In this thesis, we demonstrate the potential of economic circuit theory for the modeling, design, analysis, and control of a spot market for hydrogen. Spot prices are expected to be significantly more volatile than the current marginal-cost-plus pricing schemes and new methods are required to model the dynamics of price as it reacts to fluctuations in supply and demand.

To model such dynamic pricing, we use recently developed economic circuit theory, a subfield of economic engineering where markets are modeled as electrical circuits. We model market agents, including production operators, storage facilities, market makers, and industry clusters, as analogous electrical components. We structure their interactions in an economic network that reflects the flow of hydrogen through the backbone and the balancing of price-driving incentives among the market agents.

We design three economic networks: a core network and two extensions. The core network incorporates a renewable wind-hydrogen supply chain, a low-carbon hydrogen supply chain, and imports of gaseous and liquid hydrogen. One extension divides the hydrogen spot market into renewable and low-carbon segments, and the other integrates an ammonia market. We implement and simulate the networks in MATLAB Simulink.

We analyze the networks' dynamics using dynamic scenario analyses, a technique within economic circuit theory. This permits us to quantify the dynamic resilience of the market under supply disruptions and demand extensions; in particular, we use overshoot and settling time as metrics for the volatility and recovery of stocks, prices, and hydrogen supply. In addition, we establish how wind variability generates a ripple effect that impacts the dynamics across the coupled commodity markets.

In conclusion, we model and analyze a market design that includes intervention by a regulatory agency. Specifically, we design a PID controller to implement a subsidized price-settlement system. We demonstrate that such a controller effectively mitigates excessive spot price levels, reduces price volatility, and secures the supply of hydrogen.

In this thesis, we demonstrate the efficiency of Laplace domain techniques for the design and analysis of economic systems. To make the techniques applicable to economic modeling, we establish the economic analogs to the various tools and nomenclature in the engineering literature. We show that the Laplace domain provides an alternative description of economic systems, offering insights into behavior not apparent in the time domain. This allows economic discounting and cycles to be efficiently analyzed using pole-zero maps, Bode plots, and similar techniques. In addition, we demonstrate that transforming the linear differential equations of economic engineering into algebraic equations in the Laplace domain simplifies the design of economic systems.

We use the Laplace domain techniques to design and analyze a macroeconomic model. By designing the model in the Laplace domain, we are able to integrate supply chain dynamics and the housing market using two-port network theory.
By analyzing the model using a pole-zero map, we show that the economy's discount rates and business cycles are represented by complex poles and the economy's transmission blocking rates by complex zeros. Additionally, we demonstrate that the Bullwhip effect, a supply chain phenomenon, can be intuitively visualized using a Bode plot. These applications illustrate how Laplace-domain techniques enable the efficient design and analysis of economic systems.

In this thesis, the analogy between the special theory of relativity and the dynamics of a laborer is developed in the context of labor economics. At the basis of this analogy stands an individual laborer who cannot supply more than 24$hours of labor in a day. This represents the theoretical limit to the flow of labor services (velocity). We argue this limit is analogous to the speed of light. The development of the analogy continues using hyperbolic functions independent of the demand frame of reference (frame of reference) and dependent on the degree of demand (rapidity) as well as the wage inelasticity (mass). This analogy describes the behavior of an individual laborer, detailing the quantity of labor services (position) and their flow, the wage (momentum) and the causation of changes in the flow of labor services (forces). These dynamics in labor economics are consistent with the theory of special relativity, demonstrating economic engineering principles.

Economic engineering is applied to model an individual laborer using the newly developed analogy. The laborer's supply curve shows that wage inelasticity does not change when a laborer performs more labor. Instead, the nonlinear supply curve is attributed to the difference in a laborer's perception of time (proper time). The perception of time depends on the flow of labor services of the observer, making it possible to observe the labor market from different perspectives, including those of companies and laborers. The laborer's perspective on their supply is visualized on the Poincaré disk, from which occupational compositions and job transitions can be analyzed.

Although competition is a dynamic phenomenon, currently used competition models do not take price dynamics into account, and some models are not even quantitative. This poses a problem for regulators or hedge funds and M&A departments who rely on these models to either quantify price and demand movements, or to determine the cost of competition.

This thesis solves that problem by using Economic Engineering to build on the existing game-theoretic models of competition to include price dynamics. A bond-graph model of a competitive market is developed, from which the price dynamics are derived. Model-predictive controllers are used to model profit-maximizing companies within this model, and to simulate competitive behavior and its effects on prices and demand flows.

Finally, this thesis shows how control engineering tools in both the time and the frequency domain can then be exploited by regulators and hedge funds. Time-domain simulations enable regulators to quantify the effects of competition on prices and demands, and analyses in the frequency domain enable hedge funds to determine the change in company valuations due to changes in competition, i.e., the cost of competition.

The purpose of Supply Chain Management (SCM) is to maximize and stabilize the flow of goods through a supply chain. Disruptions to this flow, such as the Bullwhip Effect (BWE), have become increasingly severe and dynamic, challenging current methods for counteracting these disruptions. This thesis develops a systems and control framework for designing SCM policies to meet this challenge.

The thesis makes use of economic-engineering modeling principles to model the dynamics of the supply chain and calculate the flow of goods. Specifically, the supply chain is considered to be analogous to an electrical circuit, with the flow of goods analogous to the current and price changes analogous to voltage drops. Based on these analogies, the thesis develops the building blocks required for modeling a supply chain, consisting of storage, production and external markets. The building blocks are used to construct a serial supply chain with multiple stages and products. The supply chain is analyzed in both the time and frequency domain, quantifying how disruptions influence the flow of goods.

To regulate the flow of goods through a supply chain, this thesis models the procurement, production and product pricing policies of SCM as individual PID controllers. The PID controllers are shown to regulate the flow of goods in a manner similar to how an actual manager would.

The effectiveness of the framework is demonstrated in a simulation study of the BWE in the supply chain of Valtris Specialty Chemicals (VSC). It is shown how tools in classical control theory, like Bode diagrams, are effective in the analysis of the dynamics and severity of the BWE in terms of the resonance frequency and the amplification, respectively. In addition, this thesis shows how the tuning of the PID controllers relates to specific adjustments in the policies of VSC managers.

In this thesis, an economic-engineering model of the ripple effect in the housing market is put forward. The ripple effect in the housing market is modeled by integrating into one model the local price dynamics of the rental market, the spatial price dynamics between local rental markets, and the valuation of real estate. Such a model is lacking in current housing-market literature.

The economic-engineering model design has two main aspects. First, economic-engineering model design uses analogs between mechanical systems and the housing market, ensuring that the model contains only economically and mechanically interpretable parameters. In this way input optimization and parameter optimization have a direct implementation in the real world. Second, economic-engineering model design relies on classical-mechanical modeling techniques that make the model suitable for optimally and robustly determining governmental policy using control formalism.

This thesis takes the perspective of the housing market as a heterogeneous economic space, where the dimensions are geographic proximity and economic influence. The model put forward in this thesis spatially discretizes this heterogeneous economic space into homogeneous local markets, such that local price dynamics govern the local markets and inter-local differences add spatial price dynamics.

The model put forward in this thesis is designed to predict where shortages will arise due to the introduction of rent control. Such a model guides policymakers in where to build for effectively relieving shortages in the housing market. Finally, such a model informs investors about the value change to expect due to policy changes and migration trends.