please solve it quickly

9 10 11 12 13 Title CLO 3 (5 marks), Abstract CLO 2 (5 marks), Introduction CLO 2 (5 marks) Explain how the following planned manuscript title, abstract and text could be improved? Find all missing aspects, punctuation and grammar mistakes and propose correction. A table is given below title, abstract and text which is required to be filled with line no, mistake, proposed correction and teacher's comment Availability estimation of wind power forecasting & optimization of dayahead unit commitment with STATCOM Title Line No. Mistake Identified Proposed Correction Teacher's Comment 14 15 16 17 18 19 20 21 22 23 24 25 26 Abstract: Due to the uncertainty of the accuracy of wind power forecasting, wind turbines cannot be accurately equated with dispatchable units in the preparation of a day-ahead dispatching plan for power grid. A robust optimization model for the uncertainty of wind power forecasting with a given confidence level is established. Based on the forecasting value of wind power and the divergence function of forecasting error, a robust evaluation method for the availability of wind power forecasting during given load peaks is established [1]. A simulation example is established based on a power system in Northeast China and an IEEE 39-node model. The availability estimation parameters are used to calculate the equivalent value of wind power of the conventional 27 28 29 30 unit to participate in the day-ahead dispatching plan. The simulation results show that the model can effectively handle the challenge of uncertainty of wind power forecasting, and enhance the consumption of wind power for the power system with 25% increase in efficiency at 3.0 loading condition Abstract Mistake Identified Proposed Correction Line No. Teacher's Comment 31 32 33 34 35 36 37 38 39 40 41 Introduction: With the ongoing global petrochemical energy depletion, environmental degradation is an increasingly serious situation. The global Energy Internet, with renewable energy, has emerged as the main energy supply form and electric energy as the main energy carrier, which is an inevitable trend for the development of human energy system and energy industry [2,3]. In addition, such power generations with renewable energy such as wind power and photovoltaic power, have transformed the pattern of modern power system and the form of power generation [4]. In the current pattern, one of the serious challenges is that the operation of power grid requires stability, while the integration scale of fluctuating unpredicted renewable energies has been increasing (5, 6]. 42 43 44 45 46 47 48 49 50 Wind power generation is now a key component in renewable energy generation in 2016, the installed capacity in China increased to 16900000000000 kW while the abandoned wind power increased to 49.7 billion kW, a 50% increase over the previous year, with 17% rate of curtailed power [9]. The main reason is that the output of wind power is obviously random and uncertain due to the climate and environment change. The increasing scale of the existing system, including wind power, will have to guarantee a stronger power balance in power system and make its operation less hazardous. Therefore, the current methods are being challenged [10,11,12,13). 51 52 53 54 55 56 57 58 59 60 61 62 Wind power forecasting and its ongoing improvements are eye-catching in wind power industries and the management of power system. So far, the studies of wind power forecasting and its improvement are based on the assumption that completely accurate information of geographic environment and climate is given Then, the investigation of theory or method about the relationship between this information and wind power capacity is determined. And on this basis, the probability distribution of errors is forecasted [14, 15). At present the general method within and outside China is based on the criteria of climate, namely, the improvement of forecasting accuracy of wind power output. The model of the numerical weather prediction (NWP) as well as the information about the developer, will be listed in [16]. On such a basis, the Kalman filtering algorithm is proposed in [17] to filter the output of the SKIRON NWP model, which significantly improves the forecasting accuracy of wind speed and wind power. II 63 64 65 66 67 68 69 70 71 A scenario tree tool is developed in [17], which allows the statistics of wind power forecasting error to be altered and facilitates the study of how these statistics impact unit commitment and system operation. A general methodology for deriving optimal bidding strategies based on probabilistic forecasting of wind generation is proposed in [18], and the sensitivity of wind power costs has been analyzed. The opportunities available are explored for wind power producers (WPPs) if they can purchase or schedule some reserves to offset part of their deviations rather than being fully penalized in the real-time market, and the revenue for WPPS with such mechanisms is modeled in [19]. 