Research of Rural Power Network Reactive Power Optimization Based on Improved ACOA

In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm （ACOA） was used to optimize the reactive power compensation for the rural distribution system. In this study, the traditional ACOA was improved in two aspects： one was the local search strategy, and the other was pheromone mutation and re-initialization strategies. The reactive power optimization for a county＇s distribution network showed that the improved ACOA was practicable.

Analyzing the Effectiveness of Policy Implementation at the Local Level: A Case Study of Management of the 2009–2010 Drought in Yunnan Province, China

Several research efforts have focused primarily on policy implementation and improving innovative actions to address disaster risks. Discussions are ongoing on how to measure the effectiveness of policy implementation at the local level. But there is no definitive theory of effective policy implementation, and very few frameworks have been found acceptable as the basis of an analysis of the effectiveness of policy implementation, especially on droughts. Based on the 2009–2010 extreme drought in Yunnan, China, this article presents a modified framework to assess the effectiveness of policy implementation by defining policy, practice, and performance, as well as a feedback loop by which to share the lessons learned. Water conservancy projects in Luliang County and the agricultural diversity program in Longyang County in Yunnan Province were analyzed from a farmers' perspective. It was found that farmers are highly dependent on government policies and projects, and the effectiveness of policies is measured by short-term, immediate, and tangible benefits rather than long-term adaptation strategies. The results highlight the urgent need to reduce risks by developing better awareness about climate change and drought and its impacts, increased understanding of drought hazards, and implementation of appropriate measures for long-term adaptation.

A new approach to LST modeling and normalization under clear-sky conditions based on a local optimization strategy

The normalization of LST relative to environmental parameters is of great importance in various environmental applications. The purpose of this study was to develop a new approach for LST normalization relative to environmental variables. These included topographic variables (i.e. solar irradiance and near-surface temperature lapse rate (NSTLR)) as well as biophysical properties (i.e. vegetation,wetness,and albedo). The study was conducted in two phases,namely (1) using global and (2) local optimization strategies to calculate the regression coefficients of environmental variables in the partial least squares regression (PLSR) and build the non-linear linking model in the random forest regression (RFR). The RMSEs between actual LST and modeled LST based on the global and local optimization strategies using PLSR (RFR) were 2.202 (0.935) and 0.939 (0.835) °C,respectively. The results showed that RFR had higher efficiency than PLSR in normalizing LST. Moreover,the local optimization method outperformed the global optimization method in terms of normalization accuracy. The results of this study could be very useful in many environmental applications such as identifying thermal anomalies,and surface anthropogenic heat island modeling.

TOWARD SUSTAINABLE MAIZE PRODUCTION FOR SMALLHOLDERS THROUGH OPTIMIZED STRATEGIES IN NORTH CHINA

Agricultural production by smallholders is crucial for ensuring food provision in China.However,smallholders face a series of challenges on their farms including high-to-excess resource inputs,low use efficiency,as well as negative environmental impacts,which may be unfavorable for sustainable agriculture production.This study developed a county-level sustainability assessment of maize production in Hebei,China,by applying multiple data sources in combination with emergy,carbon footprint,nitrogen footprint and costbenefit analyses.Scenario analysis was applied to explore the localized implementation strategies to achieve the sustainable farming system.The results show that the average emergy sustainability index(ESI)of maize at 2.31 is relatively low.The average greenhouse gas(GHG)emissions and reactive nitrogen(Nr)losses are 0.15 g·kcal^(−1) CO_(2)-eq and 3.75 mg·kcal^(−1) N,respectively.The average cost and net income are 12,700 and 4340 CNY·ha^(−1),respectively.These results indicate a great potential to improve the environmental-economic sustainability of the maize production system of smallholders.In addition,the environmental and economic indicators calculated from the maize production show a substantial spatial heterogeneity among counties,indicating a requirement for different optimization strategies to improve the environment-economy sustainability at a finer scale.Based on the multiple scenario analysis,optimal strategies targeting each county are proposed.By adopting the optimal strategies,the average ESI and net income could increase by 32%and 83%,respectively,and the average GHG emissions and Nr losses reduce by 33%and 35%,respectively.These findings provide an important reference for adopting different strategies to achieve environmenteconomy sustainability for smallholders production systems with diverse landscapes in North China and propose a transition pathway toward achieving agriculture sustainability for smallholders worldwide.

Route planning of truck and multi-drone rendezvous with available time window constraints of drones

During the scenarios of cooperative tasks performed by a single truck and multiple drones,the route plan is prone to failure due to the unpredictable scenario change.In this situation,it is significant to replan the rendezvous route of the truck and drones as soon as possible,to ensure that all drones in flight can return to the truck before running out of energy.This paper addresses the problem of rendezvous route planning of truck and multi-drone.Due to the available time window constraints of drones,which limit not only the rendezvous time of the truck and drones but also the available period of each drone,there are obvious local optimum phenomena in the investigated problem,so it is difficult to find a feasible solution.A two-echelon heuristic algorithm is proposed.In the algorithm,the strategy jumping out of the local optimum and the heuristic generating the initial solution are introduced,to improve the probability and speed of obtaining a feasible solution for the rendezvous route.Simulation results show that the feasible solution of the truck-drones rendezvous route can be obtained with 88%probability in an average of 77 iterations for the scenario involving up to 25 drones.The influence of algorithm options on planning results is also analyzed.