Schedule Coordination Research Articles

Abstract PS13-26: Effect of an outpatient pharmacy team to improve management and adherence to oral chemotherapy

Abstract Introduction Oral chemotherapy agents have become increasingly common for the treatment of various malignancies, specifically in the metastatic setting. In metastatic breast cancer, oral chemotherapy is now considered the standard of care for first-line treatment due to progression-free survival and overall survival benefits. Oral agents are also considered to be a convenient and less toxic therapy option, improving quality of life. However, these benefits are offset by challenges in the delay to initiation of therapy, adherence, and toxicity management which may lead to high co-pays, delays in treatment, increased clinic visits, and non-adherence. These issues can be augmented at a safety net hospital charged to care for the most vulnerable patients. Close monitoring and follow-up are critical but can be complex and pose an additional burden on the treating oncologist. Pharmacists can serve as an extender to the oncologist and may help mitigate many of these clinical and operational barriers through adherence strategies, toxicity management, care coordination, and optimization of dosing schedules and regimens. Methods/Materials We conducted a quality improvement (QI) initiative aimed to decrease the average number of treatment day delays experienced by patients receiving oral chemotherapy for the treatment of MBC during the first six cycles of chemotherapy. A secondary aim was to improve adherence and patient-provider satisfaction. A protocol was designed and implemented utilizing pharmacists to provide assistance with obtaining the medications through a specialty pharmacy, oral chemotherapy counseling, toxicity assessments, and strategies to help optimize oral adherence (OPTIMAL protocol). Pharmacists conducted live in-person visits and telemedicine visits at weekly to monthly intervals to supplement the ongoing routine care of the oncology provider. All treatment and supportive care recommendations, in addition to any identified barriers, were communicated to the provider. Results A baseline assessment of 63 patients receiving oral oncolytic therapy from December 1st, 2018 through November 26th, 2019 was completed. Patients experienced most delays during cycle 1, with an average of 14.5 days of delay (range 1 - 34 days). The most common reasons for delay throughout the first six cycles of therapy were toxicity development, receipt of medication from the pharmacy, and patient adherence. A separate analysis of patients on CDK4/6 inhibitors (n=8) identified an average treatment day delay of 7.7 days (range 3.2 - 15.3 days) during the first six cycles of chemotherapy. Over a 7-month period, fifteen patients were enrolled in the OPTIMAL protocol and experienced an average treatment day delay of 2.9 days (range 0 - 6.8 days) during the first six cycles. Pharmacists made 206 documented interventions amongst the patients on the protocol, encompassing medication reconciliations, therapy counseling, and clinical recommendations. Eleven patients reported treatment-related toxicities, resulting in six therapy modifications and two-dose modifications. Four patients experienced progression on oral oncolytic therapy and subsequently went on to other treatment options. Conclusion Our protocol to incorporate pharmacists in initial and follow-up clinic visits at an outpatient breast cancer clinic within a safety net hospital was associated with decreased treatment day delays. Pharmacists performed a large number of meaningful clinical and operational interventions to facilitate medication treatment in a, particularly vulnerable population. This intervention supports the valuable and versatile role pharmacists can play in co-managing patients with the rest of the healthcare team. Citation Format: Jasmine Patel, David Michael Hughes, Kathryn Quinn, Tsion Fikre, Naomi Ko. Effect of an outpatient pharmacy team to improve management and adherence to oral chemotherapy [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS13-26.

