1、 Dr Josh Wall is the leader of the Intelligent Building Controls research area at CSIRO | Energy, based in Newcastle, Australia. Mr Jeremy Stoddard is a CSIRO Industry Scholar and is currently undertaking a Bachelor of Engineering (Electrical) degree at the University of Newcastle, Australia. Utiliz
2、ing Passive Thermal Storage for Improving Residential Air Conditioning Demand Response Jeremy Stoddard Josh R. Wall, PhD Student Member ASHRAE Member ASHRAE ABSTRACT As air conditioning (AC) has evolved from luxury to modern day necessity, the rapid uptake of residential AC systems is creating major
3、 problems for centralized electricity network infrastructure, particularly on peak summer days. By using automated demand response (DR) signals, energy service providers aim to constrain the electrical demand that these systems place on the network. One such DR signalling scheme for residential cust
4、omers in Australia is the Australian Standard 4755.3 that defines how residential loads (i.e. air conditioners, swimming pool pumps, electric-boosted hot water heaters, grid connected electric vehicle chargers) respond to a set of initiating signals for reducing energy consumption. This paper highli
5、ghts potential benefits obtained when performing pre-cooling control strategies in summer prior to a demand response event. Real-world results from both laboratory and field tests show that the addition of a pre-cooling period prior to a DR event could enable a greater demand reduction for longer pe
6、riods and with improved end user comfort. Laboratory results were obtained from the CSIRO National HVAC Performance Test Facility (NHPTF). Using a reverse-cycle air-source heatpump, the duration and temperature setpoint during a pre-cool period were varied, along with the amount of thermal mass pres
7、ent in the indoor space. Using a typical summer outdoor temperature profile, space temperature variations and energy consumption of the AC system were monitored to compare each control strategy. A DR event was activated after the pre-cool in each test. Construction type and passive thermal mass was
8、found to play a crucial role in the provision of temperature benefits after a pre-cool period. In the test facility, added thermal mass limited the temperature rise during a demand response event, but also acted to increase the relative benefit of longer pre-cool durations. With representative therm
9、al mass added, a 4 hour pre-cool led to a maximum temperature difference of -0.73C (-1.3F) during a 3-hour DR event and an 81 Wh energy savings, relative to a non-pre-cool equivalent. The results of real-world field tests were similar, showing a 4 hour pre-cool strategy provided a -2.0C (-3.6F) maxi
10、mum temperature difference during a 3-hour DR event, as well as an energy saving of 602 Wh. All pre-cool control strategies tested had lower total energy consumption than the baseline AC system operation. The results suggest that pre-cooling residential thermal mass prior to a DR event would allow u
11、tilities to further reduce energy consumption in peak demand periods and significantly limit the peak indoor temperatures and discomfort experienced by end users. INTRODUCTION The rapid deployment of residential AC systems over the past decade can be predominantly attributed to the availability of l
12、ow cost AC imports combined with what has been relatively inexpensive electricity to power them. Suggestions have been made that it is the deteriorating thermal performance of newer housing stock in Australian metropolitan areas (de Dear and White, 2008). Another possible explanation worth debate is
13、 that as conditioned air is becoming ubiquitous (in our homes, cars and at our work), we are associating our thermal comfort and satisfaction with the need for AC, and thus are becoming addicted to very narrow and unnatural thermal conditions. At times of extreme heat (typically occurring over a few
14、 hours or days in each year) when a large proportion of people in Australia require more electricity to cool their homes and businesses, the centralized electricity network (the poles and wires) can become constrained. The impact of this peak demand is analogous to a busy highway at peak hour. Addin
15、g an extra lane (requiring significant investment) on the highway can alleviate congestion at peak times. However, outside of peak hour the additional lane is seldom used. Similarly, increasing the capacity of the network to cater for extreme peak demand can alleviate congestion issues. However, the
16、 costs of augmenting the network are significant. Australian National Electricity Market (NEM) load duration data highlights that around the top 20% of maximum demand occurs for less than 2% of time. This implies that network investments made to meet peak demand are significantly underutilised. By u
17、sing automated demand response (DR) signals, energy service providers aim to constrain the electrical demand that these systems place on the network, thus avoiding costly upgrades and helping to minimise electric price increases. With the AS4755.3.1 DR standard (Standards Australia, 2014) now being
