• Energy Research
• 12. Responsible consumption close

Abstract As part of the inputs for of the Colombian Strategy for Low-Carbon Development (ECBDC), the Studies Group for Urban and Regional Sustainability (SUR) of Universidad de los Andes, working with a group of national experts in the transport sector, developed a model to estimate greenhouse gas (GHG) emissions generated by that sector in 2010. National emissions were projected for the period 2010-2040, using Kaya factors, and there were assessments of a range of options to mitigate emissions through a cost-effectiveness analysis. A marginal abatement cost curve (MACC) was generated, identifying potential mitigation of 290 million tons accumulated up to 2040. An estimate was made of the uncertainty associated with the input parameters for the model mentioned. The statistical properties were estimated based on technical and scientific literature and the IPCC recommendations. The intention was to identify the stochastic condition of the initially deterministic model. For this purpose, random values were generated based on Monte Carlo simulations, and a sensitivity analysis was conducted to find the variables with the greatest influence on the final results.

Abstract As part of the inputs for of the Colombian Strategy for Low-Carbon Development (ECBDC), the Studies Group for Urban and Regional Sustainability (SUR) of Universidad de los Andes, working with a group of national experts in the transport sector, developed a model to estimate greenhouse gas (GHG) emissions generated by that sector in 2010. National emissions were projected for the period 2010-2040, using Kaya factors, and there were assessments of a range of options to mitigate emissions through a cost-effectiveness analysis. A marginal abatement cost curve (MACC) was generated, identifying potential mitigation of 290 million tons accumulated up to 2040. An estimate was made of the uncertainty associated with the input parameters for the model mentioned. The statistical properties were estimated based on technical and scientific literature and the IPCC recommendations. The intention was to identify the stochastic condition of the initially deterministic model. For this purpose, random values were generated based on Monte Carlo simulations, and a sensitivity analysis was conducted to find the variables with the greatest influence on the final results.

Variable renewable energy (VRE) and energy storage systems (ESS) are essential pillars of any strategy to decarbonize power systems. However, there are still questions about the effects of their interaction in systems where coal’s electricity generation share is large. Some studies have shown that in the absence of significant VRE capacity ESS can increase CO2 emissions. This paper shows that contrary to this intuition, ESS reduces operational costs and emissions even without higher penetration of VRE in power systems with large shares of coal. It also shows that when combined with VRE, ESS delivers higher benefits. These findings are based on the examination of China Southern Power Grid under seven VRE and ESS penetration scenarios. Results show that at the 2018 penetration levels, ESS alone reduced operational costs by 2.8% and CO2 emissions by 1% and that by being paired with VRE, these reductions increased to 8.1% and 6.5%, respectively. The results clarify the synergy between ESS and VRE and explain the underlying mechanism. While VRE lowers coal units’ economic efficiency and environmental performance (measured in RMB/MWh and kg CO2/MWh), ESS offsets this effect by increasing large coal units’ power generation and improving their efficiency. ESS reduces coal consumption and CO2 emissions by substituting power generation from low-efficiency coal units with electricity from high-efficiency units and allowing them to operate at levels closer to full capacity and avoid start-ups.

Variable renewable energy (VRE) and energy storage systems (ESS) are essential pillars of any strategy to decarbonize power systems. However, there are still questions about the effects of their interaction in systems where coal’s electricity generation share is large. Some studies have shown that in the absence of significant VRE capacity ESS can increase CO2 emissions. This paper shows that contrary to this intuition, ESS reduces operational costs and emissions even without higher penetration of VRE in power systems with large shares of coal. It also shows that when combined with VRE, ESS delivers higher benefits. These findings are based on the examination of China Southern Power Grid under seven VRE and ESS penetration scenarios. Results show that at the 2018 penetration levels, ESS alone reduced operational costs by 2.8% and CO2 emissions by 1% and that by being paired with VRE, these reductions increased to 8.1% and 6.5%, respectively. The results clarify the synergy between ESS and VRE and explain the underlying mechanism. While VRE lowers coal units’ economic efficiency and environmental performance (measured in RMB/MWh and kg CO2/MWh), ESS offsets this effect by increasing large coal units’ power generation and improving their efficiency. ESS reduces coal consumption and CO2 emissions by substituting power generation from low-efficiency coal units with electricity from high-efficiency units and allowing them to operate at levels closer to full capacity and avoid start-ups.