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.     

Minimization and control of battery energy storage for wind power smoothing: Aggregated,distributed and semi-distributed storage

A battery energy storage system (BESS) is usually integrated with a wind farm to smooth out its intermittent power in order to make it more dispatchable. This paper focuses on the development of a scheme to minimize the capacity of BESS in a distributed configuration using model predictive control theory and wind power prediction. The purpose to minimize the BESS capacity is to reduce the overall cost of the system as the capacity of BESS is the main cost driver. A new semi-distributed BESS scheme is proposed and the strategy is analyzed as a way of improving the suppression of the fluctuations in the wind farm power output. The scheme is tested for similar and dissimilar wind power profiles, where the turbines are geographically located closer and further from each other, respectively. These two power profiles are assessed under a variety of hard system constraints for both the proposed and conventional BESS configurations. Based on the simulation results validated with real-world wind farm data, it has been observed that the proposed semi-distributed BESS scheme results in the improved performance as compared with conventional configurations such as aggregated and distributed storage.     

Predictive control and sizing of energy storage to mitigate wind power intermittency

This paper studies how the control algorithm impacts the required capacity of battery energy storage system (BESS) to mitigate wind intermittency. We study a futuristic scenario in which wind generation is traded in the energy market on an hourly basis, and the wind power producer has to procure reserves to handle wind fluctuations. The wind power producer can avoid paying for conventional reserves by charging/discharging BESS to compensate for wind surplus and deficit. We develop control algorithms using the model predictive control (MPC) methodology, which incorporates wind forecasts for the next few hours when determining wind scheduling. The MPC algorithm is developed by solving a non‐linear optimization problem to minimize operation costs to the wind power producer. In addition to operation costs, the MPC algorithm considers two practical aspects: the efficiency loss of BESS and the smoothness in wind power scheduling. BESS sizing is studied by parametric analyses. Simulations show that BESS is more effective in reducing operation costs and reducing wind curtailment than conventional reserves. In addition, MPC is a horizon‐based control algorithm and can preview future information in its control action. Simulations also show that MPC consistently outperforms an instantaneous heuristic algorithm that does not use future information. Therefore, we confirm that MPC can reduce the BESS capacity required to cover wind uncertainties. Copyright © 2015 John Wiley & Sons, Ltd.     

A market‐oriented wind power dispatch strategy using adaptive price thresholds and battery energy storage

In this paper, an adaptive dispatch strategy is presented to maximize the revenue for grid‐tied wind power plant coupled with a battery energy storage system (BESS). The proposed idea is mainly based on time‐varying market‐price thresholds, which are varied according to the proposed algorithm in an adaptive manner. The variable nature of wind power and market price signals leads to the idea of storing energy at low price periods and consequently selling it at high prices. In fact, the wind farm operators can take advantage of the price variability to earn additional income and to maximize the operational profit based on the choice of best price thresholds at each instant of time. This research study proposes an efficient strategy for intermittent power dispatch along with the optimal operation of a BESS in the presence of physical limits and constraints. The strategy is tested and validated with different BESSs, and the percentage improvement of income is calculated. The simulation results, based on actual wind farm and market‐price data, depict the proficiency of the proposed methodology over standard linear programming methods.     

Modeling of integrated renewable energy system for electrification of a remote area in India

Over the years, renewable energy based power generation has proven to be a cost-effective solution in stand-alone applications in the regions where grid extension is difficult. The present study focused on the development of models for optimal sizing of integrated renewable energy (IRE) system to satisfy the energy needs in different load sectors of four different zones considered in Chamarajanagar district of Karnataka state in India. The objective of the study is to minimize the total cost of generation and cost of energy using genetic algorithm (GA) based approach. Considering optimization power factor (OPF) and expected energy not supplied (EENS), optimum system feasibility has been investigated. Based on the study, it has been found that IRES is able to provide a feasible solution between 1.0 and 0.8 OPF values. However, power deficit occurs at OPF values less than 0.8 and the proposed model becomes infeasible under such conditions. Customer interruption cost (CIC) and deficit energy (DE) for all zones were also computed to quantify the reliability of the systems.     

