to the proposed approach has been performed in an environment object of study with the consumption data base and its performance tested in simulations runs. The testing results show that energy savings can be achieved through of recommendations provided by energy audit and proposed states by dynamic manager.MaestríaMagister en Ingeniería Electrónic

ENERGY – CLIMATE CHANGE PACKAGE IMPACT ON ROMANIAN URBAN AREAS

Europe recognized the tight link between energy and climate change and took - through a coherent legislative package - the role of a global leadership to tackle climate change, to face up to the challenge of secure, sustainable and competitive energy, and to make the European economy a model for world sustainable development in the 21st century. EU targets to improve the relation between energy and environment are very ambitious and can not be reached without a clear understanding of the requirements of European policies and the effort that each and every Member State has to do. In these conditions, the present paper aims to make a short qualitative analysis on the possible impact that the legal package energy-climate change could have on housing and urbanism in Romanian towns in order to raise some question marks and alert the decision makers.sustainable energy, housing, urbanism, public authorities.

A three-dimensional model of residential energy consumer archetypes for local energy policy design in the UK

This paper reviews major studies in three traditional lines of research in residential energy consumption in the UK, i.e. economic/infrastructure, behaviour, and load profiling. Based on the review the paper proposes a three-dimensional model for archetyping residential energy consumers in the UK by considering property energy efficiency levels, the greenness of household behaviour of using energy, and the duration of property daytime occupancy. With the proposed model, eight archetypes of residential energy consumers in the UK have been identified. They are: pioneer greens, follower greens, concerned greens, home stayers, unconscientious wasters, regular wasters, daytime wasters, and disengaged wasters. Using a case study, these archetypes of residential energy consumers demonstrate the robustness of the 3-D model in aiding local energy policy/intervention design in the UK

Energy audit experiences in foundries

Steel industry presents one of the highest energy demand of all the industrial sector. Foundries have a really relevant role both in economical terms and as regards the energy demand. The cost of energy represents several percentage points of the overall costs of a foundry. The electricity demand is very high, particularly for the induction melting furnaces. A large amount of thermal energy is obtained both from natural gas combustion and from the coal needed for the process of formation of cast iron in cupolas. Moreover, the plant services must be considered: one very energy consumer is compressed air production. Every factory is different from another so that the proposal of actions of energy savings or thermal recovers requires a detailed study of each plant considering the lay out and analysing the single processes with related energy needs and thermal levels. The co-operation of the University of Padua with the Centro Produttivita` Veneto allowed to plan a series of energy audits in some foundries located in Vicenza province. The experiences of the first facilities surveys and audits recommendations demonstrated both potential advantage of energy savings and the related difficulties, often due to the high investment costs. Anyhow the joint work of auditing between the university experts and the foundry technicians produced a better awareness on the critical points of the plant and a higher rationality level in the evaluation of investments for the renewable of the machinery. Here, the method of performing the energy audits is described together with the very first results in terms of roposals for energy savings evaluated technically and economically