Multiperiod heating storage control for distributed electric heating considering wind curtailment accommodation

Electric heating is perceived as an effective way to tackle heavy wind curtailment and severe smog in northern China, wherein distributed electric heating (DEH) accounts for a significant proportion. However, more research is required with regard to its thermal characteristic. This paper presents the multiperiod heating storage control for a DEH load to reduce wind curtailment. To cope with intermittent wind power, a novel multi-objective and layered optimization method is proposed by decomposing the integrated electricity and heating optimization problem into the electricity optimization subproblem and the heating optimization subproblem. Additionally, the influence of solar radiation on the thermal characteristic of the DEH load is considered in the building thermal process model when creating the day-ahead schedule of the DEH load control, and this is also regarded as the basis for grouping DEH users. Last, the simulation and economic feasibility analysis based on the data measured by the DEH system of Jilin Province, China, are carried out. The results show that this proposal can reduce the electricity cost for DEH users by 25%, and the critical feasible price for curtailed wind power is varying between 86.1 and 115.3 yuan/MWh according to different subsidy methods.     

Assessing wind uncertainty impact on short term operation scheduling of coordinated energy storage systems and thermal units

Renewable resources, especially wind power, are widely integrated into the power systems nowadays. Managing uncertainty of the large scale wind power is often known as one of the most challenging issues in the power system operation scheduling. Additionally, energy storage systems (ESSs) have been widely investigated in the power systems owing to their valuable applications, especially renewable energy smoothing and time shift. In this paper, a stochastic unit commitment (UC) model is proposed to assess the impact of the wind uncertainty impact on ESSs and thermal units schedule in UC problem. Wind uncertainty is modeled based on the two measures. First, the wind penetration level is changed with respect to the basic level. Second, the wind forecasting error is modeled through a normal probability distribution function with different variances. The ESSs are modeled based on several technical characteristics and optimally scheduled considering different levels of the wind penetration and forecasting accuracies. The proposed formulation is a stochastic mixed integer linear programming (SMILP) and solved using GAMS software. Simulation results demonstrate that the wind uncertainty have a considerable impact on operation cost and ESSs schedule while proposed optimum storage scheduling through the stochastic programming will reduce the daily operational cost considerably.     

基于帝国竞争算法考虑运行风险的电力系统随机无功备用优化

针对目前电力系统中的随机无功备用优化不能控制系统总无功备用风险,从而导致对系统的安全水平评估不准确的问题,首先建立考虑目标函数置信水平的随机无功备用优化模型,采用Nataf变换重构生成风速样本,然后采用蒙特卡洛法将原问题转化为多次的确定型优化运算,最后采用帝国竞争算法对问题进行求解。算例分析结果表明,相比于传统基于期望值目标函数的随机无功备用优化,所提方法可有效控制目标函数的风险;其中帝国竞争算法的采用是该算法效率提升的关键因素。     

考虑供热系统热储能特性的电-热综合系统随机优化调度模型研究

热电联产机组、热泵等装置的应用促进了电-热综合系统间的耦合关系,为风电的消纳提供了新途径。文章考虑了供热系统热储能动态特性,采用多场景法模拟风电出力不确定性,搭建了电-热综合能源系统随机优化调度模型。首先,针对供热管道传输时延动态特性,研究分析了其储热能力;其次,以电-热综合能源系统购能费用最低为目标函数,以热网约束、电网约束为约束条件,提出了综合系统能量最优化调度方案;最后,在IEEE33节点和6节点热网上进行算例分析,验证了模型的有效性。     

计及风光不确定性的新能源虚拟电厂多时间尺度优化调度

针对中国西北地区新能源消纳问题,该文聚合风力发电、光伏发电、光热电站、电储能装置组成虚拟电厂（VPP）,提出一种基于鲁棒随机优化理论的新能源虚拟电厂多时间尺度优化调度策略。首先对风力发电、光伏发电、光热电站与电储能装置进行数学描述,在此基础上建立VPP多时间尺度优化调度模型。在日前调度层中,以VPP运行效益最大为目标,依据风光日前预测出力建立日前优化调度模型;在时前调度层中,以VPP运行成本最小为目标,根据风光时前预测出力建立时前调度修正模型。同时,为了衡量风电、光伏发电出力不确定性对系统的运行影响,建立VPP随机优化调度模型。仿真结果验证该模型可提高运行效益与新能源消纳能力。     