An Exploratory analysis of flight delay propagation in China

Delay propagation is the flight departure delay caused by the arrival delay of pre-segment flight. Chinese airline market has suffered very poor on-time performance (OTP) in recent years. It is, however, unclear whether delay propagation prevails as one major source for such problem. This study first aims to empirically quantify delay propagation in the Chinese airline market. Specifically, we shed light on heterogenous levels of delay propagations across different airports and airlines. Then, the distinct delay propagation patterns in China are also discussed and compared with other developed airline markets (e.g., the US and Europe). Our estimation is based on OTP data for over 12 million Chinese flights covering the 2015–2017 period. Specifically, it is found that 10 min arrival delay of pre-segment flight within 1 hr before the departure lead to an average of 7.49 mins delay propagation for subsequent departure flight. Arrival delay of earlier pre-segments (1–2 and 2–3 hr before the departure) leads to much less delay propagation, due to longer ground buffer. Chinese airlines arrange longer ground and flight buffer than that of the US airlines to prevent the delay propagation from accumulating along the subsequent flights in a day. Thus, unlike the US market, delay propagation is not the major reason for poor OTP in China. In addition, delay propagation is less prevailing at the Chinese hub airport. This is because China has relied on point-to-point network, which does not require sophisticated schedule coordination. And the local passengers at these Chinese hub airports have higher time value such that the Chinese airlines also try to improve OTP at these hub airports to better serve these lucrative but time-sensitive local passengers. Unlike the European LCCs, Spring Airlines, the largest low-cost carrier (LCC) in China, outperforms major full-service carriers (FSCs) in controlling delay propagation. This finding may also apply to other Northeast Asian LCCs sharing common operational characteristics as Spring Airlines. Last, we find that airlines purposely tolerate moderate departure delays of up to 15 min, which is the threshold that defines delays, no matter whether the pre-segment flight arrives late or on-time. The relevant policy and managerial implications are also discussed.

Joint Optimization of Condition-Based Maintenance and Spare Parts Orders for Multi-Unit Systems with Dual Sourcing

Efficient coordination of maintenance scheduling and spare parts management for critical components can reduce overall operational costs for companies. When sourcing spare parts from more than one supplier, planners can balance response times and prices provided by different suppliers to further reduce operational costs. We develop a joint condition-based maintenance and spare parts provisioning policy for a multi-unit system with dual sourcing. We use a Markov decision process to formulate the sequential-decision problem, which considers degradation states of multiple components and spare parts inventory information from two suppliers. An exact value iteration algorithm is adopted to derive the optimal joint maintenance-and-ordering policy. Interestingly, we find that a replacement will be delayed to judge which component will be replaced first in a two-component system when the degradation level of one component approaches the level of the other one. Numerical results show that our proposed policy with dual sourcing can reduce the expected cost by as much as 42%, compared to the traditional (s,S) policy with single sourcing.

Modeling and optimization of implementation aspects in industrial robot coordination

Cycle time for an assembly line in the automotive industry is a crucial requirement for the overall production rate and business achievements. In a multi-robot station, besides workload distribution, operations sequencing, and robot motions, an important issue is robot coordination. A key aspect, so far neglected, is the robot motion delay due to the implementation of robot coordination scheduling: our first contribution is to model these delays into a mathematical formulation in order to minimize their contribution to the overall cycle time. Two different setup scenarios, based on typical hardware setups, are modeled and optimized. The major contribution is an efficient heuristic algorithm to optimize our suggested model, which provides near optimal solutions in fraction of the time required by a general optimization package. We have also integrated such algorithm in a CAM software for robot offline simulation to be able to run industrial scenarios with real CAD models from the automotive industry. The results show that it is possible to reduce the delays due to the synchronization points and consequently cycle time, while still maintaining the pre-computed nominal time scheduling for robot coordination.

Coordinative scheduling of the mobile robots and machines based on hybrid GA in flexible manufacturing systems

Mobile robots (MRs) constitute a novel manufacturing concept in flexible manufacturing systems and can perform transportation tasks of parts and tools, which significantly contributes to the workshop flexibility and sharing of manufacturing resources. In such a scene, this paper focuses on a complex coordinative scheduling problem of MRs and machines, and a mixed-integer programming model is developed to optimize the makespan. Then, a hybrid genetic algorithm (GA) embedded with a rule-based solution construction method is proposed to solve this problem. Finally, the case study is conducted, and the results indicate that the proposed model performs well with our methods.

Optimal Battery Energy Storage System Scheduling Based on Mutation-Improved Grey Wolf Optimizer Using GPU-Accelerated Load Flow in Active Distribution Networks

In this paper, a novel Mutation-Improved Grey Wolf Optimizer (MIGWO) model is introduced in order to solve the optimal scheduling problem for battery energy storage systems (BESS), considering the mass integration of renewable energy sources (RES), such as solar and wind generation, in active distribution networks. In this regard, four improvements are applied to the conventional GWO algorithm to modify the exploration–exploitation balance for an enhanced convergence rate. The validity and performance of the proposed model are tested on 23 classical benchmark functions and compared to the original algorithm. The new technologies present in active distribution networks lead to increased complexity in the efficient coordination of existing resources, making it necessary to resort to advanced optimization and calculation methods. As operational planning and control functions in power systems are computationally demanding and require multiple power flow calculations, the necessity of simultaneous (parallel) computing techniques emerged. In order to reduce the computing time, an accelerated GPU parallel computing technique is also applied in the proposed model. The MIGWO algorithm is further applied on the modified IEEE-33 bus system aiming to minimize the total power losses, based on the optimal coordination of BESS operation scheduling and RES generation for multiple load demand and local generation scenarios, as well as for various initial state-of-charge values of BESS.

