Optimal design and control are coupled tasks for enhancement of energy system performances. Model based dynamic optimization can enhance system performances significantly. However, it is difficult to obtain the optimal structure and control solution for a complicated nonlinear physical system model simultaneously, thus we proposed a coupled dynamic optimization method for structure and control co-optimization and implement it successfully for a transcritical CO2 ejector expansion heat
pump coupled with hot and cold thermal energy storages during energy charging process. A complicated nonlinear dynamic system model with genetic algorithm were used to obtain the structure and control co-optimization solution of the coupled system during energy charging. The structures of gas cooler, evaporator, hot and cold thermal storage tanks were optimized, and dynamic optimal control strategy was obtained for energy charging process. Compared to the constant control parameter strategy, the overall coefficient of performance can be increased by 21.1%. The performances can be enhanced more significantly if the water temperature at the hot tank outlet remains at a low level, i.e. the charging time reduced. This study would be helpful for a structure and control co-optimization of other dynamic energy systems.
Electric sector emissions represent a large and growing fraction of anthropogenic emissions and should be a strong focus for environmental policy measures. In electric grids with significant penetrations of renewables, the emissions intensity of electricity varies in space and time. To encourage and guide decarbonization efforts, we need better tools to monitor the emissions embodied in electricity consumption, production and exchanges. Previous efforts resulted in a dataset for 2016 electricity and emissions at the hourly and balancing – area levels in the US electricity system. We now provide tools to make such datasets available much faster, by using a n approximation for released emissions and an algorithm to automate data cleaning. A s an example of how this type of new, detailed information on the electricity system can be used, we assess the current impacts of high penetrations of renewables on other grid components in the US. We demonstrate how dispatchable generation and electricity exchanges play an essential role in integrating fluctuating wind and solar generation.
Introduced in this document is a combination of research published by our university cluster. It outlines the requirements for an ultra-fast response system to correct generation/load imbalances on timescales that could be considered virtual inertia. Much of the research is based on real power system measurements and lab experiments, supplemented by computational models. The work has been tailored to the Irish power system that is facing a low inertia threshold, limiting the utilization of renewable generation. Ireland is taken as a test case for the necessary road other power system will need to take as they integrate converter interfaced renewable generation. At present Ireland has the objective to decarbonize its power system by 2050; as anyone who has read the IPCC 2018 summary will appreciate, this is far too late and if preparatory research is not undertaken, projects may be rushed.
This work aims to study and analyze the potential and impact on CO2 avoided emissions from now to 2030, of scaling up an innovative hybrid solar technology to satisfy the energy demand of the Food and Beverage (F&B) industrial sector in Mexico. Positive and negative economic growth (including the recession caused by the COVID-19 pandemic) is considered as well as three technological scenarios: large, medium, and short technology deployment (BTD, MTD, and LTD). The study is based on a top-down and a button-up approach to determine F&B sector final energy consumption growth and share of primary and secondary energy sources. The results show that the proposed LCPV/T technology has an excellent decarbonization potential in the studied sector, achieving GHG emissions reduction of up to 51.7% and 34.10% from the levels of 2018 for the negative and positive economic growth, respectively.
CO2 Plume Geothermal (CPG) is a carbon neutral renewable electricity generation technology where geologic CO2 is circulated to the surface to directly generate power and then is reinjected into the deep subsurface. In contrast to traditional water geothermal power generation with an Organic Rankine Cycle (ORC), CPG has fewer system inefficiencies and benefits from the lower viscosity of subsurface CO2 which allows power generation at shallower depths, lower temperatures, and lower reservoir transmissivities.
In this paper, we modify our existing geothermal electricity models by: 1) replacing TOUGH2 reservoir simulations with analytic solutions for a 5-spot reservoir impedance, and 2) including heat loss to the surrounding rock using a semi-analytical heat transfer solution. We report the results of 3050 simulations in a single plot, showing the power generation of both direct CPG systems and indirect water geothermal systems for depths between 1 and 7 km and reservoir transmissivities between 102 and 105 mD-m (10-13 and 10-10 m3).
The outcome of possible changes in interlinked industrial energy systems is hard to predict, especially in retrofit scenarios. This results in investment decisions under uncertainties. In this paper, a new combined optimization approach is presented, that aims to support decision-making in these cases. The approach links models for optimal design of supply systems and heat exchanger networks with operational constraints and is specifically designed for retrofit applications. It is formulated as one combined mixed integer linear programming (MILP) problem. The results of the presented approach are demonstrated using a case study representing a typical industrial process. The optimal solution shows a cost-effective way for a transition to more efficient use of energy and an increased share of renewable sources.
This paper presents a comprehensive study of various sources of methane emissions, assess the impact of each source on emissions, and their dependency to throughput, time, and events. The analysis builds upon prior work  positing that a cause-based, marginal approach to estimating methane emission impacts of change in natural gas use was more accurate than assuming that methane emissions vary one-for-one with throughput. The results show that there are many components in the natural gas system that emit the same amount of methane to the atmosphere regardless of their operational mode; meaning some emissions sources have no or only partial dependence on throughput. As a result, reducing natural gas consumption in the future will not yield a directly proportional reduction in the methane emissions. The results of this study will be used in future works to build a model using the marginal emission methodology to estimate the change in methane emissions of natural gas systems as system throughput changes. It is believed that the results of this study will help energy policymakers to understand better the effect of policies aimed at reducing natural gas use on greenhouse gas (GHG) emissions and where such policies should be applied.
Realization methods for energy optimal urban driving are the prime focus of this paper. Insights into the real-time generation of such trajectories as well as “in traffic” methods for their execution are provided. This includes the usage of piecewise linear approximations of typical urban speed profiles, urban platooning, filtering of trajectories, and modifying initial accelerations on the trajectory implementation side. On the computation side, precomputed trajectories, and closed-form approximated solutions are investigated.
This paper solves the problem of dynamic pricing strategy in an urban integrated energy-traffic system. A three-stage incentive scheme has been introduced to enhance operational profits and mitigate the impact of system uncertainties. Pricing strategies in the three stages, namely day-ahead equilibrium references, hour-level prices, and surge prices, are used to incentivize human users. The proposed framework could yield a set of charging and service prices for IETS, which could improve in overall revenue and security.
Fossil fuels are the primary energy source because of their (1) low cost, (2) ease of storage, (3) low-cost transport and (4) economic dispatchability. Because the capital cost of power plants, furnaces, and boilers is small relative to the cost of the fuel, it is economic to meet variable energy demand by operating fossil plants at part load. Nuclear, wind, solar and hydrogen production plants have high capital cost; thus, operating these facilities at half capacity can almost double energy costs. A low-carbon system is defined that enables high-capital-cost low-operating-cost technologies to operate at high capacity while providing variable heat, hydrogen and electricity to the customer. This minimizes total costs. In the U.S., over 80% of all energy used is in the form of heat; thus, heat production and storage is central to a low-carbon economy. Nuclear power is the primary low-carbon low-cost heat producing technology.