考虑风电不确定性的电-气综合能源系统协调优化

风电不确定性与波动性是制约风电消纳的关键因素,传统优化方法在处理风电不确定性时存在诸多局限,电-气综合能源互补优化可提高风电利用率。基于此,建立了以电转气装置为耦合元件的综合能源调度模型,以常规机组运行成本、弃风惩罚成本等为系统优化目标。首先,通过数值天气预报方法对风速进行预测,建立预测误差累加状态转移矩阵,构建风场景马尔科夫链模型形成不确定合集;然后,通过拟合形成服从威布尔分布的风功率预测场景集,以引入扰动的改进型蝙蝠算法对模型进行求解。最后采用修改后的IEEE39节点算例验证了所提模型对风电消纳的经济性和实用性。     

考虑消纳风电的区域综合能源系统电转气与储能设备优化配置

电转气(PtG)技术与多类型储能设备相结合,可以大量增加可再生能源的就地消纳,减小系统弃风.针对区域内集成有电、气、热、冷多种能源的综合能源系统,首先对系统进行建模,具体介绍了电转气技术与多类型储能设备的工作原理.其次,以综合能源系统总年费用最低为目标,建立电转气与多类型储能设备的联合优化配置模型,并采用Big-M方法...     

基于合作博弈的综合能源系统电-热-气协同优化运行策略

在"双碳"背景下,为有效提高综合能源系统(IES)的能源利用率,减少碳排放量,同时提升系统运行的灵活性,提出一种基于合作博弈的IES优化运行模型.首先构建IES框架,针对电转气(P2G)、碳捕集、燃气轮机、热储能等设备进行建模;其次考虑系统内各主体之间存在协同合作的可能,将系统内各运营主体分为三方构建合作联盟,阐述能源...     

考虑电-气综合需求响应的综合能源系统低碳经济调度

随着“碳达峰”和“碳中和”目标的提出,低碳电力更加符合社会发展的需求。氢气具有清洁无污染、能量密度大等特点,合理利用氢能源为综合能源系统的发展提供了新的方向。基于此构建了含制氢-储氢设备的综合能源系统低碳经济调度模型,引入电-气综合需求响应并考虑碳排放惩罚成本,以系统总成本最优为目标函数,利用粒子群算法对实际算例进行分析求解。仿真结果表明通过引入综合需求响应和制氢-储氢设备,可提高可再生能源的消纳水平,降低系统的成本,减少系统的碳排放。     

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。     

考虑电转气与冷热负荷惯性的综合能源系统优化调度

风电、光伏等清洁能源发电具有反调峰特性和不确定性,容易造成弃风、弃光。为应对清洁能源消纳这一挑战,提出考虑电转气与冷热负荷惯性的综合能源系统优化调度模型。搭建电转气和冷热负荷惯性模型,并分析碳交易机制下电转气设备的工作特性以及冷热负荷惯性对其需求的影响,从而建立冷热负荷供需不等式约束条件;进一步建立考虑电转气与冷热负荷惯性的综合能源系统运行成本最小目标函数,以及相应的各机组与系统功率约束。通过YALMIP和GUROBI工具箱建立并求解最优调度模型,结果表明：所提方法能够提高清洁能源消纳能力,降低综合能源系统运行成本。     

考虑需求侧响应的园区综合能源系统优化配置

以园区综合能源系统(PIES)的优化配置为研究对象,考虑电力市场分时定价机制下的需求侧响应策略,以PIES的运行成本、污染排放和能耗为优化目标,建立主问题与子问题的迭代优化架构,最后采用多属性决策方法从待选方案中选出最优的系统配置。算例结果表明,可再生能源的接入可以有效地提高PIES的综合效益,引入价格型和替代型需求侧响应后可以进一步提升PIES的经济性,但同时降低了PIES的环保性。     

考虑零碳排放的电-气综合能源系统日前优化调度

基于碳捕集和电转气（P2G）技术，该文建立考虑零碳排放的电-气综合能源系统日前调度模型。首先，搭建零碳电-气综合能源系统框架，通过在燃煤机组上增设碳捕集装置收集燃煤机组产生的二氧化碳，并将其作为原料通过P2G技术将二氧化碳转换为甲烷，同时针对火电机组出力与产生甲烷量之间的数学关系进行深入研究。然后，以综合运行成本最低为目标建立日前调度模型，同时考虑电-气综合能源系统的零碳目标，将无法收集利用的二氧化碳通过购买碳排放权的方式排放到大气中，进而实现零碳的目标。最后，通过算例验证所提的零碳电-气综合能源系统的合理性，结果表明该文所提模型可实现电-气综合能源系统零碳排放的目标，且与传统电-气综合能源系统相比，减少弃风1320.96 MWh，降低运行成本56.16万元。     