18、widely implemented into residential systems available on the Australia market, a mechanism exists that enables large scale DR using standardised signals and interfaces. Although the current version of AS4755.3.1 is a significant first step to enabling large-scale residential DR in Australia, this pa
19、per provides supporting evidence of the potential benefits that a pre-cooling mode could bring if adopted. Key findings show that the addition of a new pre-cooling DR mode not currently defined in the standard could enable a greater demand reduction for longer periods and with improved end user comf
20、ort. DEMAND RESPONSE AND AS4755 A demand response is an automatic alteration of an electrical products normal mode of operation in response to an initiating signal (Standards Australia, 2007)0. The signal may be initiated remotely by an energy service provider or directly by the end user, however th
21、e latter is uncommon perhaps due to a lack of technical knowledge on the demand response enabling device (DRED) interface (Standards Australia, 2007), or more likely due to the end user having more accessible controls (via the supplied remote control) to initiate desired control actions that result
22、in energy and/or cost savings. First published in Dec 2009, AS4755.3.1 aims to reduce the amount of energy that AC systems use, which in turn reduces the demand placed on the network. For the benefit of the reader, a comprehensive list of AS4755 compliant AC system models is available on the Energex
23、 website (Energex, 2015). In addition to AS4755, another DR protocol gaining industry support is OpenADR 2.0 (Holmberg et al., 2012). As OpenADR allows two-way signalling, an advantage over AS4755 is that it can be used to gain immediate feedback from the controlled devices including instruction ack
24、nowledgement and the actual amount of energy/demand reduction. Although intended for commercial building applications, OpenADR could also be used for residential applications. Australian Standard AS/NZS 4755.3.1:2014 A demand response operational instruction as defined in AS4755.3.1 (Standards Austr
25、alia, 2014) can take the form of three modes: demand response mode (DRM) 1, 2, or 3. A demand response event is the period between the initiation and termination of an operational instruction. Each of these modes affects the AC systems power and energy usage differently as described in Table 1. Curr
26、ently, only DRM1CompressorOff is mandatory for compliance with this standard, however to date, most manufacturers of inverter based systems support both DRM250% and DRM375%. Typically, energy service providers have connected to their customers AC systems via custom made DREDs that are signalled by a
27、 remote agent using power line communications (also known as direct load control or ripple control) or wireless mobile telephony. Other options include using smart meter 2-way communications and integrated home area network (HAN) Zigbee wireless interface. The current generation of DRED devices supp
28、ort little more than the straight pass-through of DRM signals. They do not offer any advanced control features, such as pre-cooling or any type of end user intervention, even if there is a desire by the end user to activate DR modes that further increase the reduction in demand and save energy. DEMA
29、ND RESPONSE INDUSTRY TRIALS Motivated largely by the ability to reduce demand on the distribution network at their discretion, a number of energy service providers have conducted large scale residential DR trials in Australia to date, particularly using approaches that cycle the compressor of AC sys
30、tems off and on again over a defined period. A report released by Deloitte (Deloitte Australia, 2012) analysed a number of initiatives to lower peak demand including direct load control of AC systems. Of the related industry trials they looked at, peak demand reductions over the range 11.7% - 35% we
31、re reported. However, it has only been the last few years that we have seen AS4755 compliant systems becoming available (since around 2011) and being incorporated into such trials, hence little results have been made available in the public domain. Examples of utilities who have run Australian trial
32、s using AS4755 enabled AC systems include Energex, Ausgrid and Endeavor Energy. Scarce publically available results show demand reductions anywhere from 13% - 30% (Wall and Matthews, 2014). With nearly all of the commercial-scale DR trials to date, little consideration has been given to thermal comf
33、ort and satisfaction, other than general statements about the whole-of-trial experience along the lines of x% of participants had no complaints with thermal comfort; or the participants had a y% satisfaction rate. Furthermore, little work has been done on quantifying the initial and persistent influ