Visualization of Emergency Needs Posted on Social Media by Metaphor Map

Thematic analysis based on a social network is one of the effective means in emergency management. To improve users' understanding, the results of the thematic analysis are often displayed through visualization. However, the previous researches on text theme visualization rarely considered the unified representation of theme structure and theme evolution. Cognitive load leads to difficulty, and it happens due to the separate representation of structure and evolution relationship and it still increases because of the characteristics of urgency, uncertainty, etc. Therefore, a metaphor map is introduced in this study to overcome the limits of previous visualization tools in characterizing the structure and evolutionary relationship of emergency. On the one hand, different elements in the metaphor map represent the information of popularity and structure of the demand, respectively. On the other hand, the visual design based on the metaphor map strengthens the representation of the content and evolution states of the demand themes. At the theoretical level, a visualization method for emergency needs based on the metaphor map is proposed in this study, which enriches the theory of emergency information visualization. At the practical level, this study explores the design of a visualization system based on the metaphor map under crisis scenarios, which enhances the interaction between users and crisis information, and provides references for decision-making such as emergency material scheduling and emergency resource coordination.

Planning skip-stop services with schedule coordination

This paper develops a continuum approximation model for simultaneously designing and coordinating an AB-type skip-stop service, which had been successfully operated in many places (e.g., Chicago, Philadelphia, and Portland in US and Santiago in Chile). The model accounts for spatially heterogeneous demand patterns in transit corridors. Thanks to the parsimonious property, a solution algorithm is developed using calculus of variations and direct search method. In numerical experiments, a variety of scenarios were examined with respect to 14 operational schemes (i.e., the all-stop scheme, the uncoordinated skip-stop scheme, and the coordinated ones of 12 coordination plans), 2 transit modes (i.e., regular bus and rail), and 3 demand patterns (i.e., uniform, low-varied and high-varied demand). The results indicate: (i) the additional benefit of schedule coordination is 2–3% for uncoordinated skip-stop services, which eventually may add up to 6% cost saving as against the traditional all-stop service; (ii) among all coordination plans, the simplest common-headway plan often works best in all tested scenarios; and (iii) for rail system, the operation of the coordinated skip-stop service is very costly due to the requirement of building an extra track, and positive benefit only emerges in the very busy corridors. Lastly, a case study in Chengdu (China) using real surveyed demand data illustrates the application of our model.

A Multilayer Genetic Algorithm for Automated Guided Vehicles and Dual Automated Yard Cranes Coordinated Scheduling

At present, a lot of studies on automatic terminal scheduling are aimed at the shortest operating time. An effective way to reduce the operating time is to increase the amount of operating equipment. However, people often ignore the additional costs and energy consumption caused by increasing the amount of equipment. This paper comprehensively considers the two aspects of the equipment operation time and equipment quantity matching. With the minimum total energy consumption of the operating equipment as the objective function, a cooperative scheduling model of Automated Guided Vehicles (AGVs) and dual Automated Yard Cranes (AYCs) is established. In the modelling process, we also considered the interference problem between dual Automated Yard Cranes (AYCs). In order to solve this complex model, this paper designs an improved multilayer genetic algorithm. Finally, the calculation results from CPLEX and a multilayer genetic algorithm are compared, and the effectiveness of the model and algorithm is proved by experiments. In addition, at the same time, it is proved that it is necessary to consider the interference problem of dual Automated Yard Cranes (AYCs), and the optimal quantity matching scheme for the equipment and the optimal temporary storage location is given.

