Long-term Optimal Operation Research Articles

Medium- and long-term optimal operation of a hybrid energy system enhanced by cascade hydropower energy storage system

To address the grid connection challenges derived from the high penetration of intermittent new energy sources, some generation companies are trying to use existing cascade hydropower stations to develop “large-scale cascade hydropower energy storage systems” (LCHES). They intend to combine the LCHES with new energy power to become a new type of hybrid power system (the LCHES-WP hybrid power system). For such an emerging hybrid power system, performance in the medium- and long-term operation is more worthy of attention. Therefore, we propose “monthly LCHES-WP operation strategy” and “short-term dispatch strategy for LCHES” to constrain the operation of the LCHES-WP hybrid power system. On this basis, a multiple time-scales nested optimizing model is presented to estimate the performance in the medium- and long-term operation. A case study in the Yellow River Basin in China was presented based on the baseline scenario (1800 MW of hydroturbine, 1200 MW of pump, 2000 MW of new energy, and 0.24 billion m3 of regulating storage capacity). It reveals that (1) the LCHES-WP hybrid power system can achieve a consistent output process every day during a month with low energy curtailment and low energy supply shortage, which indicates that it can meet satisfactory performance in medium to long-term operation. (2) it will significantly increase energy curtailment (controlling the energy supply shortage is as low as the baseline scenario) without the pumping system or sufficient regulating storage capacity. (3) based on sensitivity analysis, it is indicated that the capacity of new energy can further improve to 5000 ∼ 6000 MW. The simulation framework and the result provided in this paper can be referred to by the same research.

Microplastics transfer from a malfunctioning municipal wastewater oxidation pond into a marine protected area in the Colombian Caribbean

Wastewater is an important source of microplastics (MPs) in aquatic ecosystems, threatening their biodiversity and environmental services. This study examines the contribution of MPs from the effluents of a municipal wastewater treatment pond system (WTS) to a stream that flows into the Cispata marine protected area (MPA) in the Colombian Caribbean. Samples of influent and effluent wastewater and sludge in the WTS were analyzed to determine the abundance and types of MPs. Additionally, the wastewater flow rate was measured using a volumetric method, and its MP load calculated. The abundance of MPs in the influent and effluent of the WTS was 15 and 5 items L–1 of wastewater, and 11 and 4 items Kg–1 dw of sludge, respectively. Fibers (67–75%) prevailed in the wastewater, while fragments (56–67%) were predominant in the sludge. Whereas the removal of MPs entering the WTS was 67%, the wastewater effluents still contribute approximately 1.3 million items day–1 to the stream flowing into the MPA. Our study highlights that a poorly functioning WTS causes substantial MP discharges into sensitive aquatic coastal ecosystems. These WTS require ongoing maintenance and improvements to ensure their long-term optimal operation and function of reducing pollutant loads and environmental risks in recipient aquatic ecosystems.

基于鸟群算法的梯级水库群长期优化调度研究

基于鸟群算法的梯级水库群长期优化调度研究

Long-Term Optimal Dispatching of Hydropower Station Based on Controlling the Frequency of Reservoir Level Fluctuation

In this paper, a method for long-term optimal operation of hydropower station is proposed to control the frequency of reservoir level fluctuation. We introduce the integer variable which describes the rise and fall of the reservoir level, the number of changes, and the state transition equation for the change of the reservoir level fluctuation into the dynamic programming method. This method can obtain the global optimal solution under the control of different numbers of reservoir level rise and fall, thus improving the controllability and practicability of optimal operating results. We consider the maximum number of water level fluctuations as a constraint condition while the reservoir level, the state of fluctuation, and the number of state changes that have occurred as the three state variables to construct a dynamic programming model. Three state transition equations are the water balance, the state of the reservoir level rise and fall, and the number of fluctuations. Besides, the penalty function is used to handle minimum output and surplus water. We solve this model by using a dynamic programming reverse recursion equation. The application of this method in the Manwan Hydropower Station shows that it can effectively solve the frequent water level fluctuation problem that is generally inconsistent with the actual situation in the long-term optimal dispatch scheme of hydropower stations and improve the practicability of the optimal dispatch results.