考虑多弹性资源调峰成本的可再生能源开发协同优化模型

中国制定了2030年和2060年的碳排放目标.可再生能源,主要是风能和光伏发电,被认为是未来的发电方式.新能源发展的主要制约因素是电力系统资源监管灵活性有限,导致消费能力不足.因此需要考虑调峰灵活的资源成本以及区域可再生能源的合理协调开发和运行优化.本研究考虑了电力系统综合成本,综合分析电力系统各种弹性调节资源潜力及其...     

Discrete harmony search based size optimization of Integrated Renewable Energy System for remote rural areas of Uttarakhand state in India

In the recent years, decentralized power generation using locally available renewable energy resources has been recognized as a cost effective alternative of uneconomical grid extension. The present paper deals with the size optimization of Integrated Renewable Energy System (IRES) for a cluster of villages of Uttarakhand state in India. The proposed IRES consists of locally available renewable energy resources of Micro Hydro Power (MHP), biogas, biomass, wind and solar energy in order to meet the electrical and cooking demands of the study area. A system operation strategy has been developed in the paper for size optimization of IRES. Also, the loss of power supply probability (LPSP) has been used as the reliability criteria in order to ensure the continuous supply of power without any failure problems. Further, in order to utilize renewable energy resources in different contributions, four different resource scenarios are considered for the study area. Finally, the total net present cost (NPC) of the considered scenarios has been optimized using discrete harmony search (DHS) algorithm. Among different scenarios, MHP-biogas-biomass-wind-solar-battery based IRES offers the lowest net present cost of INR 49.0309 million at the estimated LCOE of INR 5.47/kWh.     

An energy system for the integration of renewable energy with energy storage in a frigid plateau region

面向高原高寒地区对稳定供热和供电的迫切需求,本文提出了一种新型的可再生能源与储能集成供能系统。该系统包括风力发电、光伏发电、水力发电、槽式太阳能集热器、储热系统、储电装置以及集成控制系统,实现了多种可再生能源高效利用;制定了一种考虑热电设备性能的实时能量管理策略,并建立了以年成本为主要优化目标的容量配置方法;利用该系统与优化方法对高原高寒地带民用住宅群的供能系统进行了优化设计,通过案例对比分析,验证了该集成供能系统容量配置方法和能量管理策略的可行性。研究结果为高原高寒地区供能系统的选择提供了有益的参考。     

Integrated battery controller for distributed energy system

In this article, an improved integrated battery energy storage system (BESS) controller for distributed energy system is presented. The BESS is integrated in parallel with the full wave bridge converter into the distributed energy system network. In a normal operating mode, the BESS serves as a power conditioner as well as an active power filter in a distributed power system network. This work presents BESS controller which is designed for regulating the state of charge of the batteries and also to manage the active power in a distributed power system network. The off peak load energy is used to recover the batteries’ state of charge through the BESS controller. In this BESS controller, the constant current-constant voltage (CC-CV) mode is used and it helps to keep the batteries’ state of charge conditions for improving the reliability of the distributed power system system. This control strategy is incorporated into the main converter. The controller helps in managing the phase, amplitude and waveform of the current and voltage on the distributed power system network. The controller ensures the power quality and also assists in improving the power factor with respect to the utility for the intermittent distributed generation as well as the load. In this article, the test results of a prototype system are presented, which validates the proposed controller strategy of BESS in a distributed power system network.     

Allocation and sizing of battery energy storage system for primary frequency control based on bio-inspired methods: A case study

This paper presents a new procedure for optimal allocation and optimal sizing of a battery energy storage system (BESS) for primary frequency support in an isolated power system. For the BESS allocation, a transmission bus system with larger frequency decline is recognized and the BESS sizing is performed by a constrained optimization strategy based on a new modified metaheuristic, called Developed Harris Hawks Optimization (DHHO). The simulation results of the suggested DHHO are compared with Bat Optimization Algorithm (BOA) and Genetic Algorithm (GA) from the literature to show the method efficiency. The final results showed higher precision with lower required iterations for the suggested DHHO method. Also, the proposed DHHO gives lower investment costs for BESS with lower power and energy requirement toward the other compared methods.     

