This study presents an assessment of the version-6 (V06) of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product from June 2014 to December 2017 over different hydro-climatic regimes in the Tianshan Mountains. The performance of IMERG-V06 was compared with IMERG-V05 and the Tropical Rainfall Measuring Mission (TRMM) 3B42V7 precipitation products. The precipitation products were assessed against gauge-based daily and monthly precipitation observations over the entire spatial domain and five hydro-climatologically distinct sub-regions. Results showed that: (1) The spatiotemporal variability of average daily precipitation over the study domain was well represented by all products. (2) All products showed better correlations with the monthly gauge-based observations than the daily data. Compared to 3B42V7, both IMERG products presented a better agreement with gauge-based observations. (3) The estimation skills of all precipitation products showed significant spatial variations. Overall performance of all precipitation products was better in the Eastern region compared to the Middle and Western regions. (4) Satellite products were able to detect tiny precipitation events, but they were uncertain in capturing light and moderate precipitation events. (5) No significant improvements in the precipitation estimation skill of IMERG-V06 were found as compared to IMERG-V05. We deduce that the IMERG-V06 precipitation detection capability could not outperform the efficiency of IMERG-V05. This comparative evaluation of the research products of Global Precipitation Measurement (GPM) and TRMM products in the Tianshan Mountains is useful for data users and algorithm developers.

Managing transmission congestion had been a major problem with growing competition in the power networks. Competitiveness emerges through the network's reconfiguration and the proliferation of secondary facilities. Congestion of transmission lines is a critical issue, and their regulation poses a technical challenge as the power system is deregulated. The present research illustrates a multi-objective strategy for reaching the optimal capabilities of distributed generators (DG) like wind power plants and geothermal power-producing plants to alleviate congestion throughout the transmission network. Goals such as congestion management during power delivery, power loss reduction, power flow improvement with the enhancement of voltage profile, and investment expenditure minimization are considered to boost the network's technological and economic reliability. The congestion management is achieved using the locational marginal price (LMP) and calculation of transmission congestion cost (TCC) for the optimal location of DG. After identification of congested lines, DG is optimally sized by particle swarm optimization (PSO) and a newly proposed technique that combines the features of modified IL-SHADE and PSO called hybrid swarm optimization (HSO) which employs linear population size reduction technique which improves its performance greatly by reducing the population size by elimination of least fit individuals at every generation giving far better results than those obtained with PSO. In addition, optimal rescheduling of generations from generators has been done to fulfill the load demand resulting in alleviation of congested lines thereby enhancing the performance of the network under investigation. The performance of the proposed methodology of HSO and PSO has been tested successfully on standard IEEE-30 & IEEE-57 bus configurations in a MATLAB environment with the application of MATPOWER power system package.

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Escalation in electricity consumption and environmental pollution worldwide necessitates the need for alternative and sustainable energy sources other than conventional sources. Therefore, in this article, renewable energy-based microgrid is presented to cater such needs. Different feasible microgrid topologies are determined and analyzed to meet the demand of the proposed site. The feasibility evaluation of the different microgrid configurations is performed based on the cost factors and carbon dioxide (CO 2 ) emissions. The optimum configuration is selected based on the minimum cost of annual operating charges, annual energy charges and annual social cost of CO 2 emissions taken altogether. Besides this, the comparison of the various configurations is also performed on the basis of net present cost, capital expenditure and cost of energy. For analysis, the site profile and load profile of Jamia Millia Islamia University, India, are taken. The optimization is performed in HOMER. It is obtained from the simulation results that the microgrid configuration comprising grid-solar photovoltaic-wind turbine is found to be best suited for the proposed site based on various parameters. Furthermore, the efficacy of the proposed system is compared with conventional grid-only system.

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Electricity market economics is one of the vital factors which play a key role in achieving the efficient operation of the power system. Economic operation along with secure & reliable operation is must for ensuring optimum utilization of the resources in order to maximize social welfare. This article presents a method for achieving economic operation of electricity market in case of congestion occurring in the system. The generator sensitivity (GS) method alone can manage the system congestion, however it does not consider the economic benefits which can be achieved by considering the bids submitted by the generators and as a result it leads to situation of market power. To avoid such scenario, bid sensitivity factor (BSF) is proposed to select the generators to participate and regulate their real power generation for alleviating congestion from the system optimally. The BSF takes into account the GS as well as bids of the generators.In this paper, the effectiveness of the proposed method in eliminating market power is realized by changing the bids of the generators. The proposed method is tested on IEEE 30-bus system and IEEE 118-bus system. The obtained results show an encouraging pattern for managing the congestion more optimally and economically.