Development of a Simulation Framework for Analyzing Security of Supply in Integrated Gas and Electric Power Systems

Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the impacts of the interactions in both systems is crucial for governments, system operators, regulators and operational planners, particularly, to ensure security of supply for the overall energy system. Although simulation has been widely used in the assessment of gas systems as well as power systems, there is a significant gap in simulation models that are able to address the coupling of both systems. In this paper, a simulation framework that models and simulates the gas and power network in an integrated manner is proposed. The framework consists of a transient model for the gas system and a steady state model for the power system based on AC-Optimal Power Flow. The gas and power system model are coupled through an interface which uses the coupling equations to establish the data exchange and coordination between the individual models. The bidirectional interlink between both systems considered in this studies are the fuel gas offtake of gas fired power plants for power generation and the power supply to liquefied natural gas (LNG) terminals and electric drivers installed in gas compressor stations and underground gas storage facilities. The simulation framework is implemented into an innovative simulation tool named SAInt (Scenario Analysis Interface for Energy Systems) and the capabilities of the tool are demonstrated by performing a contingency analysis for a real world example. Results indicate how a disruption triggered in one system propagates to the other system and affects the operation of critical facilities. In addition, the studies show the importance of using transient gas models for security of supply studies instead of successions of steady state models, where the time evolution of the line pack is not captured correctly

Combined analysis of coupled energy networks

Energy supply systems such as the electricity, natural gas, district heating and cooling networks are typically designed and operated independently of each other. The increasing use of technologies such as combined heat and power units, gas turbines, heat pumps and recently, power to gas systems are increasing the links between energy systems introducing technical and economic interactions. There is a significant interest from academics, industry and policy makers in different parts of the world to identify and realise the opportunities of integrating energy networks while avoiding any undesirable impacts. Analysis of the interdependencies between different energy systems requires powerful software models and analysis tools. However, there are no commercial tools available to date. The aim of this research is to develop a model for the combined steady state simulation and operation planning of integrated energy supply systems. As part of this thesis, three key components of the model were developed i.e., a) Optimal power dispatch of an integrated energy system: A real case study was used to demonstrate the economic benefits of considering the interactions between different energy systems in their design and operation planning. b) Simultaneous steady state analysis of coupled energy networks: An example of a coupled electricity, gas, district heating and district cooling network system was used to illustrate the formulation of equations and the iterative solution method. A case study was carried out to demonstrate the application of the method for integrated energy network analysis. c) Steady state analysis of gas networks with the distributed injection of alternative gases: A case study was carried out to demonstrate the impact of alternative gas injections on the pressure delivery and gas quality in the network

Developing Models Using Game Theory for Analyzing the Interaction of Various Stakeholders in Energy Systems