Multi-objective planning and optimization of microgrid lithium iron phosphate battery energy storage system consider power supply status and CCER transactions

Lithium iron phosphate battery (LIPB) is the key equipment of battery energy storage system (BESS), which plays a major role in promoting the economic and stable operation of microgrid. Based on the advancement of LIPB technology and efficient consumption of renewable energy, two power supply planning strategies and the china certified emission reduction (CCER) model are proposed respectively. Based on it, the multi-objective planning optimization model with economic benefits, environmental benefits and power supply stability as the objective function is established for the first time, and the Newton Weighted Sum Frisch method (NWSFA) solution model is adopted. In the planning process, rain flow counting method is used to research the life of BESS, which improves the accuracy of energy storage annual cost calculation. A park in northern China is taken as a case study to demonstrate the application of this model. The simulation results show that the annual economic operating cost of BESS is decreased by 18.81%, the energy supply reliability is increased by 0.15%, and the optimal electricity price adjustment ratio of the system is 15%.     

Techno-economic analysis of a hybrid energy system for CCHP and hydrogen production based on solar energy

A typical problem in Northeast China is that a large amount of surplus electricity has arisen owing to the serious photovoltaic power curtailment phenomenon. To effectively utilize the excess photovoltaic power, a hybrid energy system is proposed that uses surplus electricity to produce hydrogen in this paper. It combines solar energy, hydrogen production system, and Combined Cooling Heating and Power (CCHP) system to realize cooling, heating, power, and hydrogen generation. The system supplies energy for three public buildings in Dalian City, Liaoning Province, China, and the system configuration with the lowest unit energy cost (0.0615$/kWh) was obtained via optimization. Two comparison strategies were used to evaluate the hybrid energy system in terms of unit energy cost, annual total cost, fossil energy consumption, and carbon dioxide emissions. Subsequently, the annual total energy supply, typical daily loads, and cost of the optimized system were analyzed. In conclusion, the system is feasible for small area public buildings, and provides a solution to solve the phenomenon of photovoltaic power curtailment.     

Steady-state modelling of hybrid energy system for off grid electrification of cluster of villages

Electrification of villages from the main grid leads to large investments and losses, and this forms the basis of decentralized Hybrid Energy System. In order to evaluate the techno-economic performance of hybrid energy system for remote rural area electrification, a mixed integer linear mathematical programming model (time-series) has been developed to determine the optimal operation, optimal configuration including the assessment of the economic penetration levels of photovoltaic array area, and cost optimization for a hybrid energy generation system consisting of small/micro hydro based power generation, biogas based power generation, biomass (fuelwood) based power generation, photovoltaic array, a battery bank and a fossil fuel generator. An optimum control algorithm written in C++, based on combined dispatch strategy, allowing easy handling of the models and data of hybrid energy system components is presented. A special feature of the proposed model is that a cost constant (cost/unit) for each of the proposed resource is introduced in the cost objective function in such a way that resources with lesser unit cost share the greater of the total energy demand in an attempt to optimize the objective function.To demonstrate the use of model and algorithm, a case study for a rural remote area is also presented.     

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.     

A new approach of sizing battery energy storage system for smoothing the power fluctuations of a PV/wind hybrid system

In this paper, a new approach for optimally sizing the storage system employing the battery banks for the suppression of the output power fluctuations generated in the hybrid photovoltaic/wind hybrid energy system. At first, a novel multiple averaging technique has been used to find the smoothing power that has to be supplied by the batteries for the different levels of smoothing of output power. Then the battery energy storage system is optimally sized using particle swarm optimization according to the level of smoothing power requirement, with the constraints of maintaining the battery state of charge and keeping the energy loss within the acceptable limits. Two different case studies have been presented for different locations and different sizes of the hybrid systems in this work. The results of the simulation studies and detailed discussions are presented at the end to portrait the effectiveness of the proposed method for sizing of the battery energy storage system. Copyright © 2016 John Wiley & Sons, Ltd.     