考虑梯级碳交易机制和电转气两阶段运行的综合能源系统优化

为提升综合能源系统（integrated energy system,IES）的能效水平,提出了一种考虑梯级碳交易机制和电转气（power-to-gas,P2G）两阶段运行的IES调度模型。首先引入碳捕获与封存技术（carbon capture and storage,CCS）,解决了P2G所需碳源和热电联产机组的碳排放问题;同时在传统P2G的基础上引入氢燃料电池,研究P2G两阶段运行的多重效益;最后,运用梯级碳交易机制限制碳排放。在此基础上,建立以碳交易成本、系统运行成本、新能源利用率相关成本最小为目标的优化调度模型,利用IPOPT商业求解器进行求解,通过与其他传统模型对比分析,表明所提模型的经济性、低碳性和风光消纳能力较高。     

含电转气的电—气综合能源系统低碳经济调度策略

为优化用能效率和发展低碳电力,采用综合能源系统(IES)模式耦合电力网络和天然气网络,通过电转气(P2G)技术形成电—气—电能量闭环流动,提升电力与天然气网络间的强耦合性和IES整体供能稳定性。兼顾电—气综合能源系统的经济性与低碳性,引入碳排放机制构建IES低碳经济调度模型,首先详细阐述了IES模型架构、电转气技术、碳排放交易机制等基本理论,并对天然气网络进行建模,然后采用多场景法考虑风电出力波动,以经济成本和碳交易成本最小为优化目标,构建综合能源系统新型低碳经济优化调度模型,最后通过算例对比分析了4种不同调度方案,验证了所提模型的有效性和合理性。     

Energy station and distribution network collaborative planning of integrated energy system based on operation optimization and demand response

In the energy station and distribution network collaborative planning of integrated energy system (IES), it is difficult to consider station and network interaction in IES operation at the same time. For resolving this problem, the model and solution of planning and operation alternative optimization are proposed considering multiagent interest balance. First, the three-stage optimization framework and model of station and network planning of IES are proposed based on the operation scheduling of IES and the response of energy station and users as different subjects, aiming at optimization of station and network cost-effectiveness, respectively. Second, the distribution network simplification method is proposed based on topological equivalence principle. The topological structure characteristics of distribution network is analyzed, the rapid generation strategy of single tie line network based on broken circle method is proposed, and then an encoding/decoding scheme is proposed based on particle swarm optimization algorithm. Third, considering the load characteristics and energy station demand response based on flexible comfort level of users, a dynamic spot price optimization method and operation strategy of IES are proposed. And then the station and network collaborative planning solution is presented based on the operation optimization of IES. Finally, an example is given to verify the practicability and effectiveness of the proposed method in this paper.     

Decoupling optimization of integrated energy system based on energy quality character

Connections among multi-energy systems become increasingly closer with the extensive application of various energy equipment such as gas-fired power plants and electricity-driven gas compressor. Therefore, the integrated energy system has attracted much attention. This paper establishes a gas-electricity joint operation model, proposes a system evaluation index based on the energy quality character after considering the grade difference of the energy loss of the subsystem, and finds an optimal scheduling method for integrated energy systems. Besides, according to the typical load characteristics of commercial and residential users, the optimal scheduling analysis is applied to the integrated energy system composed of an IEEE 39 nodes power system and a 10 nodes natural gas system. The results prove the feasibility and effectiveness of the proposed method.     

Cross-regional integrated energy system scheduling optimization model considering conditional value at risk

Integrated energy system is a very important way to improve energy efficiency. Based on the combined heating cooling and power system, combined with energy storage equipment, a cross-regional integrated energy system scheduling optimization problem is studied. An integrated energy system scheduling optimization model is established that meets the requirements of electrical, heating, and cooling load under a variety of energy sources while both considering the interaction of electrical, heating, and cooling load between regions, and complementation of them within one region. Meanwhile, the value at risk (VaR) theory is introduced and the operating constraints of equipment in the integrated energy system fully considered, the integrated energy system scheduling model with VaR is established. The example shows that the model can realize multi-type electrical, heating, and cooling load optimized by schedule across regions under the premise of satisfying the balance of energy supply and demand, which can reduce the system operation cost. The sensitivity analysis of the minimum expected cost and the influencing factors of conditional VaR is carried out to verify the validity and feasibility of the proposed model.