Long-term stochastic model predictive control and efficiency assessment for hydro-wind-solar renewable energy supply system

It is popular to combine the hydropower plant with the wind and solar power plants to supply electricity, and the joint is termed as the hydro-wind-solar renewable energy supply system (RESS). The long-term optimal operation of the RESS is a challenging task, due to the nature of different spatial and temporal variabilities associated with renewable energy resources, and the significant operation uncertainties due to the changing natural environment. To address the task, the stochastic model predictive control (MPC), based on probabilistic forecasting and rolling stochastic optimization, is designed and implemented for the long-term operations of the RESSs in Yunnan province, China. The paper tests out the system efficiencies for different penetration levels of wind and solar power, and finds out that (1) the Long Short-Term Memory performs best among candidate point prediction algorithms; (2) the stochastic MPC considering the correlations among renewable resources helps the RESS operate with a higher efficiency; (3) the large-scale hydropower plant has great potential to offset the effects of seasonal uncertainties and demand-generation mismatch, but cannot completely avoid the electricity shortage enabled by unexpected scenarios of renewable resources.

Research on Reservoir Optimal Operation Based on Long-Term and Mid-Long-Term Nested Models

In order to solve the problem that the existing optimal operation model of reservoirs cannot coordinate the contradiction between long-term and short-term benefits, the paper nested the long-term optimal operation and mid-long-term optimal operations of reservoirs and established the multi-objective optimal operation nested model of reservoirs. At the same time, based on this model, the optimal control mode is determined when there are errors in the predicted runoff. In the optimal scheduling nested model, the dynamic programming algorithm is used to determine the long-term optimal scheduling solution, and the genetic algorithm is used to solve the mid-long-term optimal scheduling. The optimal control mode is determined by three indicators: power generation benefit, water level over limit risk rate and the not-exploited water volume. The results show that, on the premise of meeting the flood control objectives, the nested model optimal dispatching plan has higher benefits than the long-term optimal dispatching plan and the actual dispatching plan, which verifies the superiority of the nested model in the reservoir optimal dispatching problem. When there is error in predicting runoff, among the water level control mode, flow control mode and output control mode, the average power generation benefit of output control mode is 150.05 GW·h, the low-risk rate of water level overrun is 0.29, and the not-exploited water volume is 39,270 m3. Compared with the water level control mode and the flow control mode, the output control mode has the advantages of higher power generation efficiency, lower water level over limit risk rate and less not-exploited water volume. Therefore, from the perspective of economic benefit and risk balance, the output control mode in the optimization scheduling nested mode is the optimal control mode.

Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin

Study regionReservoir system on the Upper Yellow River Basin (UYRB), China. Study focusA multipurpose reservoir system with multi-year regulation capacity calls for new optimization with high efficiency owing to the curse of dimensionality. This paper presents a state-of-the-art large-scale multi-objective evolutionary algorithm (LSMOEA), called the weight optimization framework (WOF) with Non-dominated Sorting Genetic Algorithm II (NSGAII) optimizer, to alleviate the problem, and improve its performance by determining applicable grouping mechanism based on inflow features. A novel constrains handle method named dual progressive repair is used to ensure search progress in feasible decision space. New hydrological insights for the regionCompared to classic NSGA2, WOF with NSGA2 optimizer (WOF-NSGA2 herein) shows better performance on diversity, convergence, and convergence rate. The tuning method, along with the repair method, makes WOF-NSGA2 outperform in all parameter combinations, and produces satisfying operation schedule in the case of multi-objective reservoir operation in the UYRB. The tuning and repair method could be used widely for the large-scale multi-objective reservoir system operation.

