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.
The global fossil fuel source is limited and is getting depleted rapidly. The growth in energy demand worldwide is ever increasing, thus increasing fossil fuel consumption. Use of fossil fuels in electrical energy generation have environmental impacts like global warming , CO2 emissions etc., This necessitated use of alternate renewable energies like solar, wind to meet energy requirements. But the limitation of renewable energy sources are that they are intermittent in supply, uncertainty of availability etc., lead to difficulties in ensuring stability in electrical grid networks. These constraints led to the development of various energy storage technologies so that available surplus energy from renewable sources can be stored and released as and when needed to maintain grid supply stability both in terms of power and frequency. Thus Electrical Energy Storage (EES) is of great importance to ensure striking a balance between demand and supply .Many storage technologies have been developed and used at present like pumped hydro, solar thermal, batteries, compressed air, flywheel etc., Compressed air storage technology has the advantage of reduced emission and possibility of large capacity plants. About 440 MW installations of CAES are available at present around the world. Compared with other energy storage technologies, CAES is proven to be a clean and sustainable type of energy storage with the unique features of high capacity and long-duration of the storage.
The intention of this paper is to model and analyse a small scale compressed air storage system useful for standalone and micro-grid applications. The economics of CAES is also discussed. Thermodynamic analysis of the charging and discharging cycles in the storage tank is modelled and analysed for a small capacity CAES. A thermodynamic study on the proposed system covering all components like compressor, expander is also done and related models analysed. The heat energy released during compression
stage is recovered, utilized during expansion so that the round trip efficiency improves. This paper also covers this aspect, comparing the efficiencies of systems with and without heat recovery.
With the proliferation of distributed energy resources and the volume of data stored due to advancement in metering infrastructure, energy management in power system operation needs distributed computing. In this paper, we propose a fully distributed Alternating Direction Method of Multipliers (ADMM) algorithm to solve the distributed economic dispatch (ED) problem, where the optimization problem is fully decomposed between participating agents. In our proposed framework, each agent estimates the dual variable and the average of the total power mismatch of the network using dynamic average consensus, which replaces the dual updater in the traditional ADMM with a distributed alternative. Unlike other distributed ADMM, the proposed method does not rely on any specific assumption and captures the real-time demand change. The algorithm is validated successfully via case studies for IEEE 30-bus and 300-bus test systems with the penetration of solar photovoltaic.
Electric power systems in many parts of the world are undergoing a transformation from relying almost exclusively on dispatchable power (e.g., fossil, nuclear, and large hydropower) toward incorporating more variable nondispatchable generation (e.g., wind and solar PV). We show for the first time that solar generation can decrease some aspects of variability in the peak residual load in power systems. The electric load minus generation from nondispatchable resources is known as the “residual load.” The maximum or peak residual load provides an estimate of the quantity of dispatchable generation capacity required to supply electric load during all hours. We study the peak residual load as a function of increasing wind and solar generation for three power systems in the U.S.: the PJM system in the Mid-Atlantic, the ERCOT system in Texas, and the NYISO system in New York. We analyze more than a decade of historical data for each region. The introduction of variable renewable power is often thought to increase the variability of most characteristics of power systems. Contrary to this idea, we show the inter-annual variability in peak residual load decreases for all three systems as a function of increasing solar generation. We attribute this effect to correlations between solar generation and peak electric load values. Peak electric load values for all three systems occur during summer heat waves, when air conditioning is used. We find that as solar generation increases, the quantity of dispatchable generation capacity needed to supply the residual load becomes more similar year-to-year. Therefore, in some systems, expansion of variable solar generation can increase predictability of the peak residual load. Thus, an increase in solar generation could ease achievement of certain system reliability targets.
Renewable energy is attracting much attention due to limited traditional energy sources and severe environmental issues caused by the over-consumption of fossil fuels. It is promising to use renewable energy for the power supply to buildings, as the building sector accounts for a large portion of global energy consumption with a continuous increasing trend. This study aims to analyze the technical and economic feasibilities of applying hybrid photovoltaic-wind-battery systems for high-rise buildings in Hong Kong based on the TRNSYS platform. Detailed economic benefits of the hybrid renewable energy system are estimated considering the feed-in tariff, transmission line loss saving, network expand and infrastructure saving, and social benefit of carbon reduction. It is found that the hybrid photovoltaic-wind-battery system can cover 24.79% of the annual electrical load of a high-rise building. The average self-consumption and self-sufficiency ratio of the hybrid system is 100% and 46% respectively. Battery storage in the hybrid system can not only improve the self-consumption and self-sufficiency performance, but also benefit the utility grid relief. The levelized cost of energy of the hybrid photovoltaic-wind-battery system is about 0.431 US$/kWh. This study can provide references for the development of hybrid renewable energy systems in Hong Kong and guide the application of renewable energy and battery systems to high-rise buildings in urban regions.
