Modelling the Spatial Transformation of the Urban Environment using Renewable Energy Technologies
This PhD research project attempts to unify two distinct domains of urban planning practice, including energy modelling and spatial transition modelling. As a result an integrated urban energy model framework is designed and implemented that considers both the energy and spatial effects of renewable energy policies that promote renewable energy technologies (RET's) in urban areas supporting planners and policy makers to make more effective, economical and sustainable policy choices on the future urban energy developments. For the realization of this framework, three modules are developed and applied to generate an optimized fully renewable-based urban environment under different policy scenarios, including:
- Demand module: As the first component of the proposed framework, the demand module determines the annual electricity usage and the usage profile of the built environment by considering the most important electricity usage explanatory variables.
- Supply module: This module examines the spatial and technical conditions of the urban areas to allocate RET's and then evaluates their energy potentials to generate an optimal configuration of these technologies with minimal exploitation cost while satisfying the spatial constraints and the specified loads.
- Storage module: In this module a heuristic optimization model is developed to examine the feasibility of storage technologies on the urban level that can absorb the variability of the RET's and generate an optimal storage solution for the study area.
These modules are integrated in the proposed framework that can support policy recommendation development concerning urban energy transition planning.
Front-cover of the dissertation (click here for downloading the digital file of the dissertation)
1- Urban Energy Model Framework
Over the last few decades, a variety of new global challenges have emerged from the fossil fuel-based energy systems such as global warming, security of energy supply, and increasing energy prices which impose dramatic changes on the current energy sources and infrastructure. To combat these challenges, particularly in urban areas, distributed renewable energy sources are being targeted. As a result, there has been a paradigm shift in the scale and nature of the energy generation in urban areas with the application of the distributed renewable energy technologies. Increasingly, these technologies form an important part of the urban energy system in many cities and represent a future framework of the energy systems both on the building and on the urban scale. The trend towards a distributed renewable-based energy system where energy is locally produced and consumed affects all energy system components,especially in cities which have high power densities and needs extensive planning to build a viable and reliable energy system.As of now, a wide variety of tools have been developed to model the urban energy transition and analyze the integration of renewable energy technologies (RET's) into the urban environment to support urban planners, urban designers and policy makers to evaluate future alternative scenarios. However, the literature study reveals two major shortcomings of these models including firstly the lack of an integrated model to optimize the configuration of the distributed renewable energy technologies to maximize the exploitation of local renewable resources and secondly the lack of an energy model to take into account the spatial aspects of the distributed renewable energy technologies. To fill these gaps, in this research an integrated urban energy model framework is proposed to generate an optimized configuration of the distributed renewable energy technologies that considers both spatial and energy effects of these technologies in urban areas. Accordingly, this research aims to develop a comprehensive urban energy model framework to study the energy and spatial effects of renewable energy policies that promote RET′s in urban areas to support planners and policy makers to devise appropriate policy schemes towards an electrical neutral urban area. The proposed framework describes the operation, configuration and components of the renewable-based urban energy system, the behavior of the components and the possible interactions between them. Three components, namely demand, supply and storage are embedded in the framework and their corresponding modules are developed. The proposed framework adopts a parcel-based data structure for the spatial analysis and representation of the urban environment.
Urban energy model framework and energy and data flow between the embedded modules
1-1 Demand Module
Since applying any sustainable intervention in the urban energy system requires fundamental knowledge of the energy demand dynamics, accordingly the first component of the proposed framework is the demand module. In this module the annual electricity usage and the usage load profile of the building connections in the urban built environment are determined. Through a literature review, the important electricity usage explanatory variables of the built environment are recognized. For each building connection, besides the annual electricity usage, three major categories of explanatory variables, including physical, socioeconomic and Geo-spatial characteristics are determined. Based on the available data sources and identified variables, the building electricity usage database is constructed and categorized based on the two most frequently used building sectors including residential and nonresidential. By creating the database, multiple linear regression method is applied to determine the relationship between the annual electricity usage and the explanatory variables. In order to determine the contribution of each category of variables in the variability of the annual electricity usage, the regression analysis is performed separately. The results revealed that in both building sectors most of the predictors are statistically significant and in total all variables can explain 28.1%, 39.4% and 42.9% of the electricity usage variability of residential, service and industrial building connections respectively.
Annual electricity usage histograms of the Eindhoven municipality (kWh/yr.)
Load profiling is the last step of the demand module in which the usage load profile of the building connections will be generated in hourly resolution for the entire year based on the physical characteristic of the connections and applied electricity tariff structure. The resulting annual electricity usage and the usage load profile of the building connections will be applied in the supply and storage modules respectively.
