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This study proposes a site location potential model for urban energy supply plants and renewable energy availability using an environment and energy geographical information system (E-GIS) database (DB) and an artificial neural network (ANN). This model addresses the technical methodology of examining the potential for the suitability of urban energy supply plants and renewable energy latency in a region for support material for urban energy supply planning in the draft plan development stage. The applicability of this model is examined by applying it for a planned city in the Republic of Korea, where urban planning is in process. The results from this study are as follows: (1) The E-GIS DB was integrated with geography, climate, and energy-related information to construct an ANN model that can manage, in an integrated manner, the factors that affect the site location of the energy supply plants. (2) The input dataset included the topography, land cover classification, accessibility, water usability, and energy demand, and the target dataset included the system capacity of domestically installed energy supply plants. (3) The site location potential model of the ANN for the urban energy supply plants and renewable energy availability was deduced, and the Levenberg–Marquardt (trainlm) and scaled conjugate gradient (trainscg) algorithms were used. The potentiality class map was constructed for 10 types of energy supply systems and renewable energy resources. (4) The applicability of this energy model was tested in the Gwang-myung/Si-heung public housing district area, a domestic ‘planned city’ of the Republic of Korea. The most appropriate urban energy supply systems for the research area were considered to be the general hydraulic power and solar power based on the topographic conditions and profitable locations for solar resources in Korea. Wind power generation was found to be the least suitable. (5) In terms of the wind energy potential, the technical wind power generation by horizontal – axis wind turbines is unattainable even in the area that has the maximum wind speed, and at least a 10-kW rated power wind turbine should be installed for vertical – axis wind turbines in the research area of interest. In terms of the solar energy potential, the maximum electric power generation potential is 413, 186 MJ/month·mesh, which is applied by mono-crystalline bulk PV.

This study proposes a new urban energy demand forecasting system that includes the following improvements: (a) a facility planning information database (DB), (b) an energy and planning statistics DB, and (c) an enhancement of the accuracy of the energy calculation method. Each of these improved aspects is involved in energy demand forecasting for urban planning. The results from this study are as follows. (1). An Environment and energy Geographical Information System Database (E-GIS DB), which provides the mesh unit facility information, was utilized to allow for the forecasting and control of urban energy demands for each unit space. (2). An energy consumption unit figure was connected with an energy simulation to diversify the level of the urban energy consumption sector and the primary energy into hourly information. This figure allows for more accurate demand forecasting. (3). Urban facilities were categorized according to energy use characteristics and were modeled to allow for energy demand forecasts. (4). The energy demand was considered in an urban climate during summer with the characteristics of the heating methods that are suitable for domestic circumstances. Thus, a separate algorithm was suggested for a cooling period and a heating/intermission period to enhance the accuracy of the demand forecasts. (5). The performance of this energy demand forecasting system was validated, such that excessively high or low calculated values can be modified from the current method in a ‘planned city’ while the urban energy demand can be forecasted relatively correct and in detail with differences of a factor of 0.20–0.44 for the cooling period in the ‘existing city’. (6). The proposed urban energy demand forecasting system was constructed as EnerISS Solver which is an automated module. This module drastically reduced time consuming for predicting energy demand and urban climate to respond for the urban energy planning subjects’ needs immediately.

This study proposes a method to create an urban planning support model, applying the Environment and energy Geographical Information System Database (E-GIS DB) through the urban life cycle to reduce energy use for environmentally friendly urban planning. The results deduced from this study are organized as follows. The proposed E-GIS construction model is composed of (a) an urban GIS integration model, (b) an E-GIS DB model, and (c) a visualization model. The urban GIS integration model has the ability to integrate urban GIS constructs as well as to connect and visualize urban planning and the environment and energy DB in 3D space. The E-GIS DB model includes a function to visualize the 2D and 3D information, which is used in the environment and energy planning of a city. To validate the proposed E-GIS construction model, a Korean city undergoing the urban planning process is selected as a case study. An E-GIS DB section with an 8 km × 12 km area for the research subject area was constructed in 2D and 3D GIS, and the urban space, climate elements, and energy distribution characteristics are compared.

This paper will focus on the energy performance evaluation of a cooling plant system in a semiconductor factory. Several energy saving technologies namely: integrated cooling towers, free cooling systems, control of the chilled water quantity, etc., have been adopted to improve efficiency of the cooling plant system. We have collected actual operating data for 2 years and evaluated the performance of chillers’ COP and the whole cooling plant system's COP and they showed satisfactory results even if the thermal load of the factory was about half compared with design phase assumption. We also have verified each effect of the energy saving technologies through model-based simulation analysis. The annual electric power consumption dropped about 35% compared to conventional cooling plant systems in case of design phase thermal load. And the faulty status operation of the chiller's number control miss occurred while we monitored. Electric power consumption increased about 17% compared to normal status operation at the same period.

There are many reports about faulty status in building air-conditioning systems recently. It becomes difficult to keep indoor air temperature appropriately as faults occur, and the faults cause waste of building energy consumption. The model-based fault detection and diagnosis (FDD) methods have been researched for specific parts of air-conditioning system such as chillers, coils, variable air volume units (VAV units), etc. It needs, however, much time and labor to monitor and check every single part because we cannot predict where and when the faults occur. The purpose of this study is to examine indoor air temperature changes and energy consumption increase when faults occur and to develop an easy-to-use FDD tool that helps to find out the faulty place through the whole building air-conditioning system. And then, we treat the reliability of the proposed FDD tool and effectiveness to control of indoor environment deterioration and energy consumption increase by the tool is evaluated based on building air-conditioning system simulation in this paper.

This paper treats energy and cost performance of a cooling source system with indirect seawater utilization for air conditioning in a commercial complex. Seawater utilization has merits as a cooling source, because seawater temperature is lower than outdoor air in summer and it is cost effective because there is no water monetary cost. Actual operating data has been measured for about 2 years and the chiller and system co-efficient of performance (COP) have indicated about 4.77 and 2.93, respectively, even in summer season and the mean efficiency of the thermal storage system was about 89.9% taking into account heat loss of pumps. In addition, we have constructed simulation models for cooling tower systems, air cooling chiller systems and direct seawater utilization systems then compared them to this system. The electric power consumption of the indirect seawater utilization system was almost the same as the other systems except the air cooling chiller system, because using lower seawater temperature made the chiller efficiency higher. In conclusion, our results showed the indirect seawater utilization system was able to improve the system COP compared to air cooling chiller system, and cancel water consumption compared with the cooling tower system, and cut down an initial and maintenance costs compared with the direct seawater utilization system.

The purpose of this paper is to clarify energy performance of the cooling plant system in the industrial building using actual measured operating data and numerical simulation analysis. One aspect of industrial buildings is that they have large energy consumption for manufacturing and air-conditioning compared with office and commercial buildings. Some examples of high-efficiency technologies installed in this particular cooling plant system are inverter chillers, integrated cooling towers and a free-cooling system. The inverter chiller which has been put on the market recently is state-of-the-art technology. The maximum COP of the inverter chiller reaches about 18 under certain conditions and integrated cooling towers make lower temperature cooling water as the whole capacity is large. Actual operating data indicates satisfied values for chiller and system COP during the running period and the simulation results show that the cooling plant system can cut down annual electric power consumption by about 48% compared with conventional cooling system.