Demand Response Operation of Electricity-Intensive Chemical Processes for Reduced Greenhouse Gas Emissions: Application to an Air Separation Unit

Oxygen production in cryogenic air separation units is related to a significant carbon footprint and its supply in the medicinal sphere became critical during the recent COVID-19 crisis. An improved unit design was proposed, utilizing a part of waste heat produced during air pre-cooling and intercooling via absorption coolers, to reduce power consumption. Variable ambient air humidity impact on compressed air dryers’ regeneration was also considered. A steady-state process simulation of a model 500 t h−1 inlet cryogenic air separation unit was performed in Aspen Plus® V11. Comparison of a model without and with absorption coolers yielded an achievable reduction in power consumption for air compression and air dryer regeneration by 6 to 9% (23 to 33 GWh year−1) and a favorable simple payback period of 4 to 10 years, both depending on air pressure loss in additional heat exchangers to be installed. The resulting specific oxygen production decrease amounted to EUR 2–4.2 t−1. Emissions of major gaseous pollutants from power production were both calculated by an in-house developed thermal power plant model and adopted from literature. A power consumption cut was translated into the following annual greenhouse gas emission reduction: CO2 16 to 30 kilotons, CO 0.3 to 2.3 tons, SOx 4.7 to 187 tons and NOx 11 to 56 tons, depending on applied fossil fuel-based emission factors. Considering a more renewable energy sources-containing energy mix, annual greenhouse gas emissions decreased by 50 to over 80%, varying for individual pollutants.

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Demand response scheduling under uncertainty: Chance‐constrained framework and application to an air separation unit

AIChE Journal ◽

10.1002/aic.16273 ◽

2020 ◽

Vol 66 (9) ◽

Cited By ~ 2

Author(s):

Morgan T. Kelley ◽

Ross Baldick ◽

Michael Baldea

Keyword(s):

Demand Response ◽

Air Separation ◽

Separation Unit ◽

Air Separation Unit ◽

Scheduling Under Uncertainty

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The Potential Role of Flexibility During Peak Hours on Greenhouse Gas Emissions: A Life Cycle Assessment of Five Targeted National Electricity Grid Mixes

Energies ◽

10.3390/en12234443 ◽

2019 ◽

Vol 12 (23) ◽

pp. 4443 ◽

Cited By ~ 2

Author(s):

Ingrid Munné-Collado ◽

Fabio Maria Aprà ◽

Pol Olivella-Rosell ◽

Roberto Villafáfila-Robles

Keyword(s):

Life Cycle Assessment ◽

Life Cycle ◽

Environmental Impact ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Demand Response ◽

Gas Emissions ◽

Electricity Grid ◽

Attributional Life Cycle Assessment ◽

Yearly Average

On the path towards the decarbonization of the electricity supply, flexibility and demand response have become key factors to enhance the integration of distributed energy resources, shifting the consumption from peak hours to off-peak hours, optimizing the grid usage and maximizing the share of renewables. Despite the technical viability of flexible services, the reduction of greenhouse gas emissions has not been proven. Traditionally, emissions are calculated on a yearly average timescale, not providing any information about peak hours’ environmental impact. Furthermore, peak-hours’ environmental impacts are not always greater than on the base load, depending on the resources used for those time periods. This paper formulates a general methodology to assess the potential environmental impact of peak-hourly generation profiles, through attributional life cycle assessment. This methodology was applied to five different countries under the INVADE H2020 Project. Evaluation results demonstrate that countries like Spain and Bulgaria could benefit from implementing demand response activities considering environmental aspects, enhancing potential greenhouse gas reductions by up to 21% in peak hours.

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Demand Response Economic Assessment with the Integration of Renewable Energy for Developing Electricity Markets

Sustainability ◽

10.3390/su12072653 ◽

2020 ◽

Vol 12 (7) ◽

pp. 2653 ◽

Cited By ~ 3

Author(s):

Abdul Conteh ◽

Mohammed Elsayed Lotfy ◽

Oludamilare Bode Adewuyi ◽

Paras Mandal ◽

Hiroshi Takahashi ◽

...

Keyword(s):

Renewable Energy ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Demand Response ◽

Peak Load ◽

Load Factor ◽

Gas Emissions ◽

Load Profile ◽

Profile Modification ◽

Load Demand

Electricity disparity in sub-Saharan Africa is a multi-dimensional challenge that has significant implications on the current socio-economic predicament of the region. Strategic implementation of demand response (DR) programs and renewable energy (RE) integration can provide efficient solutions with several benefits such as peak load reduction, grid congestion mitigation, load profile modification, and greenhouse gas emissions reduction. In this research, an incentive and price-based DR programs model using the price elasticity concepts is proposed. Economic analysis of the customer benefit, utility revenue, load factor, and load profile modification are optimally carried out using Freetown (Sierra Leone) peak load demand. The strategic selection index is employed to prioritize relevant DR programs that are techno-economically beneficial for the independent power producers (IPPs) and participating customers. Moreover, optimally designed hybridized grid-connected RE was incorporated using the Genetic Algorithm (GA) to meet the deficit after DR implementation. GA is used to get the optimal solution in terms of the required PV area and the number of BESS to match the net load demand after implementing the DR schemes. The results show credible enhancement in the load profile in terms of peak period reduction as measured using the effective load factor. Moreover, customer benefit and utility revenues are significantly improved using the proposed approach. Furthermore, the inclusion of the hybrid RE supply proves to be an efficient approach to meet the load demand during low peak and valley periods and can also mitigate greenhouse gas emissions.

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