Examples of weekly electricity load variation in residential sector over a summer and winter weeks
1-2 Supply Module
The second component of the urban energy model framework is the supply module. The main objective of this module is examining the spatial and technical conditions of the parcels in urban areas to allocate RET′s in order to generate an optimal configuration of these technologies to minimize the total exploitation cost while satisfying the technical and spatial constraints and the required demand towards the electricity neutral area. In this module the focus is on the technologies that are spatially and technically feasible for the installation in the urban environments, including roof mounted photo voltaic panels and urban scale wind turbines that are installed adjacent to the built environment. For each technology the resource availability, power output determination procedure and spatial and technical requirements for installation in urban areas are determined. A RET-allocation algorithm as a core of the module evaluates the feasibility of allocating PV-panels and wind turbines to the parcels while considering parcel spatial specifications, technology technical requirements and renewable resource availability. The analysis is performed based on the spatial conditions that exist at the locations where RET's are installed and the technologies mutual interactions. Scenario analysis based on the technology configurations and resource availability is conducted which shows that the resulting cost of electricity generated by the applied RET's are significantly lower than the current retail electricity price which indicates that renewables can compete with the fossil fuel resources even with the current market conditions. The resulting supply profile of the urban parcels will be applied in the storage module for load balancing.
Annual electricity generation profile of the wind turbine and PV-panels
Generated optimal configuration plans of RET's - PV-panel scenario
Generated optimal configuration plans of RET's - Combined PV-panel and wind turbine scenario
1-3 Storage Module
The last component of the proposed framework is the storage module. The main objective of this module is developing a heuristic optimization model to analyze the deployment of energy storage systems on the urban level to balance the demand and supply profile of the parcels and generate an optimal energy storage solution for the study area. Distributed application of RET′s in the urban environment leads to the growth in the penetration of renewable energy resources which often have a random and intermittent generation. Moreover, the electricity demand has also showed a highly volatile behavior. These dynamics and inconsistencies on both urban energy system sides create a large amount of surplus and shortage of electricity, which only it can be mitigated by application of the storage technologies. As of now the storage applications have been mostly constrained to the building level and little attention has been paid to the application of these technologies on the urban scale. In this research a model is developed to investigate the feasibility of the application of storage systems on the urban scale. A simulated annealing algorithm is applied as an optimization algorithm to investigate how storage systems will be deployed at the urban scale and what implications they might have.
Changes in the acquired benefits from the building level to the urban level storage application
The results of the storage scenarios show that by connecting and sharing storage technologies on the urban scale, more benefit can be acquired compared to the building level applications. Analyzing the generated storage plans revealed that the spatial requirements for the application of storage technologies on the urban scale are influenced by two major factors. Firstly, the intended area should have enough space to install the storage systems such as green area in the permitted distance. Secondly, the high density of buildings is also a required condition for the installation of the urban scale storage systems. Moreover, the surplus profiles have an effect on the type of deployed storage system. In the high density built area with high surplus profiles if the spatial requirements are appropriate, most likely urban scale storage system will be applied. In total, the results show that the feasibility of storage's application at the urban level is significantly optimistic and by utilizing the shared storage systems collectively, higher benefits can be achieved.
Generated storage solutions of the study area for the wind turbine application scenario
2- Sensitivity Analysis
Experimentation's in the form of sensitivity analysis and policy demonstrations show the performance of the designed modules. Primarily a sensitivity analysis is conducted to explore the performance of the modules under small changes in the input parameters for three different configurations of RET′s. For each configuration, a series of sensitivity tests are performed, varying a range of input parameters and then examining the effects to analyze how the model works at a more detailed level. The results show that the most sensitive parameter is electricity-price which has the largest impact on the output of the modules. Also analyses showed that the PV-panel application has the better performance to store surplus electricity compared to the wind turbine application. One of the most striking results of the sensitivity analysis is that even with deploying unlimited energy/power capacity of the storage system, the global charge/discharge are lower than the total electricity surplus of the study area since some parcels in the study area due to the spatial and technical restrictions only can deploy the building level storage types with limited energy/power capacity.
Effects of the changing energy/power-capacity on the global-charge/discharge
3- Policy Demonstration
In more realistic scenarios the consequences of applying a number of policy programs as a practical demonstration of the modules for policy analysis are explored. Two policies are developed and implemented in the modules: introduction of the up-front renewable energy subsidy and applying electricity real-time pricing policy. Analyses show that PV-panel subsidies have a positive correlation with the PV-panel supply which indicates that an increase in the subsidies leads to the increase in the PV-panel electricity production. The results also show that an increase in the PV-panel subsidies will reduce the electricity generation cost of PV-panels. For the storage scenarios, there are also significant positive correlations between subsidies and acquired global-benefits. Also analyses show that applying the real time pricing policy leads to the increase in the global-benefit for all storage scenarios. These changes indicate that the real time pricing policy can significantly increase the feasibility of the application of storage systems in the renewable-based energy system.
Effects of the implemented PV-subsidies programs on the RET′s supply
4- Further Research
The proposed framework in this research is the first step towards developing a comprehensive urban energy model which seeks to investigate the spatial implications of the RET′s in an urban environment towards the electrical neutral environment. However, the results show that the proposed modules can be improved, particularly by considering aspects such as: applying large scale time-series data of the smart meters in the demand module, integrating 3D spatial models with the supply module to include urban vertical surfaces in analyzing the spatial implication of the RET′s and incorporating the load flexibility of the smart grid technologies such as heat pumps and electric vehicles with the storage module to utilize their potential shift able loads to reduce the peak loads.