34、ence that programme incentives may have on thermal comfort and satisfaction, including cash, gift cards, energy discounts or other financial or non-financial incentives. LABORATORY AND FIELD TRIALS To better understand the potential benefits that pre-cooling can bring to energy management and demand
35、 response events, a number of laboratory tests were performed at the National HVAC Performance Test Facility (NHPTF) at the CSIRO Newcastle Energy Centre. In these tests, an AC system was used to pre-cool an indoor space for varying durations before activating a standard DRM scheme. Peak demand redu
36、ctions and indoor temperature profiles were used as a basis for comparing each pre-cool strategy. The thermal mass characteristics of the test room were also altered and quantified between experiment sets to identify the role of implicit thermal storage in providing pre-cool benefits. Following the
37、laboratory testing, residential trials were performed at a house in Newcastle, NSW, Australia, which utilised the same DRM and pre-cool strategies previously evaluated in the NHPTF. The results of the residential experiments were collated with laboratory findings to identify the nature and potential
38、 magnitude of pre-cool benefits in Australian houses. Experimental System Configuration The AC system used in NHPTF testing was a reverse cycle variable speed (inverter based) heat pump rated at 3.5kW cooling and 4.9kW heating capacity and efficiency ratios of 4.22 (EER) and 4.02 (COP) respectively.
39、 It is AS4755.3.1 compliant, supporting DRMs 1, 2 and 3. Table 1. Demand Response Modes as Defined in AS4755.3.1:2014 DRM Description of Operation in this Mode DRM1 Compressor off (indoor unit fan may still run) DRM2 The air conditioner continues to cool or heat during the demand response event, but
40、 the electrical energy consumed by the air conditioner in a half hour period is not more than 50% of the total electrical energy that would be consumed in a half hour period during normal operation under the same temperature and humidity conditions, and the same user settings. DRM3 The air condition
41、er continues to cool or heat during the demand response event, but the electrical energy consumed by the air conditioner in a half hour period is not more than 75% of the total electrical energy that would be consumed in a half hour period during normal operation under the same temperature and humid
42、ity conditions, and the same user settings. The test facility is a calorimeter chamber consisting of two separate and independently climate controlled rooms. The outdoor unit of the AC system was installed in room two (simulating the outdoor climate) and the indoor unit in room one (simulating the i
43、ndoor climate). A Modbus gateway device was used to monitor and control AC system parameters (e.g. AC mode, temperature set-point, fan speed) via Modbus commands issued from a controller. The controller also acted as the DRED to issue DRM operational instructions to the AC system. To make a direct c
44、omparison between the different pre-cool strategies, a common outdoor temperature profile was generated in room two of the facility. The temperature profile was based on historical data (8 January 2013) from the Newcastle Nobbys Signal Station (number 61055), and is representative of hot summer days
45、 which elevate peak demand requirements on the electricity network. In the indoor room, a dynamic heat load was implemented to emulate the conditions which would be present in a residential space. The load consisted of a real-time leakage component based on the temperature difference between the ind
46、oor and outdoor room, as well as a standard internal load profile obtained from NatHERS guidelines (Department of Industry and Science, xxxx). The internal load is based on a 4 person household, and accounts for occupancy, lighting and appliances on a typical weekday. Solar gain load was not conside
47、red in this instance, but could be included in future work to further improve the internal load profile. The total dynamic load was designed so as to match the rating of the AC system during the peak demand period. The AC control structure, visible in Figure 1, included a 21C (70F) pre-cool in the s
48、houlder period with varying start time, followed by a DRM control scheme with 23C (73.5F) setpoint in the peak tariff period. The order of the DRMs reflect typical summer demand patterns, where peak demand is generally highest in the 4-6pm period (based on real data obtained by CSIRO from approximat
49、ely 340 residential houses in south-east Queensland, Australia). A baseline test was also included, where no pre-cool occurred and the temperature setpoint remained at 23C for the entire day. Each test was initiated with the same indoor temperature, which had been established over several hours to ensure steady-state operation of the AC system and an adequate thermal equilibrium in the room. In the residential trials, the AC system used for testing was similar to the aforementioned test system, however with a 5kW cooling capacity. The same AC control struc