A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems

The power management strategy (PMS) plays an important role in the optimum design and efficient utilization of hybrid energy systems. The power available from hybrid systems and the overall lifetime of system components are highly affected by PMS. This paper presents a novel method for the determination of the optimum PMS of hybrid energy systems including various generators and storage units. The PMS optimization is integrated with the sizing procedure of the hybrid system. The method is tested on a system with several widely used generators in off-grid systems, including wind turbines, PV panels, fuel cells, electrolyzers, hydrogen tanks, batteries, and diesel generators. The aim of the optimization problem is to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES). These uncertainties are modeled by using various possible scenarios for wind speed and solar irradiation based on Weibull and Beta probability distribution functions (PDF), respectively. The differential evolution algorithm (DEA) accompanied with fuzzy technique is used to handle the mixed-integer nonlinear multi-objective optimization problem. The optimum solution, including design parameters of system components and the monthly PMS parameters adapting climatic changes during a year, are obtained. Considering operating limitations of system devices, the parameters characterize the priority and share of each storage component for serving the deficit energy or storing surplus energy both resulted from the mismatch of power between load and generation. In order to have efficient power exploitation from RES, the optimum monthly tilt angles of PV panels and the optimum tower height for wind turbines are calculated. Numerical results are compared with the results of optimal sizing assuming pre-defined PMS without using the proposed power management optimization method. The comparative results present the efficacy and capability of the proposed method for hybrid energy systems.     

基于风-光-蓄-火联合发电系统的多目标优化调度

针对风电、光伏出力的随机性、间歇性和波动性而导致其在大规模接入电网时对电网发电计划制定和调度产生的影响,提出了含风-光-蓄-火联合发电系统的多目标优化调度模型。利用抽水蓄能的抽蓄特性,将风电和光伏出力进行时空平移,使风-光-蓄联合出力转变为稳定可调度电源,具备削峰填谷的功能,与火电机组共同参与系统优化调度。以风-光-蓄联合出力最大、广义负荷波动最小和火电机组运行成本最小作为目标函数,建立多目标优化调度模型,通过多目标处理策略,使目标函数简化为2个,以降低问题维数;在求解阶段,利用分层求解思想,将模型划分为两层,分别采用混合整数规划方法和机组组合优化方法进行求解。10机测试系统仿真结果表明：所建模型可以提高风能和太阳能的利用率,缓解火电机组的调峰压力,大幅降低风电反调峰特性对电网的影响,从而保证电力系统安全、稳定、经济运行。     

A new self-scheduling strategy for integrated operation of wind and pumped-storage power plants in power markets

Competitive structure of power markets causes various challenges for wind resources to participate in these markets. Indeed, production uncertainty is the main cause of their low income. Thus, they are usually supported by system operators, which is in contrast with the competitive paradigm of power markets. In this paper, a new strategy for increasing the profits of wind resources is proposed. In the suggested strategy, a Generation Company (GenCo), who owns both wind and pumped-storage plants, self-schedules the integrated operation of them regarding the uncertainty of wind power generation. For presenting an integrated self-schedule and obtaining a real added value of the strategy, participation of the GenCo in energy and ancillary service markets is modeled. The self-scheduling strategy is based on stochastic programming techniques. Outputs of the problem include generation offers in day-ahead energy market and ancillary service markets, including spinning and regulation reserve markets. A Neural Network (NN) based technique is used for modeling the uncertainty of wind power production. The proposed strategy is tested on a real wind farm in mainland, Spain. Moreover, added value of the strategy is presented in different conditions of the market.     

Market-based congestion management in electric power systems with increased share of natural gas dependent power plants

The paper addresses market-based congestion management (MBCM) in electric power systems taking into account the constraints of the electric power system (EPS) and the natural gas system (NGS). The proposed method is based on the countertrade methodology, where the system operator performs minimum-cost redispatching according to bids from generators and loads. The EPS is presented by the DC model for power flow calculation, which uses power transfer distribution factors (PTDFs) to describe the relation between generators/loads and line-power flows. The proposed solution applies the Benders decomposition method to decouple the problem into a master problem and subproblem. The master problem includes the bid-based redispatching for congestion relief and the EPS feasibility check. The subproblem checks the NGS operation feasibility when gas-fired generating units are redispatched in the master problem. Any NGS violations from the subproblem are incorporated into the master problem as power constraints for the next iteration of congestion management. The master problem is solved by linear programming. The NGS is presented in a nonlinear model and its feasibility check is performed using successive linear programming. Case studies illustrate the applicability of the proposed congestion management method on simple test models of the EPS and the NGS.     