A long-term intelligent operation and management model of cascade hydropower stations based on chance constrained programming under multi-market coupling

Under the medium- and long-term electric markets, cascaded hydropower stations face a series of practical challenges due to the uncertainty of inflow and market price. For long-term dispatch scheduling, the allocation of power generation in multimarkets is critical, including clean energy priority consumption market, inter provincial market and intra provincial market in order to maximize the operator’s expected revenue and reduce the market operation risks. Based on the hydro-dominant electricity market structure and settlement rules, we propose a long-term optimal operation method for cascade hydropower stations considering the uncertainty of multiple variables. First, a seasonal autoregressive integrated moving average model is used to handle the time-varying and seasonal characteristics of inflow series by using a copula connect function to fit the joint distribution of the monthly inflow, the clearing price of the intra provincial market and the delivery volume of the inter provincial market. Then, uncertain chance-constrained programming is established. Finally, a developed particle swarm optimization algorithm embedded in a Monte Carlo simulation is solved for hydropower operation policies, and the maximum revenue, resource allocation and scheduling strategy are obtained under the corresponding risk tolerance. Taking the actual data of cascaded hydropower stations in Yunnan Province, China, as an example, a simulation analysis is carried out. The results show that the proposed method can reasonably describe the uncertainty and correlation between the variables, realizing the optimal allocation of resources among multimarkets, and provide references for the long-term optimal operation of cascade hydropower stations in a multimarket environment. The results also show that the decision strategies should be determined considering the decision-maker’s risk preference.

An integrated framework for optimizing large hydro–photovoltaic hybrid energy systems: Capacity planning and operations management

Synchronous resolution of capacity planning and operations management sub-problems of large hybrid energy systems (HESs) may further enhance the synergy between different energy sources. However, these two sub-problems constitute a complex bi-level programming problem, which is difficult to effectively solve. In this study, we proposed an effective framework to synchronously determine the optimal photovoltaic (PV) size and long-term operating rules for large hydro–PV HESs. Firstly, a set of short-term operation models for each possible PV size were established to simulate joint operation processes of hydropower and PV power. Then, PV-energy loss functions were derived based on short-term simulation results and they were subsequently incorporated into long-term optimal operation models, aiming to maximize net energy production of the HES. Thirdly, long-term operating strategies were optimized by dynamic programing and sampled using a bootstrap method to generate inputs for a capacity planning model. Finally, the optimal PV size was determined by maximizing the net present value of the PV plant over its life-span, while operating rules were obtained using a regression analysis method. A case study was carried out using China’s Longyangxia hydro–PV HES. The results showed that: (1) the integrated framework could synchronously yield optimal PV size and operating rules for the HES without heavy computational burden; (2) the capacity planning model could provide an optimal PV size of 880 MW with a confidence interval of [820, 930] MW; and (3) the derived operating rules outperformed the conventional reservoir operating rule curves in terms of power generation and water supply performances. Therefore, the proposed framework can be an effective tool for the planning and management of large hydro–PV HESs.

Research on Optimal Operation of Reservoirs in Shule River Irrigation District Based on Dynamic Programming with Successive Approximation Method

Reservoir operation is an important means to realize optimal allocation of water resources. In order to reasonably distribute water resources in Shule River irrigation area and improve the utilization rate of water resources, according to the actual situation of Shule River irrigation area, taking the minimum annual water shortage and the highest irrigation guarantee rate of the whole irrigation area as the objective function, the deterministic long-term optimal operation model of reservoir group in the irrigation area is established, and the successive approximation dynamic programming ( DPSA ) is used to solve the problem, so as to realize the joint operation of Changma Reservoir, Shuangta Reservoir and Chijinxia Reservoir, and provide the basis and reference for the comprehensive management and scientific allocation of water resources in Shule River basin.

Hybrid Time-Scale Optimal Scheduling Considering Multi-Energy Complementary Characteristic

Evaluating the potential utilization of hybrid energy systems and determining the multi-scale optimal operation strategy is critical to power system planning in the context of energy structure adjustment, especially for large-scale hybrid energy systems. Considering the long-term and short-term complementary characteristics, this paper puts forward a coordinated optimization framework for the integrated energy system in the world's largest multi-energy complementary base on Yellow River's upper reaches. The main procedures are as follows: 1) cross-correlation method is introduced for individually analyzing the long- and short-term complementary characteristics of wind power, photovoltaic, and hydropower in this multi-energy complementary base; 2) a double-layer model combining the long-term optimal operation model and short-term optimal operation model for determining the proportion of multiple energy and optimizing the maximum peak-shaving ability; 3) Large-Scale System Decomposition-Coordination Method is applied for solving the proposed double-layer operation model. The results show that wind power 23%, photovoltaic 35%, hydropower 42% can keep the most stable generation in the long-term complementary operation. This proportion results can improve the system peak regulation capacity with 50.8% (sunny day's morning peak) and 24.2% (rainy day's morning peak) in the optimal short-term operation.