A data-driven distributionally robust optimization model for multi-energy coupled system considering the temporal-spatial correlation and distribution uncertainty of renewable energy sources

The increasing expansion of wind and gas turbine installation has intensified the interdependency between power system and natural gas network, which poses great challenges to the coordination scheduling of the multi-energy coupled system (MECS). The data-driven robust optimization (DDRO) model is proposed for the energy coupled system. In this model, the temporal-spatial correlation of wind power can be considered based on the minimum volume enclosing convex hull uncertainty set, and the confidence set about the probability distribution for wind power scenarios with the form of the norm-1 and norm-inf constraints is constructed to handle wind power uncertainty. Moreover, to describe natural gas transient characteristics, the hydrodynamic model for gas flow represented as a series of partial differential equations is transformed by the Wendroff difference scheme and linearization technique. And then the master-subproblem framework and tri-level duality-free decomposition method is developed to solve the above model. Finally, the proposed model and solving method are carried out on two test systems with different scale, and the robust optimization models and distributionally optimization models in the existing literatures are implemented for comparison. Simulation results demonstrate the effectiveness and superiority of the proposed model for solving the coordination scheduling problem of MECS.

107 Improving Transitions of Care for Patients Initiated on Buprenorphine from the Emergency Department

Opioid use disorder (OUD) is on the rise nationwide with increasing emergency department (ED) visits and deaths secondary to overdose. Although previous research has shown that patients who are started on buprenorphine in the ED have increased engagement in addiction treatment, access to on-demand medications for OUD is still limited, in part because of the need for outpatient linkages to care. The objective of this study is to describe emergency and outpatient providers’ perception of local barriers to transitions of care for ED-initiated buprenorphine patients. Purposive sampling was used to recruit key stakeholders, who identified as physicians, addiction specialists, and hospital administrators, from 10 EDs and 11 outpatient clinics in King County, Washington. Twenty-one interviews were recorded and transcribed, and then coded by two team members in order to verify accuracy of the thematic analysis. Interview guides and coding were informed by the Consolidated Framework for Implementation Research (CFIR), which provides a structure of domains associated with effective implementation of evidence-based practice. From the 21 interviews with emergency and outpatient providers, four major barriers emerged around transitions of care for ED-initiated buprenorphine patients—stigma, X-waiver shortage, referral incoordination, and loss to follow-up. Interviewees desired a protocolized “standard of care” for the treatment of ED patients with OUD to destigmatize the condition and increase patient self-identification and mission-driven practice. Additionally, participants highlighted the need to increase program capacity through promoting X-waiver training and creating a central repository of outpatient providers in order to streamline referrals. Lastly, interviewees aspired to increase retention of patients in outpatient treatment by having low-barrier scheduling, walk-in appointments, navigation services, and care coordination. There are a number of barriers to translating evidence-based practice around the transitions of care of ED-initiated buprenorphine patients to an urban community setting. Next steps for implementation of this intervention include increasing the number of X-waivered providers, creating a central repository for streamlined referrals and follow-up, and funding navigation services.

Design and Research of Elevator Group Control System Based on PLC

This paper is based on the research of elevator group control system based on PLC, aiming at the phenomenon of elevator in the running process of long time elevator phenomenon, on the basis of improving the utilization of elevator, put forward the overall design structure of elevator group control system, through the communication and control between group control and single elevator, to achieve the unified coordination of elevator scheduling. Considering the riding comfort of passengers, the shortest waiting time of passengers is shortest, and the algorithm of elevator group control scheduling system is analyzed according to the time delay algorithm. At the same time, the elevator control system is analyzed in detail, using PLC to achieve the hardware circuit design, complete the elevator control signal processing, through the inverter control motor operation, to achieve the elevator uplink and downlink. In the design of elevator control software, the overload detection and the delay treatment of the switch door are set up to improve the safety of the elevator, so that the elevator can develop in the direction of intelligent.