Environmental/economic power dispatch with wind power

Economic environmental dispatch (EED) is a significant optimization problem in electric power system. With more wide spread use of wind power, it is necessary to include wind energy conversion system (WECS) in the EED problem. This paper presents a model to solve the EED problem incorporating wind power. In addition to the classic EED factors, the factors accounting for overestimation and underestimation of available wind power in both economic and environmental aspects are also considered. In order to obtain some quantitative results, the uncertain characteristic of available wind power and the performance of WECS are determined on the basis of the statistical characteristic of wind speed. The optimization problem is numerically solved by a scenario involving two conventional generators and two wind-powered generators. The results demonstrate that the allocation of system generation capacity may be influenced by multipliers related to the cost for overestimation and underestimation of available wind power, and by the multiplier related to the emissions for underestimation of available wind power. Nevertheless, the multiplier related to the emissions for overestimation of available wind power has little impact on the allocation. Taking account of economic factors, environmental factors and impacts of wind power penetration, the proposed EED model is beneficial to finding the right balance between radical and conservative strategy for wind power development.     

Optimum design and operation under uncertainty of power systems using renewable energy sources and hydrogen storage

The presented work addresses the design and optimization under uncertainty of power generation systems using renewable energy sources and hydrogen storage. A systematic design approach is proposed that enables the simultaneous consideration of synergies developed among numerous sub-systems within an integrated power generation system and the uncertainty involved in the system operation. The Stochastic Annealing optimization algorithm is utilized to handle the increased combinatorial complexity and to enable the consideration of different types of uncertainty in the performed optimization. A parallel adaptation of this algorithm is proposed to address the associated computational requirements through execution in a Grid computing environment. The proposed developments are implemented in a system that consists of photovoltaic panels, wind generators, accumulators, an electrolyzer, storage tanks, a compressor, a fuel cell and a diesel generator. Numerous design and operating parameters are considered as decision variables, while uncertain parameters are associated with weather fluctuations and operating efficiency of the employed sub-systems. The obtained results indicate robust performance under realizable system designs, in response to external or internal operating variations.     

含风电场的电力系统经济——排放多目标调度

从火电机组燃料成本和污染物排放两方面入手,构建了含风电场的电力系统发电调度运营管理多目标优化模型。引入了一种新的概率分布模型——截断多用途分布模型(TVD)来表征风电场,并简化风电的不确定性,同时引入基于TVD的可调节置信区间(ACI)风电场成本函数模型及一种基于列维飞行及解决非凸问题的改进型闪电算法(ILFA),可在随机多目标框架中有效地解决经济—排放调度(EED)问题。最后,通过算例与其他经典分布模型进行对比分析,结果表明所提模型可更准确地反映风电情况,该算法在平衡经济成本和污染物排放方面有效。     

Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method

In this paper, wind power generators are being incorporated in the multiobjective economic emission dispatch problem which minimizes wind-thermal electrical energy cost and emissions produced by fossil-fueled power plants, simultaneously. Large integration of wind energy sources necessitates an efficient model to cope with uncertainty arising from random wind variation. Hence, a multiobjective stochastic search algorithm based on 2m point estimated method is implemented to analyze the probabilistic wind-thermal economic emission dispatch problem considering both overestimation and underestimation of available wind power. 2m point estimated method handles the system uncertainties and renders the probability density function of desired variables efficiently. Moreover, a new population-based optimization algorithm called modified teaching-learning algorithm is proposed to determine the set of non-dominated optimal solutions. During the simulation, the set of non-dominated solutions are kept in an external memory (repository). Also, a fuzzy-based clustering technique is implemented to control the size of the repository. In order to select the best compromise solution from the repository, a niching mechanism is utilized such that the population will move toward a smaller search space in the Pareto-optimal front. In order to show the efficiency and feasibility of the proposed framework, three different test systems are represented as case studies.     

Hydro-thermal-wind scheduling employing novel ant lion optimization technique with composite ranking index

A solution to the combined hydro-thermal-wind scheduling problem of multi reservoir cascaded hydro plants is presented employing a novel ant lion optimization (ALO) algorithm. Five objectives, cost, various emissions and power loss, are simultaneously optimized. The optimal schedules of thermal, hydro and wind power (WP) units are determined for continuously varying load subject to a large number of practical operational constraints. The effect of reserve and penalty coefficients and WP uncertainty is also investigated for the multi-objective (MO) problem. The newly proposed ALO algorithm has unique features like random walk, roulette wheel, and boundary shrinking. These operations provide a judicious balance between exploration and exploitation, and create a powerful optimization technique for complex real-world problems.Finding the best compromise solution (BCS) is a tedious task when multiple objectives are involved. A composite ranking index (CRI) is proposed as a performance metrics for MO problems. The CRI helps the decision maker in ranking the large number of Pareto-optimal solutions. The developed model is tested on three standard systems, having a mix of hydro, thermal and wind generators. The performance is found to be superior to published results and comparable with established algorithms like artificial bee colony (ABC) and differential evolution (DE).     