• An integrated energy system scheduling optimization model is established that meets the requirements of electrical, heating, and cooling load under a variety of energy sources while both considering the interaction of electrical, heating, and cooling load between regions, and complementation of them within one region.
• By using the conditional value at risk theory to consider various types of the integrated energy system complements and evaluates the operational risk of the system under optimal operating conditions of the system.
• The total cost of system scheduling operation is proportional to the storage capacity, which is inversely proportional to the heat storage capacity and inversely proportional to the pipeline capacity within a certain interval.

     

Modeling and daily operation optimization of a distributed energy system considering economic and energy aspects

This paper presents a distributed energy system (DES) for a local district and formulates a constrained nonlinear multiobjective optimization model for the daily operation of the system. The main objective of the study is to increase the efficiency by minimizing energy cost, energy consumption, and energy losses. It is implemented through the integration and complementation of renewable energies and fossil fuels as well as the recycling utilization of waste heat in the DES. The consideration of network topology and energy losses of water heating network could also contribute to the improvement of energy efficiency. To solve the optimization problem, a novel Whale Optimization Algorithm is employed. Furthermore, the economic and energy performance of the DES are evaluated and compared with that of conventional centralized energy systems, ie, the EG and MG energy‐supply modes. After simulation studies, the hourly optimal energy (both natural gas and electricity) purchasing schedule as well as the hourly optimal set points of mass water flow rates and supply/return water temperatures could be determined. The results show that the DES saves more than 50% of energy costs/energy consumption than the MG mode and over 22% than the EG mode for a whole day, verifying the competitive advantage and great potential of both energy saving and cost reduction of the DES.     

考虑热惯性的居民楼宇综合能源系统日前运行优化

针对居民楼宇中部分热负荷的热惯性特征,提出了一种考虑热惯性的居民楼宇综合能源系统日前运行优化方法。首先,建立了居民楼宇综合能源系统的典型结构和数学模型,探究能源供给、转换、分配、存储的机理;其次,基于线性能量平衡法,采用微分方程描述楼宇制冷采暖系统和生活热水系统的热惯性特征,并将上述方程差分化;再次,以综合成本最小为目标,考虑购能约束、功率平衡约束、热惯性约束、备用容量约束等,建立日前运行优化模型,并将上述模型转化为混合整数二次规划,通过Yalmip调用Cplex求解;最后,通过实际算例分析热惯性对居民楼宇综合能源系统运行优化的影响。结果表明,利用热惯性能够对冷热负荷进行平移或削减,从而降低运行成本。     

基于主从博弈理论的综合能源系统优化运行方法

综合能源系统作为实现智慧能源的关键技术形式,其优化运行问题是一门重要课题。针对综合能源系统优化运行问题,考虑到系统多能互补协调,基于主从博弈理论进行建模。其中:主体博弈模型以多能互补协调计划为博弈策略,以综合能源系统综合运行成本最小化为博弈支付,计及多能互补协调约束等必要约束条件;从体博弈模型以各个形式能源子网的运行计划为博弈策略,以能源子网运行收益最大化为博弈支付,计及分布式供能设备运行约束等必要约束条件。分析得到主从博弈模型的纳什均衡,基于混沌粒子群算法设计模型求解流程。最后通过仿真算法表明,所建立的模型适用于综合能源系统优化运行方案制定,能够显著降低系统运行成本。     

Multi-objective optimization of wind-hydrogen integrated energy system with aging factor

Large-scale hydrogen production with wind power generation has been gaining increasing attention and applications. Achieving a good balance between the capacity and cost of wind power generation however remains as a critical challenge restricting the development of wind-hydrogen integrated energy systems (WHIES). In addition, the aging factor may come in over time, making negative impacts on the efficiency and cost of WHIES. In this work, a method is proposed to seek a good balance between the capacity and cost of WHIES. Specifically, by comparing operational data and equipment condition, we evaluate the aging status of the wind power generation system and the hydrogen production system, then the aging economic model of WHIES is proposed. By taking into account the actual operating conditions in constructing the WHIES objective function with the aging factor, the proposed model allows striving to maximize the production capacity with the minimum cost. An improved multi-objective gray wolf optimizer algorithm is developed to solve the WHIES cost optimization problem. Finally, case studies are carried out via MATLAB based on the configuration and experimental data for a specific wind farm located in Ningxia, China. Our results help achieve a balance between maximizing capacity and minimizing cost under various conditions.     