Optimization of the Operating Room Scheduling Process for Improving Efficiency in a Tertiary Hospital

Efficient operating room (OR) scheduling can improve OR utilization and reduce costs. We hypothesize that the scheduling office (ORSO) leading the modification scheduling process could increase OR utilization rate. Using retrospective data from a single tertiary hospital in two consecutive calendar years, we compared OR utilization rate, the number of daily cases and cumulative operative time in the pre- and post-implementation of scheduling process alteration. We operated about 100,609 cases in the OR during the study period. Daytime utilization rate increased from 85.6% to 89.4% (P < 0.001); overall OR utilization rate from 115.1% to 117.6% (P = 0.019); daily case numbers from 229.9 ± 7.3 to 239.6 ± 7.6 (P = 0.0.14); and cumulative operation time of total and daytime cases from 611.7 case-hour/day to 624.5 case-hour/day (P = 0.013) and from 510.8 case-hour/day to 533.8 case-hour/day (P < 0.001), respectively. Evening/night time case-hour significantly decreased from 100.9 case-hour/day to 90.7 case-hour/day (P < 0.001). The optimization of the scheduling process and coordination by the office during regular workhours resulted in enhanced OR efficiency. The OR scheduling office can act as a control tower to make OR management more flexible, which can improve efficiency and carry financial benefits in tertiary hospitals.

Cooperative resource management for C-V2I communications in a dense urban environment

Cellular-based vehicle-to-everything (C-V2X) is one of the emerging and promising techniques to support vehicular communications by enabling both safety-critical and non-safety services. C-V2X communications is a core solution to manage and advance future traffic safety and mobility. In this paper, we design a cellular-based vehicle-to-infrastructure (V2I) communications model for a Manhattan dense urban environment that has many roads deployed in the cell edge region, which results in severe co-channel interference (CCI). Thus, we aim to utilize two cooperative interference management schemes such as dynamic inter-cell interference coordination (ICIC) and coordinated multipoint (CoMP) to mitigate interference and to improve communication reliability. We evaluate the performance of the interference management schemes based on various performance indexes, such as vehicle UE average throughput, vehicle UE received interference, and vehicle UE outage probability. By effectively implementing the dynamic ICIC scheme, we achieve an immense reduction in CCI, which results in the improvement of user (UE) received signal quality. Moreover, we employ coordinated scheduling (CS) CoMP scheme to further mitigate the interference among cells. Finally, by implementing both dynamic ICIC and CS CoMP schemes simultaneously, a meaningful level of performance enhancement is achieved.

Generation-Load Coordinative Scheduling considering the Demand-Response Uncertainty of Inverter Air Conditioners

Inverter air conditioners (IACs) have gradually become the mainstream of resident air-conditioning equipment. Similar to traditional fixed-frequency air conditioners, IACs have the potential for demand response and load scheduling. However, the uncertainty of IACs is nonnegligible in generation-load scheduling. In this paper, the uncertain demand-response cost of IACs is studied for the first time. Meanwhile, based on the cost, a generation-load coordinative day-ahead scheduling model is proposed. In the scheduling, an IACs aggregator and traditional generators are coordinately dispatched to minimize the expected scheduling cost of the power system. The case study shows that the coordinative scheduling model can reduce the scheduling cost of the power system and encourage the IACs aggregator to improve their responsiveness or reduce their uncertainty, so as to improve the economy and reliability of power scheduling.

Two-stage stochastic scheduling approach for AC/DC hybrid distribution system with renewable energy integration

This paper proposes a stochastic scheduling approach for AC/DC hybrid distribution system considering the output uncertainty of wind and photovoltaic. The energy coordination problem has been formulated as a two-stage resource scheduling problem. The first-stage decision produces an hourly day-ahead pre-scheduling plan for the dispatchable distributed generators. For a set of possible scenarios over the next 24 h, the second stage determines the appropriate corrective decisions to handle the output uncertainty. Besides, the scheduling model for AC/DC hybrid system belongs to the non-convex optimization problem, which is transformed into a mixed integer second-order cone programming problem by second-order cone relaxation and linearization techniques. In this way, the optimization problem can be solved effectively. The proposed model has been tested on a modified IEEE 33 bus AC/DC hybrid system. Simulation results demonstrate that the proposed two-stage stochastic scheduling model can better cope with the renewable energy uncertainty and the active and reactive power coordination scheduling can ensure the safe operation of the entire system.