Long-term optimal operation of cascade hydropower stations based on the utility function of the carryover potential energy

Challenge remains to find the optimal carryover storage to balance the immediate and carryover utilities for long-term hydropower reservoir operation due to low forecast accuracy, limited foresight, and complex hydrologic, hydraulic and electric connections between cascade hydropower reservoirs. Thus, this paper proposes a long-term optimal operation model to dynamically control the optimal carryover storages for cascade hydropower reservoirs. First, the carryover utility of cascade hydropower stations is expressed as a function of the carryover potential energy rather than the carryover storage, thus decreasing the function parameters and using the limited prior knowledge. Then, the utility function of the carryover potential energy (UFCPE) is fitted by a quadratic function based on a successive iteration method, based on which a two-stage optimal operation model (TSOOM) is developed to guide the long-term optimal operation of cascade hydropower stations. The case study with five cascade hydropower stations in the Yalong River Basin shows that: 1) UFCPE can be well fitted by a quadratic function, and it increases linearly in the dry season, but monotonically at a decreasing rate in the flood season resulting from a large quantity of surplus water; and 2) The performance of UFCPE-based TSOOM is much superior to those of conventional rules and conventional optimization methods and quite close to that of dynamic programming successive approximation in guiding the long-term cascade hydropower reservoirs operation.

Optimal operation of independent regional power grid with multiple wind-solar-hydro-battery power

In an independent regional power grid, the optimal coordination of renewable energy resources such as wind and solar becomes the key to making full use of the energy storage capacity of hydropower. In this paper, a medium to long-term optimal operation strategy is proposed for IRPG in the dry season based on the statistical characteristics of wind-solar power and the long-term plan of hydropower. The objective of the work is to minimize the difference between the monthly water consumption of hydropower stations and the predicted, considering the constraints of water flow and daily average battery energy storage fluctuation. Because of the pessimistic attitude of dispatchers to forecasting results, a correction coefficient is used to modify forecasting outputs. Finally, simulation results show the advantages of the proposed optimal strategy over the strategy without optimal operation in ensuring the water level of reservoir, improving the generation efficiency of hydropower, and avoiding the risk of no water to power generation in hydropower stations at the end of dry season.

Long-term versus Real-time Optimal Operation for Gate Regulation during Flood in Urban Drainage Systems

ABSTRACTIn this study, a simulation-optimization framework is built to present two approaches of long-term and real-time optimal operation for the regulation of gates during flood in urban drainage systems (UDSs). The modeling approaches are applied to a prototype network in a portion of the UDS of Tehran, Iran. A sensitivity analysis is conducted to determine the number of decision variables of the optimization models. Results are then compared with those of an uncontrolled (UC) approach as a baseline business-as-usual scenario. It has been inferred that the two optimization approaches outperform the UC method. Additionally, the real-time optimal (RTOP) operation approach, benefiting from both the current system’s state and the latest storm data, is superior to the long-term optimal (LTOP) operation approach with respect to flood mitigation efficiency. The RTOP approach has the flexibility to adapt to changes in operational conditions when part of the system’s regulation capacity is lost.

Establishment and evaluation of operation function model for cascade hydropower station

Toward solving the actual operation problems of cascade hydropower stations under hydrologic uncertainty, this paper presents the process of extraction of statistical characteristics from long-term optimal cascade operation, and proposes a monthly operation function algorithm for the actual operation of cascade hydropower stations through the identification, processing, and screening of available information during long-term optimal operation. Applying the operation function to the cascade hydropower stations on the Jinshajiang-Yangtze River system, the modeled long-term electric generation is shown to have high precision and provide benefits. Through comparison with optimal operation, the simulation results show that the operation function proposed retains the characteristics of optimal operation. Also, the inadequacies and attribution of the algorithm are discussed based on case study, providing decision support and reference information for research on large-scale cascade operation work.

