Research on Operation of Electrothermal Integrated Energy System Including Heat Pump and Thermal Storage Units Based on Capacity Planning

In view of the Three North areas existing wind power absorption and environment pollution problems,the previous scholars have improved the wind abandon problem by adding electrothermal coupling equipment or optimizing power grid operation.In this paper,an electrothermal integrated energy system including heat pump and thermal storage units was proposed.The scheduling model was based on the load data and the output characteristics of power units,each power unit capacity was programmed without constraints,and the proposed scheduling model was compared with the traditional combined heat and power scheduling model.Results showed that the investment and pollutant discharge of the system was reduced respectively.Wind power was fully absorbed.Compared with the traditional thermal power unit,the proportion of the output was significantly decreased by the proposed model.The proposed system could provide a new prospect for wind power absorption and environment protection.

Variability scaling and capacity planning in Covid-19 pandemic

Capacity planning is a very important global challenge in the face of Covid-19 pandemic.In order to hedge against the fluctuations in the random demand and to take advantage of risk pooling effect,one needs to have a good understanding of the variabilities in the demand of resources.However,Covid-19 predictive models that are widely used in capacity planning typically often predict the mean values of the demands(often through the predictions of the mean values of the confirmed cases and deaths)in both the temporal and spatial dimensions.They seldom provide trustworthy prediction or estimation of demand variabilities,and therefore,are insufficient for proper capacity planning.Motivated by the literature on variability scaling in the areas of physics and biology,we discovered that in the Covid-19 pandemic,both the confirmed cases and deaths exhibit a common variability scaling law between the average of the demand μ and its standard deviationσ,that is,σ ∝ μ^(β),where the scaling parameterμis typically in the range of 0.65 to 1,and the scaling law exists in both the temporal and spatial dimensions.Based on the mechanism of contagious diseases,we further build a stylized network model to explain the variability scaling phenomena.We finally provide simple models that may be used for capacity planning in both temporal and spatial dimensions,with only the predicted mean demand values from typical Covid-19 predictive models and the standard deviations of the demands derived from the variability scaling law.

Study of future power interconnection scheme in ASEAN

The current energy supply trajectory in the Association of Southeast Asian Nations(ASEAN)region is not sustainable.Factors such as rising standards of living and demographic patterns,including population growth,lead to continuous increase in power demand,which is difficult to meet using limited fossil fuel resources.Thus,a transition toward clean energy sources is needed in the region.While ASEAN member countries are rich in clean energy resources,such resources are located far from demand centers;thus,allocation of clean energy is necessary to increase its utilization.In this study,power demand is forecasted using a combination of prediction methods.A model to evaluate the installed capacity and power exchange potential is proposed to deal with mismatch between the location of the clean energy base and the load center.Furthermore,the concept of cross-regional allocation of clean energy between the ASEAN region,China,and South Asia is presented.A power interconnection scheme among the ASEAN member countries as well as neighboring countries is proposed based on the power exchange potential.The proposed grid interconnection scheme contributes to the utilization of clean energy in the ASEAN region,increasing the proportion of clean energy in the generation mix,which ensures that the region becomes a sustainable and resilient society with a clean and low carbon development route.Furthermore,the proposed power interconnection scheme will generate valuable economic,social,environmental,and resource allocation benefits.

Five Major Concerns about China’s Wind Power Development

Economic issue is the very focus of China's wind power development.Although all the security problems can be dealt with through technical measures,the compensation for supportive thermal power units and the subsidy from economically developed regions to resource-outputting regions would require a higher level of strategic considerations.The core purpose of developing wind energy is to reduce pollutant emissions,so planners should take into account the overall cost of all sides,without touching the bottom of social affordability.

Reliable planning of isolated Building Integrated Photovoltaic systems

In this paper,two probabilistic reliability indices are presented to define the effect of clouds on different types of Building Integrated Photovoltaic(BIPV)systems.Existing indices do not match the main features of photovoltaic(PV)sources,such as variability,uncertainty and dependency on weather conditions.In addition,they are time indicators that describe the percentage of total failure time per year without any indication about power or energy mismatch.By using the available Geographic Information System solar-irradiation database,the proposed indices consider a similar pattern of expected daily solar irradiation as a model of PV systems.Two different models are studied for diverse building loads:an energy model for flexible loads and a constant-power model for critical loads.A comparative study is implemented for six different locations:Cairo,London,Berlin,Beijing,Madrid and Riyadh.Moreover,three types of BIPV systems are studied:fixed,double-axis-tracking and concentrated PV systems.The presented results show the effects of clouds,PV type and locations on the system performance.

Air route network optimization in fragmented airspace based on cellular automata

Air route network optimization,one of the essential parts of the airspace planning,is an effective way to optimize airspace resources,increase airspace capacity,and alleviate air traffic congestion.However,little has been done on the optimization of air route network in the fragmented airspace caused by prohibited,restricted,and dangerous areas（PRDs）.In this paper,an air route network optimization model is developed with the total operational cost as the objective function while airspace restriction,air route network capacity,and non-straight-line factors（NSLF） are taken as major constraints.A square grid cellular space,Moore neighbors,a fixed boundary,together with a set of rules for solving the route network optimization model are designed based on cellular automata.The empirical traffic of airports with the largest traffic volume in each of the 9 flight information regions in China's Mainland is collected as the origin-destination（OD） airport pair demands.Based on traffic patterns,the model generates 35 air routes which successfully avoids 144 PRDs.Compared with the current air route network structure,the number of nodes decreases by 41.67%,while the total length of flight segments and air routes drop by 32.03% and 5.82% respectively.The NSLF decreases by 5.82% with changes in the total length of the air route network.More importantly,the total operational cost of the whole network decreases by 6.22%.The computational results show the potential benefits of the model and the advantage of the algorithm.Optimization of air route network can significantly reduce operational cost while ensuring operation safety.