64 65 66 67 68 69 70 71 A scenario tree tool is developed in [17], which allows the statistics of wind power forecasting error to be altered and facilitates the study of how these statistics impact unit commitment and system operation A general methodology for deriving optimal bidding strategies based on probabilistic forecasting of wind generation is proposed in [18), and the sensitivity of wind power costs has been analyzed. The opportunities available are explored for wind power producers (WPPs) if they can purchase or schedule some reserves to offset part of their deviations rather than being fully penalized in the real-time market, and the revenue for WPPS with such mechanisms is modeled in [19]. 72 73 74 75 76 77 78 79 80 81 However, as the dispatching systems of power grid are facing more and more uncertainties related to wind power forecasting errors, the scheduling system of power grid has insufficient information to handle these uncertainties under the fast increasing scale of wind power integration interconnection among various energies. Therefore, the current method demanding accurate information cannot fulfill the need in the real work of the scheduling system [20,21,22,23). It is impossible to take the forecasting value of wind power as the effective power output in day-ahead dispatching plan based on the reliability of power supply during the peak load period. This results in a large number of curtailed wind power due to the minimum output limit of conventional units during a low-load period. 82 83 84 85 86 87 88 89 Therefore, wind power availability can be accurately evaluated or calculated by using a robust estimation. The minimum possible wind power output can be inferred based on the forecasting results of wind power, so that wind power can be used as a reliable source to replace a certain proportion of conventional energy units and participate in the day-ahead dispatching plan of power system. To improve the efficiency of unit commitment, it is necessary to reduce the number of unit start-ups and shut-downs, and to have a decisive role in significantly reducing the curtailed wind. The model is show in figu.1. 90 91 92 93 94 95 96 97 A robust estimation model for the maximum probability rate of wind power prediction and its probability distribution is proposed, which is different from the traditional theory of improvement of wind power forecasting accuracy. With the current theory of prediction of wind power, based on the results of wind power forecasting, the availability of wind power during the peak load period can be obtained. According to their availability, the unit commitment can be better arranged to tackle the conflict between the fluctuation of wind power and the reserve capacity, so the challenge of dispatching faced by the power grid with large-scale wind power can be handled. Introduction Line No. Mistake Identified Proposed Correction Teacher's Comment 98 9 10 11 12 13 Title CLO 3 (5 marks), Abstract CLO 2 (5 marks), Introduction CLO 2 (5 marks) Explain how the following planned manuscript title, abstract and text could be improved? Find all missing aspects, punctuation and grammar mistakes and propose correction. A table is given below title, abstract and text which is required to be filled with line no, mistake, proposed correction and teacher's comment Availability estimation of wind power forecasting & optimization of dayahead unit commitment with STATCOM Title Line No. Mistake Identified Proposed Correction Teacher's Comment 14 15 16 17 18 19 20 21 22 23 24 25 26 Abstract: Due to the uncertainty of the accuracy of wind power forecasting, wind turbines cannot be accurately equated with dispatchable units in the preparation of a day-ahead dispatching plan for power grid. A robust optimization model for the uncertainty of wind power forecasting with a given confidence level is established. Based on the forecasting value of wind power and the divergence function of forecasting error, a robust evaluation method for the availability of wind power forecasting during given load peaks is established [1]. A simulation example is established based on a power system in Northeast China and an IEEE 39-node model. The availability estimation parameters are used to calculate the equivalent value of wind power of the conventional 27 28 29 30 unit to participate in the day-ahead dispatching plan. The simulation results show that the model can effectively handle the challenge of uncertainty of wind power forecasting, and enhance the consumption of wind power for the power system with 25% increase in efficiency at 3.0 loading condition Abstract Mistake Identified Proposed Correction Line No. Teacher's Comment 31 32 33 34 35 36 37 38 39 40 41 Introduction: With the ongoing global petrochemical energy depletion, environmental degradation is an increasingly serious situation. The global Energy Internet, with renewable energy, has emerged as the main energy supply form and electric energy as the main energy carrier, which is an inevitable trend for the development of human energy system and energy industry [2,3]. In addition, such power generations with renewable energy such as wind power and photovoltaic power, have transformed the pattern of modern power system and the form of power generation [4]. In the current pattern, one of the serious challenges is that the operation of power grid requires stability, while the integration scale of fluctuating unpredicted renewable energies has been increasing (5, 6]. 