Reservoir operation rules play an important role in regions economic development. Meanwhile, hedging policies are mostly applied for municipal, industrial, and irrigation water supplies from reservoirs and it is less used for reservoir operation for hydropower generation. The concept of hedging and rationing factors can be used to maintain the water in a reservoir for the sake of increasing water storage and water head for future use. However, water storage and head are the key factors in operation of reservoir systems for hydropower generation. This study investigates the applicability of seven competing hedging policies including four customary forms of hedging (1PHP, 2PHP, 3PHP, DHP) and three new forms of hedging rules (SOPHP, BSOPHP, SHPHP) for reservoir operation for hydropower generation. The models were constructed in MATLAB R2011b based on the characteristics of the Batang Padang hydropower reservoir system, Malaysia. In order to maximize the output of power generation in operational periods (2003–2009), three optimization algorithms namely particle swarm optimization (PSO), genetic algorithm (GA), and hybrid PSO-GA were linked to one of the constructed model (1PHP as a test) to find the most effective algorithm. Since the results demonstrated the superiority of the hybrid PSO-GA algorithm compared to either PSO or GA, the hybrid PSO-GA were linked to each constructed model in order to find the optimal decision variables of each model. The proposed methodology was validated using monthly data from 2010–2012. The results showed that there are no significant difference between the output of monthly mean power generation during 2003–2009 and 2010–2012.The results declared that by applying the proposed policies, the output of power generation could increase by 13% with respect to the historical management. Moreover, the discrepancies between mean power generations from highest to lowest months were reduced from 49 MW to 26 MW, which is almost half. This means that hedging policies could efficiently distribute the water-supply and power-supply in the operational period and increase the stability of the system. Among the studied hedging policies, SHPHP is the most convenient policy for hydropower reservoir operation and gave the best result.

Environmental Health Engineering And Management Journal مجله مدیریت و مهندسی بهداشت محیط

Background: Changes in temperature and precipitation pattern seriously affect the amount of river runoff coming into Dam Lake. These changes could influence the operating conditions of reservoir systems such as Jor hydropower reservoir system (Malaysia) with the total capacity of 150 MW. So, it is necessary to analyze the effect of changes in weather parameters on the river runoff and consequently, the hydropower production. Methods: In this research, LARS-WG was used to downscale the weather parameters such as daily minimum temperature, maximum temperature, and precipitation based on one of the general circulation sub-model (HADCM3) under three emission scenarios, namely, A1B, A2, and B1 for the next 50 years. Then, the artificial neural network (ANN) was constructed, while rainfall and evapotranspiration were used as input data and river runoff as output data to discover the relationship between climate parameters and runoff at the present and in the future time. Results: It was revealed that the monthly mean temperature will increase approximately between 0.3- 0.7°C, while the mean monthly precipitation will vary from -22% to +22% in the next 50 years. These changes could shift the dry and wet seasons and consequently, change the river runoff volume. In most months, the results of models integration showed reductions in river runoff. Conclusion: It can be concluded that the output of hydropower reservoir system is highly dependent on the river runoff. So, the impacts of climate changes should be considered by the reservoir operators/ managers to reduce these impacts and secure water supplies.

Background: Special attention should be given to the seepage in dams since it may cause failure. Seepage is not considered in the total risk factor calculated using the International Commission of Large Dams (ICOLD), the United States Bureau Reclamation (USBR) while the description of the dam seepage condition is given a weightage in the Brazilian method. Methods: Haditha Dam, Iraq, was constructed on varying degrees of limestone beds of the Euphrates and Ana formations. Therefore, seepage from the dam should be continuously monitored and accurately measured. In the present study, a methodology was proposed to overcome the problem of inconsistent seepage data. The inconsistent seepage rates can be replaced by the predicted seepage rates obtained from SEEP/W model. Results: The predicted seepage rates for different water levels in the reservoir of Haditha Dam were found in association (R2=0.96). In addition, the value of mean absolute error (MAE) for the model accuracy was found to be 0.0106. According to the Brazilian index, the weightage for the seepage condition of Haditha dam was in the second category and equal to 3. Conclusion: For Haditha Dam, the seepage data cannot be used in the dam risk assessment since it was inconsistent with gaps, and it can be replaced by the consistent predicted seepage rates predicted by SEEP/W model. Generally, the aging and other dam problems result in increasing seepage rate. This highlights the importance of efficient management that follows resilient monitoring and surveillance programs that ensure dam safety.