The building sector is one of the largest consumers of energy and producers of greenhouse gas emissions in Ontario, representing 13% of the province’s emissions. Recently, countries have been looking to decrease their emissions in response to climate change. The electrification of space heating and domestic hot water preparation has gained traction in reducing emissions in countries with low emission electricity grids. This thesis proposes a novel energy delivery system called the Integrated Community Energy and Harvesting (ICE-Harvest) system. The ICE-Harvest system is a modified 5th Generation District Heating and Cooling (5GDHC) system. An ICE-Harvest system, much like a 5GDHC system, is a district energy system that incorporates heat pumps to couple the thermal and electrical energy demands of buildings. The ICE-Harvest system uses heat pumps to supply both heating and cooling from a one pipe thermal distribution network. The ICE-Harvest system has unidirectional mass flow in a ring arrangement with branches at each building. Bidirectional energy flow between the network and buildings is permitted, meaning that heat rejection from cooling processes can be recovered in the network to reduce the total system heating load. This concept is referred to as energy sharing. The energy needs of the network, and thus the buildings, are serviced through a centralized generation station referred to as the Energy Management Center (EMC). The EMC regulates the supply temperature of the network to the controlled setpoint. Within the EMC, the primary generation source is a Combined Heat and Power (CHP) unit. The purpose of this CHP is to offset the existing centralized natural gas generators on the Ontario electrical grid. These gas generators operate intermittently and inefficiently as a form of dispatchable generation to stabilize the provincial electrical grid. In this research, it is proposed that ICE-Harvest systems with on-site CHPs could replace these gas generators while providing the same support to the electrical grid at a much higher energy utilization ratio. For an accurate comparison, the CHP is constrained to only turn on according to the electricity system operator's gas generator dispatching schedule. An auxiliary boiler is included in the EMC to provide heat when the CHP is not permitted to operate. However, the possibility for Thermal Energy Storage (TES) to replace this boiler is also explored. An ICE-Harvest system's ideal design depends on the market conditions, building energy demands, and available waste energy sources. This research presents an ICE-Harvest system in a heating demand dominated community located in Ontario, Canada. The community consists of five buildings. The ICE-Harvest system is compared to conventional and alternative building energy systems using the energy consumption data of these buildings. The systems are compared according to their energy consumption, emissions produced, and impact on the electrical grid at both the distribution and transmission levels. The topic of using thermal energy storage in ICE-Harvest systems is also discussed, and a parameter sweep is performed on the thermal energy storage capacity. The results show that the ICE-Harvest system offers demand management opportunities to electricity system operators, substantially reduces annual emissions, and offers improved energy utilization compared to conventional systems. / Thesis / Master of Applied Science (MASc)

This thesis examines community energy planning in Sweden and Canada with the aim of revealing strategies that move communities towards energy sustainability. Unsustainable energy activities are identified as major threats on both local and global levels. The challenges for energy systems are discussed and a possible scenario of a future community with sustainable energy production and consumption is presented. The literature review examines community energy planning guidebooks and key theoretical and methodological concepts including ingenuity, soft energy paths and backcasting from socio-ecological principles of sustainability. Following an analysis of energy supply and demand in a broad systems context, and a review of policies and programs supporting or hindering community energy planning, energy plans from eleven Swedish and eleven Canadian communities are evaluated. Characteristics of progressive energy planning as uncovered in the literature review form a framework for evaluating the visions, strategies and actions described in the plans. Sweden is recognized as an early player in community energy planning. Although Swedish energy plans do not contain all of the identified progressive strategies, national leadership and funding have played a role in Sweden’s successes. More recent Canadian plans are found to be highly progressive, suggesting that Canadian communities who follow their plans can too be successful in transforming their energy systems towards sustainability. / <p>Kerly Acosta, email: kerly_a@yahoo.com Arash Sangari, email: arash@stechpartner.com Jessica Webster, email: jess_violet@hotmail.com</p>

Building energy models are used to forecast building energy use to design and control efficient building energy systems. Building energy use can generally be decomposed into heating, ventilation and air conditioning, refrigeration, appliance and lighting loads. These loads will depend on multiple factors such as outdoor weather conditions, occupants, building type, controls and scheduling. Data-driven models have become more popular with the increase in smart meter data available that can be used to train and fit the models. Additionally, buildings with high refrigeration loads have greater heat harvesting potential, however, few data-driven models have been developed for buildings such as supermarkets and ice rinks. In this work, linear regression models are used to predict the disaggregated space cooling, heating, baseload and refrigeration components of building energy use. In most cases, measured aggregate electricity use is available, however individual appliances or component loads require submetering equipment which can be expensive. Therefore the proposed models use time-based and weather features to separate the thermal and baseload portions of the electrical load. A generalized approach is also used to predict new buildings with data from existing buildings. Furthermore, a simplified model is used to predict hourly space heating from monthly natural gas measurements and hourly weather measurements. The models were evaluated on real data from buildings in Ontario and the disaggregated loads were verified with synthetic data. The results found that aggregate use was predicted reasonably well using linear regression methods, with most building types having a median normalized root mean squared error between 0.2 and 0.3, depending on the forecasting period. The model is flexible as it does not require detailed information related to the building such as lighting or setpoint schedules, however, it can be adapted in the future to include additional information and improve predictive capability. / Thesis / Master of Applied Science (MASc)