42 43 44 45 46 47 48 49 50 Wind power generation is now a key component in renewable energy generation in 2016, the installed capacity in China increased to 16900000000000 kW while the abandoned wind power increased to 49.7 billion kW, a 50% increase over the previous year, with 17% rate of curtailed power [9]. The main reason is that the output of wind power is obviously random and uncertain due to the climate and environment change. The increasing scale of the existing system, including wind power, will have to guarantee a stronger power balance in power system and make its operation less hazardous. Therefore, the current methods are being challenged [10,11,12,13). 51 52 53 54 55 56 57 58 59 60 61 62 Wind power forecasting and its ongoing improvements are eye-catching in wind power industries and the management of power system. So far, the studies of wind power forecasting and its improvement are based on the assumption that completely accurate information of geographic environment and climate is given Then, the investigation of theory or method about the relationship between this information and wind power capacity is determined. And on this basis, the probability distribution of errors is forecasted [14, 15). At present the general method within and outside China is based on the criteria of climate, namely, the improvement of forecasting accuracy of wind power output. The model of the numerical weather prediction (NWP) as well as the information about the developer, will be listed in [16]. On such a basis, the Kalman filtering algorithm is proposed in [17] to filter the output of the SKIRON NWP model, which significantly improves the forecasting accuracy of wind speed and wind power. II 63 64 65 66 67 68 69 70 71 A scenario tree tool is developed in [17], which allows the statistics of wind power forecasting error to be altered and facilitates the study of how these statistics impact unit commitment and system operation. A general methodology for deriving optimal bidding strategies based on probabilistic forecasting of wind generation is proposed in [18], and the sensitivity of wind power costs has been analyzed. The opportunities available are explored for wind power producers (WPPs) if they can purchase or schedule some reserves to offset part of their deviations rather than being fully penalized in the real-time market, and the revenue for WPPS with such mechanisms is modeled in [19]. 64 65 66 67 68 69 70 71 A scenario tree tool is developed in [17], which allows the statistics of wind power forecasting error to be altered and facilitates the study of how these statistics impact unit commitment and system operation A general methodology for deriving optimal bidding strategies based on probabilistic forecasting of wind generation is proposed in [18), and the sensitivity of wind power costs has been analyzed. The opportunities available are explored for wind power producers (WPPs) if they can purchase or schedule some reserves to offset part of their deviations rather than being fully penalized in the real-time market, and the revenue for WPPS with such mechanisms is modeled in [19]. 72 73 74 75 76 77 78 79 80 81 However, as the dispatching systems of power grid are facing more and more uncertainties related to wind power forecasting errors, the scheduling system of power grid has insufficient information to handle these uncertainties under the fast increasing scale of wind power integration interconnection among various energies. Therefore, the current method demanding accurate information cannot fulfill the need in the real work of the scheduling system [20,21,22,23). It is impossible to take the forecasting value of wind power as the effective power output in day-ahead dispatching plan based on the reliability of power supply during the peak load period. This results in a large number of curtailed wind power due to the minimum output limit of conventional units during a low-load period. 82 83 84 85 86 87 88 89 Therefore, wind power availability can be accurately evaluated or calculated by using a robust estimation. The minimum possible wind power output can be inferred based on the forecasting results of wind power, so that wind power can be used as a reliable source to replace a certain proportion of conventional energy units and participate in the day-ahead dispatching plan of power system. To improve the efficiency of unit commitment, it is necessary to reduce the number of unit start-ups and shut-downs, and to have a decisive role in significantly reducing the curtailed wind. The model is show in figu.1. 90 91 92 93 94 95 96 97 A robust estimation model for the maximum probability rate of wind power prediction and its probability distribution is proposed, which is different from the traditional theory of improvement of wind power forecasting accuracy. With the current theory of prediction of wind power, based on the results of wind power forecasting, the availability of wind power during the peak load period can be obtained. According to their availability, the unit commitment can be better arranged to tackle the conflict between the fluctuation of wind power and the reserve capacity, so the challenge of dispatching faced by the power grid with large-scale wind power can be handled. Introduction Line No. Mistake Identified Proposed Correction Teacher's Comment 98