高水电比重系统随机电力电量平衡模型与算法

针对高水电比重系统中电力电量平衡问题,首先考虑利用典型周负荷曲线进行电力电量平衡分析,以更好地计及工作日和非工作日不同的负荷曲线对可调水电站库容及火电站开机的影响。为恰当考虑风电场和光伏电站出力的不确定性和波动性,建立了基于随机优化的随机电力电量平衡模型,从概率的角度更好地分析和衡量风光电站对电量平衡的贡献。为方便该模型的求解,对非线性的水电转换函数进行线性化处理,得到混合整数规划模型,采用CPLEX对模型进行求解。以某高水电比重系统作为算例进行仿真分析,验证了所提随机电力电量平衡模型与算法的正确性和有效性,从概率的角度定量分析了风光电站的电量贡献。     

A stochastic framework for clearing of reactive power market

This paper presents a new stochastic framework for clearing of day-ahead reactive power market. The uncertainty of generating units in the form of system contingencies are considered in the reactive power market-clearing procedure by the stochastic model in two steps. The Monte-Carlo Simulation (MCS) is first used to generate random scenarios. Then, in the second step, the stochastic market-clearing procedure is implemented as a series of deterministic optimization problems (scenarios) including non-contingent scenario and different post-contingency states. In each of these deterministic optimization problems, the objective function is total payment function (TPF) of generators which refers to the payment paid to the generators for their reactive power compensation. The effectiveness of the proposed model is examined based on the IEEE 24-bus Reliability Test System (IEEE 24-bus RTS).     

考虑电转气消纳风电的电-气综合能源系统两阶段鲁棒协同调度

针对传统随机规划方法和区间优化方法处理风电出力不确定性的不足之处,该文提出含电转气设备的电力-天然气综合能源系统两阶段鲁棒协同调度模型,并考虑天然气网络运行约束对燃气轮机和电转气设备调度出力及备用配置的影响。模型以风电基准场景下系统的日前调度运行成本及最劣风电场景下实时调度成本之和为目标函数,建立具max-min结构的双层优化模型,并在主/子问题求解框架下采用列约束生成（C&CG）方法进行求解。最后,在Matlab平台下构建仿真算例验证所提鲁棒协同调度模型的有效性。     

基于负荷侧响应的含储热热电联产的风电消纳模型

为了有效减少弃风,提高风电消纳能力,该文从负荷侧出发,通过峰谷分时电价策略引导用户的用电方式,达到削峰填谷,优化负荷曲线的目的。同时,在传统热电联产机组中应用大容量储热装置,通过对储热环节的控制,解耦“以热定电”约束,提高系统调节能力。以系统煤耗量最低为目标,构建包含储热的热电联产机组与风电联合出力优化调度模型。该模型考虑系统中的含储热热电联产机组运行成本,同时兼顾储热、负荷侧响应与热电平衡的相关约束等因素,采用基于模拟退火的粒子群算法对模型进行求解,并利用算例比较不同模式下的结果,验证了模型的有效性。     

Bidding strategy of wind-thermal energy producers

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.     

市场环境下基于合作博弈的风-水-火电厂收益分配研究

随着电力系统的市场化发展,发电侧各电厂企业在保证区域电能供需平衡的前提下期望用合作的方式来获取更多收益并对其进行有效分配。通过非合作博弈的方式给出风、水、火区域电网常规的调度方式,并计算出风、水、火电厂的收益;以市场环境下各主体的趋利性作为出发点引入合作博弈思想,使风、水、火电厂3个参与者构成一个－联盟,保证有功功率供应的基础上,给予单位电量收益更多的水电、风电更多发电指标,并提出一种偏差MDP指标分配方式,分析表明Shapley值法及偏差MDP指标法处于核心中。同时,与非合作博弈条件下风、水、火电厂的收入相比,偏差MDP分配方式下各电厂收入分别提高了38.2%、20.5%、6.1%。