Toward a coordination of inventory and distribution schedules for blood in disasters

The need for efficient blood supply is of more significance in the event of disasters, when there is a lack of coordination between distribution and inventory management. The recent earthquake in Kermanshah province in Iran is among such cases that confirmed the need for coordinating such schedules. In this respect, a two-stage stochastic programming (SP) approach is presented for planning supply of blood after disasters that can assist in inventory decisions under hybrid uncertainty, minimizing the shortage and wastages. The uncertainty stems from imprecise parameters and scenario variability, and a robust-fuzzy-stochastic programming (RFSP) approach is devised to hedge against the uncertainty. The perishability of blood, the substitutability of blood groups, and the age-based characteristic of blood are taken into account to make the model more reliable. The compromise programming is applied to solve the multi-objective model. The results illustrate that the RFSP model can make a reasonable trade-off between mean value, feasibility robustness, and optimality robustness, which results in a robust and reliable solution under disastrous conditions.

Resilient Schedule Coordination for a Bus Transit Corridor

Providing convenient transit services at reasonable cost is important for transit agencies. Timed transfers that schedule vehicles from various routes to arrive at some transfer stations simultaneously (or nearly so) can significantly reduce wait times in transit networks, while stochastic passenger flows and complex operating environments may reduce this improvement. Although transit priority methods have been applied in some high-density cities, operating delays may cause priority failures. This paper proposes a resilient schedule coordination method for a bus transit corridor, which analyzes link travel time, passenger loading delay, and priority signal intersection delay. It maximizes resilience based on realistic passenger flow volume, whether or not transit priority is provided. The data accuracy and result validity are improved with automatically collected data from multiple bus routes in a corridor. The Yan’an Road transit corridor in Shanghai is used as a case study. The results show that the proposed method can increase the system resilience by balancing operation cost and passenger-based cost. It also provides a guideline for realistic bus schedule coordination.

Market-based coordination of integrated electricity and natural gas systems under uncertain supply

The interdependence between electricity and natural gas systems has lately increased due to the wide deployment of gas-fired power plants (GFPPs). Moreover, weather-driven renewables introduce uncertainty in the operation of the integrated energy system, increasing the need for operational flexibility. Recently proposed stochastic dispatch models optimally use the available flexibility and minimize the total expected system cost. However, these models are incompatible with the current sequential market design. We propose a novel method to optimally define the available natural gas volume for power production scheduling, anticipating the real-time flexibility needs. This volume-based model is formulated as a stochastic bilevel program that aims to enhance the inter-temporal coordination of scheduling and balancing operations, while remaining compatible with the sequential clearing of day-ahead and real-time markets. The proposed model accounts for the inherent flexibility of the natural gas system via the proper modeling of linepack capabilities and reduces the total expected system cost by the optimal definition of natural gas volume availability for GFPPs at the forward phase. The volume-based coordination model is compared with a price-based coordination alternative, which was recently proposed. In the latter one, the natural gas price perceived by GFPPs is similarly adjusted to enhance the temporal coordination of scheduling and balancing stages. This comparison enables us to highlight the main properties and differences between the two coordination mechanisms.

Coordination Scheduling of Wind-Hydropower Generation and Profit Allocation Based on Shapley Value Method

The volatility of wind makes the forecasting of wind speed unreliable. The inaccurate forecast in wind speed always leads to generation imbalance and causes Wind Generating Companies’ (WGenCOs) losses in the intrahour market. In contrast to wind power, Hydrogenerating Companies (HGenCOs) can utilize the reservoir volume to settle the fluctuation of water inflow easily. When treated as a specialized Spinning Reserve (SR) unit for wind power, hydropower can help to settle the generation imbalance and obtain more profit in the power market for both power plants. In this paper, the author establishes a coordination scheduling model of wind-hydro alliance which covers the day-ahead market and the intrahour market. First, to evaluate the deviation of the wind-hydro generation in the intrahour market, an imbalance charge rule considering each period of schedule horizon is constructed. Second, the author introduces two parameters to control the resources that hydropower can use to coordinate with wind power. Finally, the author introduces the Shapley value method to allocate the profit of the alliance which comprises several independent entities fairly. For the simulation of uncertainties, the scenario-based approach is used to simulate the water inflow of a reservoir considering the Monte Carlo (MC) method. The wind speed for the intrahour market is forecasted with the Autoregressive Integrated Moving Average (ARIMA) model. Simulations are implemented, and the results show that when treated as an SR unit for wind power, hydropower can diminish the imbalance charges significantly and will improve the revenue of the wind-hydro alliance. Furthermore, the coordination operation also helps reduce the spillage of the reservoir and the curtailment of the wind power to achieve better utilization of renewable energy.