Air pollution, global warming, climate change, and economic development are all reasons for governments around the world to incentivize the development of renewable energy generation technologies and plan for a transition toward a low-carbon economy. The development of renewable energy projects as well as the liberation in electricity systems has led to the emergence of multiple stakeholders in energy systems. While the research focused on investigating the objective of a single stakeholder in an energy system is abundant in the literature, considering the objectives of all stakeholders in a multi-stakeholder model is a gap in the research. This thesis is aimed at developing a multilevel framework for modeling and analyzing the interaction of various stakeholders in energy systems. The models developed in this thesis are focused on investigating two areas: 1. The role of energy storage systems in Ontario and how they can be used to reduce GHG emissions in the province, and 2. Analyzing the interaction of the heat and electricity supply systems in Great Britain. The contribution of this thesis is presented through four studies. The objective of the first study is to investigate the effect and cost-efficiency of different renewable energy incentives and potential for wind and hydrogen energy systems to the perceived viability of a microgrid project from the prospective of different stakeholders, i.e., government, energy hub operator and energy consumer in the province of Ontario, Canada. Hourly simulation of a microgrid in which wind and/or hydrogen are produced is used for the analysis. Results show that using underground seasonal storage leads to the government paying less incentive per kg of CO2 emission reduction as it lowers the levelized cost of hydrogen and provides a higher carbon emission reduction potential. Results of the first study also show that for the same incentive policy, incentivizing hydrogen production with grid electricity or a blend of wind power and grid electricity and producing hydrogen using wind power with underground hydrogen storage are more cost-efficient options for government than incentivizing wind power production. Regarding the renewable energy incentives, a combination of capital grant and FIT is shown to be a more cost-efficient incentive program for the government than FIT only programs. However, FIT programs are more effective for promoting the development of renewable energy technologies. In the second study, the advantages of energy incentives for all the stakeholders in an energy system were analyzed in the context of a microgrid using a more comprehensive approach. In the second study, the effect of health impacts from fossil fuel consumption and taxes collected from the energy hub operator and energy consumer are considered in the model. The stakeholders considered in the second study include the government, the energy hub operator, and the energy consumer. Two streams of energy incentives were compared in the second study: incentives for renewable energy generation technologies and incentives for energy storage technologies. The first stream aims to increase the share of renewable energies in the electricity system while the second stream aims the development of systems which use clean electricity to replace fossil fuels in other sectors of an energy system such as the transportation, residential and industrial sectors. The results of the analysis in the second study show that replacing fossil fuel-based electricity generation with wind and solar power is a less expensive way for the energy consumer to reduce GHG emissions (60 and 92 CAD per tonne of CO2e for wind and solar, respectively) compared to investing on energy storage technologies (225 and 317 CAD per tonne of CO2e for Power-to-Gas and battery-powered forklifts, respectively). However, considering the current Ontario's electricity mix, incentives for the Power-to-Gas and battery-powered technologies are less expensive ways to reduce emissions compared to replacing the grid with wind and solar power technologies (1479 and 2418 CAD per tonne of CO2e for wind and solar, respectively). The analysis in the second study also shows that battery storage and hydrogen storage are complementary technologies for reducing GHG emissions in Ontario. This third study aims at developing a game theory model for assessing the potential of fuel cell-powered and battery-powered forklifts for reducing GHG emissions in the province of Ontario, Canada. Two stakeholders are considered in the developed model: government and energy consumer, which is an industrial facility operating forklifts. The energy consumer, which is assumed to be an industrial facility, operates 150 diesel forklifts but has the option of replacing them with fuel cell-powered and battery-powered forklifts. The government can encourage this replacement by allocating a percentage of Ontario's surplus power to the energy consumer at a discounted price. The discount is assumed to be in the form of exempting the energy consumer from paying the global adjustment. As a result, the energy consumer only pays the hourly Ontario electricity price when discounted power is available. Discounted electricity will decrease the cost of operating battery-powered and fuel cell-powered forklifts for the energy consumer and will encourage the use of those technologies instead of diesel forklifts. The government has an incentive to pursue such policy as the replacement of diesel forklifts with fuel cell-powered and battery-powered forklifts will reduce GHG emissions and subsequently, the social cost of carbon in the province. The results of the third study show that when the government does not allocate discounted power to the energy consumer, energy consumer does not reduce emissions and keeps using the 150 diesel forklifts. However, when the government provides 0.1% of Ontario's surplus power at each hour to the energy consumer at a discounted price, the energy consumer replaces 31 of diesel forklifts with battery-powered forklifts. When the percentage of discounted power is 0.6% of Ontario's surplus power at each hour, energy consumer replaces 91 of diesel forklifts with battery-powered forklifts and 54 of diesel forklifts with fuel cell-powered forklifts. A policy of discounting surplus power to encourage replacing diesel forklifts with battery-powered and fuel cell-powered forklifts is shown to benefit both stakeholders in the system. The third study also shows that the deployment of both fuel-cell powered and battery-powered forklifts is effective in reducing GHG emissions in Ontario when surplus clean power is available. Battery-powered forklifts are more cost-effective when lower levels of discounted power are available; however, with an increase in the level of available discounted power, fuel cell-powered forklifts become more cost-effective technologies compared to battery-powered forklifts. The same methodology is also used for analyzing the potential of clean surplus power in Ontario to reduce GHG emissions in the residential sector. In the fourth study, an iterative optimization model is developed to analyze the interaction of heat and electricity sectors at a national level in Great Britain. Independent mathematical models for optimizing the selection of technologies in heat and electricity supply systems are developed in the fourth study. The optimal mix of technologies for supplying electricity and heat were then calculated iteratively to take into account the interactions between the electricity and heat systems and their fragmented planning strategies. The capacity and operation of various technologies for electricity generation were optimized to supply electricity demand with a minimum annual cost. Then, the heat supply options were determined through minimization of the annualized cost of the heat supply system. Iterative optimization of electricity and heat was continued until an equilibrium was achieved. The results of the iterative approach were compared with a centralized optimization model in which heat and electricity problems are solved simultaneously

Multi-scale modelling of integrated energy supply systems

Local energy systems are changing with the use of more distributed generation as well as the decarbonisation of heat and transport, but the impacts of these local changes on national scale energy supply systems are not well understood. The existing whole energy system models lack the spatial granularity to represent local energy systems and their interactions with gas and electricity transmission networks. This key limitation was addressed by the new CGEN+Energy Hubs model. The CGEN+Energy Hubs Model enables multi-time period operational analysis of integrated national and local energy supply systems. The CGEN+Energy Hubs model was developed by extending a well�established Combined Gas and Electricity Network model (CGEN) by adding the representation of local energy systems. Energy Hubs were used to represent local energy systems in different geographic areas of GB. The CGEN+Energy Hubs model also extended CGEN by including functions for bi-directional electricity interconnector flows, intermittent renewable generation, demand response, distributed injection of hydrogen and biogas, and vehicle to grid electricity supply. The application of the CGEN+Energy Hubs model was demonstrated using contrasting Energy Supply Strategies. The Energy Supply Strategies were defined to explore options to decarbonise heat supply in GB: i.e. 1) low-carbon electricity in the Electric Strategy 2) biomass and solid-waste fuelled CHP in the Heat Network Strategy, 3) hydrogen and biogas in the Green Gas Strategy, and 4) Unconstrained, which employs cost optimisation to choose the heating technology. The Energy Supply Strategies were first applied to the Oxford-Cambridge Arc region to investigate how each strategy would cost-effectively reduce CO2 emissions from the Arc’s energy system. The Electric Strategy was shown to be able to meet the CO2 emissions target in 2050 at the lowest annualised costs per dwelling (investment and operation). The study showed that additional investment is needed to increase the capacity of transmission electricity supply, distributed generation, and the electricity distribution network. The Energy Supply Strategies were then applied to all Energy Hubs in GB simultaneously. The Electric Strategy was again shown to be able to deliver the net-zero CO2 emissions target in GB at the lowest annual operating costs. It was shown that CCGT generator capacity is required to mitigate the impact on the electricity transmission network due to the variability of renewable generation. Battery storage systems are proposed to replace CCGT plants and further reduce the use of natural gas