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 optimal allocation strategy for the energy internet in Huangpu District,Guangzhou, China

To improve the overall efficiency of the energy system, the basic structure for the energy internet of coordination and optimization of “generation-grid-load-storage” of Huangpu District, Guangzhou, China is designed, while the arrangement for the output of centralized and distributed energy module and energy storage are proposed. Taking economic benefit maximization, environmental benefit maximization and energy efficiency maximization as sub-objectives, the mathematical model of multi-objective optimal allocation and operation strategy of the energy internet is established considering supply-demand balance constraints, equipment characteristic constraints, operation mode constraints, and energy conditions constraints. The calculation results show that without considering the outsourced electricity, the balanced strategy, the economic development strategy, the environmental protection strategy, and the energy efficiency strategy are obtained by calculation, which are all superior to the traditional energy supply strategy. Moreover, considering the outsourced electricity, the proportion of outsourced electricity to total electricity is 19.8%, which is the system optimization of the energy internet under certain power demand. Compared with other strategies without outsourced electricity, the outsourced electricity strategy can have a certain emission reduction effect, but at the same time reduce the economic benefit. Furthermore, the huge difference in demand for thermal and cooling load between industrial and commercial areas results in the installed capacity of gas distributed energy stations in industrial areas being nearly twice as large as that in commercial areas. The distributed photovoltaic power generation is allocated according to the proportion of the installed roof areas of photovoltaic power generation system in residential, industrial, and commercial areas.     

Optimization and control of autonomous renewable energy systems

Recently, there has been a growing interest in harnessing renewable energy resources particularly for electricity generation. One of the main concerns in the design of an electric power system that utilizes renewable energy sources, is the accurate selection of system components that can economically satisfy the load demand. This depends on the load that ought to be met, the capacity of renewable resources, the available space for wind machines and solar panels, and the capital and running costs of system components. Once size optimization is achieved, the autonomous system must be controlled in order to correcly match load requirements with instantaneous variation of input energy. In this paper, a new formulation for optimizing the design of an autonomous wind-solar-diesel-battery energy system is developed. This formultation employs linear programming techniques to minimize the average production cost of electricity while meeting the load requirements in a reliable manner. The computer program developed reads the necessary input data, formulates the optimization problem by computing the coefficients of the objective function and the constraints and provides the optimum wind, solar, diesel, and battery ratings. In order to study the effect of parameters predefined by the designer on the optimum design, several sensitivity analysis studies are performed, and the effects of the expected energy not served, the load level, the maximum available wind area, the maximum available solar area, and the diesel engines' lifetime are investigated. A controller the monitors the operation of the autonomous system is designed. The operation of this controller is based on three major policies; in the first, batteries operate before diesel engines and hence the storage system acts as a fuel saver, while in the second diesel engines are operated first so that the unmet energy is lower but the fuel cost is high. According to the third policy, the supply is made through diesel engines only. This is done for the purpose of making a performance comparison between the isolated diesel system and the hybrid renewable energy system. The proposed optimization and control techniques are tested on Lebanese data. Although three different control policies have been adopted in this work, the software is able to accommodate other policies.     

计及不确定性的多类型发电机组联合调度优化模型

为了促进可再生能源并网,解决可再生能源机组在内的多类型发电机组联合优化调度问题,引入全额收购可再生能源发电,由火电机组提供备用、允许适度弃风,由火电机组提供备用以及水火机组联合提供备用的可再生能源发电三种不同方案。首先构建了涵盖风、光伏、水力机组的可再生能源机组发电处理模型;再结合设定的三种方案组建了多类型发电机组节能调度优化模型;最后,基于基础数据,得出该节能调度优化模型的发电系统总煤耗、备用煤耗、系统发电成本、启停成本、弃风量及弃水量等关键指标的优化效果,对多类型发电机组联合调度优化具有一定的指导意义。