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The integration of commercial onshore large-scale wind farms into a national grid comes with several technical issues that predominately ensure power quality in accordance with respective grid codes. The resulting impacts are complemented with the absorption of larger amounts of reactive power by wind generators. In addition, seasonal variations and inter-farm wake effects further deteriorate the overall system performance and restrict the optimal use of available wind resources. This paper presented an assessment framework to address the power quality issues that have arisen after integrating large-scale wind farms into weak transmission grids, especially considering inter-farm wake effect, seasonal variations, reactive power depletion, and compensation with a variety of voltage-ampere reactive (Var) devices. Herein, we also proposed a recovery of significant active power deficits caused by the wake effect via increasing hub height of wind turbines. For large-scale wind energy penetration, a real case study was considered for three wind farms with a cumulative capacity of 154.4 MW integrated at a Nooriabad Grid in Pakistan to analyze their overall impacts. An actual test system was modeled in MATLAB Simulink for a composite analysis. Simulations were performed for various scenarios to consider wind intermittency, seasonal variations across four seasons, and wake effect. The capacitor banks and various flexible alternating current transmission systems (FACTS) devices were employed for a comparative analysis with and without considering the inter-farm wake effect. The power system parameters along with active and reactive power deficits were considered for comprehensive analysis. Unified power flow controller (UPFC) was found to be the best compensation device through comparative analysis, as it maintained voltage at nearly 1.002 pu, suppressed frequency transient in a range of 49.88-50.17 Hz, and avoided any resonance while maintaining power factors in an allowable range. Moreover, it also enhanced the power handling capability of the power system. The 20 m increase in hub height assisted the recovery of the active power deficit to 48%, which thus minimized the influence of the wake effect.

Using the time series data from 1990-2011, this paper is an attempt to explore the relationship between economic conditions and criminal activities in Pakistan. Three variables are being used for economic conditions like increasing female employment in labor market, CPI which denotes inflation and income inequality. We check their relationship with total reported crime with reference to Pakistan. The Augmented Dicky Fuller test is used for unit root process which suggested that all the variables are stationary at the 1st level. For the long run relationship Johanson-Cointegration technique has been applied. After statistical procedure results suggested that female employment, inflation and the Gini index are strongly related with crime. Coefficient of Gini index is high which means that in long-run income inequality affects the crime more than other two because income inequality is a long-run phenomenon so it affect the criminal activities with great magnitude. Vector Correction Model (VCM) has been applied to check the short-run relationship between variables. VCM results suggested that the model we estimate is divergent. Divergent model mean that there is no adjustment from long-run to short-run between variables as they are going away from equilibrium. If we increase the lag length, the model can become divergent but due to crime data unavailability it was difficult to increase the observations and the lags as well. Research paper gives evidence that economic conditions have significant impact on crimes and increasing female employment which is considered as labor market improvement is positively related with crime in Pakistan. This relationship may be the result of market imperfections. Moreover inflation by decreasing purchasing power and income inequality by increasing the gap between social classes is also the cause of increasing crime and they contribute significantly in crime situation of country.

This paper tries to analyze the impacts of budget deficit on macroeconomic aspects of Pakistan. In fact the ways through which budget deficit is financed, can affect money supply, output, exchange rate and then foreign trade. Annual data for the period 1970-2010 has been taken for analysis. ADF test used for stationarity test, 3-Stage Least-Square method is adopted for estimation by using STATA-10 software. The study revealed the Output changes are positively related to BCP and Government expenditures but negatively with interest rate. Money supply is positively related to GBD, BCP and foreign reserves(R). So money supply does increase whenever we try to finance budget deficit through Government, private or external borrowing. On the other hand, changes in Exports and Imports depend on changes in ER and their relative prices respectively which are affected by money supply. But the changes in imports are bigger than changes in exports, pushing the balance of trade towards deficit. Our study has also measured the negative relation between Balance of Trade and Output. Study concludes that when government tries to use government expenditures to get higher output, deficit may come into existence and then financing the budget deficit results in inflation, trade deficit and afterwards affects output.