For the unconventional reservoirs, advances in drilling and fracturing technologies prompt operators to tend to the designs of large-scale, staged fracturing with multi-cluster in one stage. However, with the well spacing getting closer, it must be noted that the risk of inter-well interference increases since the hydraulic fractures can interfere, even hydraulically communicate. In the past few years, inter-well interference became more prominent and thus received significant attention in the development of unconventional reservoirs. The interferences in fracturing to adjacent wells have negative effects as: (1) abnormal changes in wellhead pressure, daily gas production and daily water production of adjacent wells; (2) water flood out, mud backflow or sand production, etc. In some extreme cases, production wells may never fully recover or stop production permanently.
The operational planning for Integrated Energy System (IES) with different energy carriers provides a new perspective of synergies towards a low-carbon society. Existing carbon trading scheme promotes this process via finical incentives. However, as customers are the underlying driver of emission. Planning with accurate carbon tracing and demand response would improve the effectiveness of decarbonization. Meanwhile, customers would be encouraged to participate with extra environmental profits rather than passive price takers, under the double taxation principle. Therefore, a forward cycle can be established to reduce carbon emission. This paper proposes an operation planning model for IES to study the influence of demand response to emission mitigation and system dispatch in both energy market and carbon trading market. The proposed model is tested on an IES system involving a modified IEEE 24-bus electricity network and a modified 20-bus natural gas network. Based on the simulation result, the proposed model is effective to achieve emission mitigation.
This paper evaluates data from 10 centrifugal pumps in a large wastewater treatment facility to illustrate the impact of pump design, selection, maintenance, and operation on system efficiency. The paper explores the efficiency impact of several interventions and qualitatively presents trade-offs to implementation. Of the interventions explored, energy savings up to 3% were identified representing 239,000 kWh annually.
For the past five years, the Department of Energy’s Co-Optima program has explored biomass-derived blendstocks with fuel properties that boost the efficiency of engines, seeking to enable technology for fuel-engine co-optimization. Past analysis quantified benefits of introducing co-optimized fuels and engines for light-duty vehicles with the core assumption that efficiency gains would be the same for vehicles with and without hybridized power trains. Vehicles with hybridized powertrains, however, could experience a different energy efficiency change than conventional vehicles, which could be a decrease, if the blended fuel is not tailored for their operation, or an increase, if the hybrid engine’s operational conditions take better advantage of the blended fuel. Therefore, this study examines opportunities to reduce the environmental effects of light-duty transportation when fuel properties are tailored to the unique needs of hybrid electric and plug-in hybrid electric (HEV, PHEV) vehicles to improve their engine efficiency. The analysis tracks greenhouse gas emissions reductions on a well-to-wheels basis when co-designed fuels and engines for vehicles with hybridized power trains are introduced into the market. Engine efficiency gains and incremental vehicle cost are key parameters in the analysis as we seek fuel-engine technology that will significantly boost overall vehicle efficiency at a price point that is commercially viable. Twelve co-deployment scenarios were generated based on 3 different levels of engine efficiency improvement (8% ,10% and 12%) and 4 level incremental costs ($100, $250, $500 and $1000) and the corresponding environmental effects are tracked as the technologies gain market adoption. The preliminary results show that the effect of incremental cost and efficiency gain on vehicle sales indicates that adoption of co-optimized HEV, and PHEVs are relatively insensitive to incremental vehicle purchase costs up to $250. In addition, the results indicate higher adoption of co-optimized HEVs at $100 and $250 price increase and 12% efficiency gain while the adoption of HEVs and PHEVs across other scenarios remain consistent. From the best-case scenario ($100, vehicle price increase and 12% engine efficiency increase), the result shows that using biofuels with tailored properties and advanced engines to achieve an increase hybridized engine efficiency could translate to 17.5% reduction in greenhouse gas emissions from the light duty vehicle fleet including non-hybridized vehicles in 2050.