Stochastic security-constrained operation of wind and hydrogen energy storage systems integrated with price-based demand response

Because of highly increasing energy consumption, environmental issues and lack of common energy sources, the use of renewable energy sources especially wind power generation technology is increasing with significant growth in the world. But due to the variable nature of these sources, new challenges have been created in the balance between production and consumption of power system. The hydrogen energy storage (HES) system by storing excess wind power through the technology of power to hydrogen (P2H) and delivering it to the electricity network through hydrogen-based gas turbine at the required hours reduces not only wind alternation but can play an important role in balancing power production and consumption. On the other hand, power consumers by participating in demand response (DR) programs can reduce their consumption at peak load or wind power shortage hours, and increase their consumption at low-load or excess wind power hours to reduce wind power spillage and system energy cost. This paper proposes a stochastic security constrained unit commitment (SCUC) with wind energy considering coordinated operation of price-based DR and HES system. Price-based DR has been formulated as a price responsive shiftable demand bidding mechanism. The proposed model has been tested on modified 6-bus and 24-bus systems. The numerical results show the effect of simultaneous consideration of HES system and price-based DR integrated with wind energy on hourly generation scheduling of thermal units. As a result there is some reduction in wind generation power spillage and daily operation cost.     

Distributed generation integrated with thermal unit commitment considering demand response for energy storage optimization of smart grid

This paper deals with an optimal battery energy storage capacity for the smart grid operation. Distributed renewable generator and conventional thermal generator are considered as the power generation sources for the smart grid. Usually, a battery energy storage system (BESS) is used to satisfy the transmission constraints but installation cost of battery energy storage is very high. Sometimes, it is not possible to install a large capacity of the BESS. On the other hand, the competition of the electricity market has been increased due to the deregulation and liberalization of the power market. Therefore, the power companies are required to reduce the generation cost in order to maximize the profit. In this paper, a thermal units commitment program considers the demand response system to satisfy the transmission constraints. The BESS capacity can be reduced by the demand response system. The electric vehicle (EV) and heat pump (HP) in the smart house are considered as the controllable loads of the demand side. The effectiveness of the proposed method is validated by extensive simulation results which ensure the reduction of BESS capacity and power generation cost, and satisfy the transmission constraints.     

Multi-objective planning of micro-grid system considering renewable energy and hydrogen storage systems with demand response

Recently, researchers in the power system industry have considered the intelligent parking lot idea. The intelligent parking lots (IPL) try to exchange power with the upstream by electric vehicles (EVs) charge/discharge application. The mentioned process of charge/discharge can provide a solution model of regular problems in this field, i.e., peak time problems. Additionally, such vehicles' existence can play an essential role in environmental performance enhancement in power systems. The primary purpose of this paper is to consider such enhancements of EVs in power systems and environmental performance. For this purpose, a multi-objective optimization approach is suggested for the environmental performance and economical operation of IPL by considering the time-of-use rates of a demand response program. Since such a model is associated with various practical bounds, the multi-objective grasshopper optimization algorithm is suggested to solve this problem. The outcomes indicate the effectiveness of the compared techniques utilizing fuzzy decision-making strategies. Chaos theory is employed to increase this method and progress searching operators. Additionally, the proposed multi-objective technique is a model created using fuzzy theory, variable detection, strategy selection-based memory, and non-dominated sorting theory to choose the best Pareto from a list of solutions with robust functionality for resolving the problems mentioned above. The proposed technique is tested on a sample system that includes an intelligent parking lot, local production facilities, and non-renewable and renewable production systems under the proposed uncertainty strategy of upstream grid pricing. The study showed the effectiveness of the suggested method. The simulation findings indicate that the emission rate and overall cost of intelligent parking lots are reduced by 3.87 and 2%. It indicates that economic and environmental objectives are also satisfied due to the successful deployment of a demand response program.