Function-based scheduling method on initial identified water level of reservoir long-term optimal scheduling

In this paper, a function-based scheduling method combining with statistical analysis of historical runoff data and inflow data is proposed to calculate the initial water level of a reservoir under long-term optimal operation. Two-ary interpolation function and database searching are integrated in the solving process. An example is taken to demonstrate the feasibility and engineering practicability of this method. Initial water level obtained by this method establishes a foundation for making optimal scheduling plans.

A hybrid nonlinear optimization method for operation of large-scale cascaded hydropower plants

This paper develops a hybrid nonlinear optimization method for solving long-term optimal operation of large-scale cascaded hydropower plants with complex spatial coupling constraints. This method proposes conversion factors relevant to generation and discharge in order to cope with complex nonlinear total generation limitation considered in the optimization problem. Thus, the original nonlinear optimization problem can be broken down into a sequence of standard quadratic programming sub-problems. A combination of progressive optimality algorithm (POA) and quadratic programming (QP) method is employed to optimize the operation of hydropower systems. The results obtained from POA are first chosen as the initial solution of QP, which also decide the feasible decision space. During the solution process, the previous conversion factors are dynamically updated depending on the destroying range of total generation limitation. The boundary values of these constraints are accordingly modified in the new QP model. Solving the QP problem and updating the convention factors are performed alternately until the optimal solution or satisfactory solution for original problem is obtained. The proposed hybrid nonlinear method is applied to scheduling Hongshui River cascaded hydropower plants. The simulation results show that our method can enhance the total power generation in dry season and produce more energy than POA.

A Two-Stage Approach for Large-Scale Cascaded Hydropower System Operations

The paper presents a two-stage approach to cope with the long-term optimal operation of cascaded hydropower systems. This approach combines progressive optimality algorithm (POA) with quadratic programming (QP) to improve the optimization results. POA is used at the first stage to generate a local optimal result, which will be selected as the initial feasible solution of QP method employed at the second stage. Around the initial solution, a rational local search range for QP method is then determined, where the nonlinear water level function and tailrace level function can be linearized nearly with high accuracy. The simplified optimization problem is formulated as a QP model with a quadratic generation function and a linear set of constraints, and solved using the available mathematic optimization software package. Simulation is performed on the long term operation of Hongshui River hydropower system which is located in southwest China and consists of 9 built hydropower plants. Results obtained from the proposed approach show a significant increase in the total energy production compared to the results from POA.

Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid

This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.

生态流量约束下梯级水电站群补偿调度的模拟优化方法

针对梯级水电站水库群发电与生态流量调控的协调问题，提出了梯级水电站群不完全补偿优化调度方法。在以梯级蓄能作为总出力决策依据、以时段末梯级蓄能最大为出力分配准则的优化调度规则基础上，建立了以梯级水电站群多年平均发电量最大为目标、以各河段生态流量为约束的长期优化调度模型。结合模拟和逐次逼近优化算法进行调度规则的优化，并通过寻求各长期调节水库最小出库流量的最佳组合来满足关键河段的生态流量需求。澜沧江梯级的应用实例表明所提出的方法能够在保证梯级发电效益的基础上，满足生态流量调控要求，发挥水电站水库综合利用效益。 Given coordination problems between power generation and ecological flow regulation, a limited compensative operation method of cascade reservoirs was proposed. In this paper, total power generation of cascade reservoirs was decided by cascade storage energy. On the basis of maximizing cascade storage energy, a long-term optimal operation model was developed with maximizing energy production as the objective function and ecological flow as a constraint. The simulation-based optimization algorithm was adopted to optimize operation rules. And the ecological flow constraint was satisfied by regulating minimum release of each reservoir. The Lancang River cascade reservoirs were used as case study. Simulation results show that the proposed method can meet the requirements of ecological flow and maximize comprehensive benefits with reliable generation benefits.