Uncertainty is a common and critical problem for planning the capacity and operation of integrated energy systems (IESs). This study evaluates the effects of uncertainties on the capacity and operation of an IES. To this aim, system planning and operation with uncertainties are optimized by a two-stage stochastic programming model and compared with a referencing deterministic case. Specifically, the uncertainties of photovoltaic (PV) generation and energy demand are investigated.

Regarding system capacity, a larger energy storage capacity is needed to accommodate a higher uncertainty. The superimposed uncertainties have a higher effect on system capacity than the sum of the effect of each uncertainty. The uncertainty of energy demand has a higher impact than the uncertainty of PV generation.

Regarding system operation, the increase in operation cost is smaller than the increase in investment cost and total cost. In addition, the average flexibility provided by the energy storage increases with uncertainty and uncertainties affect the change rate for power charging/discharging of the electric energy storage. Regarding the effect on the grid, the uncertainties increase not only the magnitude of ramping-rate, but also the frequency of power-dispatch.

Intra-city Public Charging Stations (PCSs) play a crucial role in promoting the mass deployment of Electric Vehicles (EVs). To motivate the investment on PCSs, this work proposes a novel framework to find the optimal location and size of PCSs, which can maximize the benefit of the investment. The impacts of charging behaviors and urban land uses on the income of PCSs are taken into account. An agent-based trip chain model is used to represent the travel and charging patterns of EV owners. A cell-based geographic partition method based on Geographic Information System is employed to reflect the influence of land use on the dynamic and stochastic nature of EV charging behaviors. Based on the distributed charging demand, the optimal location and size of PCSs are determined by mixed-integer linear programming. Västerås, a Swedish city, is used as a case study to demonstrate the model's effectiveness. It is found that the charging demand served by a PCS is critical to its profitability, which is greatly affected by the charging behavior of drivers, the location and the service range of PCS. Moreover, charging price is another significant factor impacting profitability, and consequently the competitiveness of slow and fast PCSs.

Governments foster voluntary actions within households to mitigate climate change. However, the literature suggests that they may not be as effective as expected due to rebound effects. We use a dynamic economy–energy–environment computable general equilibrium (CGE) model of the Catalan economy to simulate the effect of 75 different actions on GDP and net CO2 emissions, over a 20-year period. We also examine how a carbon tax could counteract the carbon rebound effects. We find energy rebound effects ranging from 61.77% to 117.49% for voluntary energy conservation actions, depending on where the spending is redirected, with similar carbon rebound values. In our main scenarios, where energy savings are redirected to savings and all non-energy goods proportionally, the rebound is between 64.47% and 66.90%. We also find, for these scenarios, that a carbon tax of between 2.4 and 3.6 €/ton per percentage point of voluntary energy reduction would totally offset carbon rebound effects. These results suggest that voluntary actions in households need additional measures to provide the expected results in terms of energy use reduction and climate change mitigation.

This paper provides retrospective firm-level evidence on the effectiveness of China’s carbon market pilots in reducing emissions in the electricity sector. We show that the carbon emission trading system (ETS) has no effect on changing coal efficiency of regulated coal- fired power plants. Although we find a significant reduction in coal consumption associated with ETS participation, this reduction was achieved by reducing electricity production. The output contraction in the treated plants is not due to their optimizing behavior but is likely driven by government decisions, because the impacts of emission permits on marginal costs are small relative to the controlled electricity prices and the reduction is associated with financial losses. In addition, we find no evidence of carbon leakage to other provinces, but a significant increase in the production of non-coal-fired power plants in the ETS regions.