Sustainable Infrastructure Planning Systems - completed
Sustainability as a word has been co-opted by so many interests that it is beginning to lose all meaning. However, the basic concept remains the same: ensuring that meeting today’s needs does not compromise future generation’s abilities to meet their own. There are many frameworks that aim to measure sustainability, one of which is the Inclusive Wealth concept that is beginning to gain momentum worldwide.
The aim of the SIPS project was to utilize the Inclusive Wealth framework to evaluate and guide large public infrastructure investments; the hypothesis being that this evaluation methodology would lead to more sustainable decisions.
Within this project I worked on the power system case study, evaluating the effects of various generation investment scenarios on the measured national stocks of Natural, Built, and Human capital that compose the Inclusive Wealth index.
Urban Energy Systems - ongoing
Energy use in Saudi Arabia is terribly inefficient with per-capita consumption at more than three times the world average. It is estimated that 70% of the buildings in the Kingdom have no thermal insulation with HVAC, lighting, and transportation energy efficiency all performing below international standards.
This wasteful domestic energy consumption costs Saudi Arabia nearly 10% of its annual expenditure in subsidies and its unchecked escalation may threaten the country’s status as an oil exporter in the future. In this vein the Kingdom has embarked on numerous programs to increase energy conservation and efficiency. The aim of this project is to develop models and tools to aid Saudi stakeholders in this endeavor.
The project will create a high resolution urban energy model of
Riyadh city. The model and simulation will aim to identify the
causes of energy loads in buildings. By focusing at the city scale where most energy consumption occurs, the project will investigate direct strategies for the causal reduction of Saudi Arabia’s domestic demand. The developed urban energy model of Riyadh will provide a testbed for a plethora of scenarios and domestic energy solutions to be trialed.
Power System Evolution - ongoing
The Kingdom of Saudi Arabia’s electricity sector is set to see significant change. Power demand is set to double over the next twenty years due to a swelling population and increasing standards of living. At the same time the country is attempting to diversify it’s generation mix to incorporate an ambitious amount of solar and nuclear power. An industry restructuring program announced 10 years ago is still underway with a competitive electricity forever on the horizon.
What are the future pathways for the Kingdom’s power system and how will these be affected by the technological, economic, and regulator decisions being made today?
This project aims to explore and map out this terrain, producing an interactive decision support system that will help guide policy makers within this complex space to evaluate trade-offs, negotiate, and devise the best electricity policies for the nation.
Integrated Energy Decision Support System - completed
Countries that are looking to decarbonize and transition their energy future face numerous and complex decisions. For instance they could decide to switch their fuel sources, or invest from a range of various technologies, or even choose to focus upon demand-side methods. This whole decision making process is subject to wide uncertainty and the complex interactions between numerous stakeholders.
IEDSS is designed to help decision makers explore numerous scenarios of potential energy policies, through rapid prototyping of possible “what if” scenarios. The methodology is applied in the context of Saudi Arabia which faces a significant challenge in meeting its future energy demands.
IEDSS employs the concept of “serious gaming” by running simulations of real-world scenarios used for strategizing and problem solving. The analytical and predictive capabilities of the tool are generated by representing the supply and demand dynamics of the power sector that are embedded at the heart of the software.
Within this project I worked on applying the developed national-level system dynamics logic to an agent-based simulation that would allow for the decision making process to be decentralized from national control to a more competitive regional market.
Strategic Solar Desalination Network - completed
As a desert country with a booming population Saudi Arabia has turned to desalination to sate its thirst. This is problematic as the current desalination procedure is effectively converting the Kingdoms oil wealth to potable water, an expensive and unsustainable paradigm.
Luckily what the country lacks in regenerative natural water sources it compensates for with an abundance of solar energy. The aim of this is SSDN project is then to set the stage for sustainably and effectively harnessing the power of the sun for desalination.
Within this project I worked on utilizing a graph theoretic framework, termed INFINIT, to model the national power system. The resulting model determines the optimal network configuration of solar plants with relation to the desalination system.
City Dynamics - Completed
Many cities in Saudi Arabia, and indeed the world, are experiencing rapid growth due to various factors such as natural population growth, urbanization, and immigration. These driving forces impact cities infrastructures in a myriad of ways straining the cities’ infrastructure to the point of becoming a major hindrance to socioeconomic and daily activity. Left unaddressed, this strain on infrastructure threatens to weigh down the return on investment from the massive public development projects throughout the Kingdom, and adversely affect the quality of life of all residents.
Such rapid urban growth creates both challenges and opportunities for the public sector. The challenges stem from the need to ensure that various city services are expanded at a pace to meet the growing demands of this burgeoning population, and that both growth and development proceed in an orderly and sustainable manner. As many initiatives are still being planned and/or implemented, these challenges also create opportunities to apply new modes of thinking toward the future planning of the city, and the potential application of new tools and techniques for citizens and policymakers.
This project addressed the intricacies of demand and supply on cities’ infrastructures under the influence of multiple driving factors by employing a mixture of modeling and analysis methods such as complex networks modeling and machine learning techniques. Pervasive technologies, such as mobile phones, were utilized as a proxy to infer human mobility and the characteristics of the demand on infrastructures
Within this project I assisted work on developing a data-driven model of solar-powered urban microgrid solutions. Traditional power system procedures were combined with statistical network analysis to investigate the trade-offs in the investment of microgrids as an alternative to traditional power distribution networks.