Incorporating Energy Storage Research Articles

Incorporating energy storage and demand response into intentional controlled islanding using time decomposition

Incorporating energy storage and demand response into intentional controlled islanding using time decomposition

Retrofitting solar power plants with thermal energy storage

A thermal energy storage system module has been retrofitted into a validated system-level model of an existing concentrating solar power plant to evaluate the outcome of incorporating energy storage into its operation. The number of solar field loops had to be doubled to provide the proposed thermal energy storage system with heat leftover after delivering the heat demand of the power block. Most power block equipment were unaffected by the energy storage augmentation; however, the capacity of the heat transfer fluid pump was amplified to meet the increased circulation demand in the solar field. As a result of this thermal energy storage augmentation, electric power generation was increased and made more streamlined while idle time was reduced. Formulas to size thermal energy storage systems and solar fields are introduced. Sample results from the validated concentrating solar power plant model operating with and without the proposed thermal energy storage augmentation are presented.

Retrofitting solar power plants with thermal energy storage

A thermal energy storage system module has been retrofitted into a validated system-level model of an existing concentrating solar power plant to evaluate the outcome of incorporating energy storage into its operation. The number of solar field loops had to be doubled to provide the proposed thermal energy storage system with heat leftover after delivering the heat demand of the power block. Most power block equipment were unaffected by the energy storage augmentation; however, the capacity of the heat transfer fluid pump was amplified to meet the increased circulation demand in the solar field. As a result of this thermal energy storage augmentation, electric power generation was increased and made more streamlined while idle time was reduced. Formulas to size thermal energy storage systems and solar fields are introduced. Sample results from the validated concentrating solar power plant model operating with and without the proposed thermal energy storage augmentation are presented.

Intelligent Energy Management for Off-Grid Renewable Hybrid System Using Multi-Agent Approach

Smart Hybrid Home Power Systems are interested in studying power issues for isolated customers who have an off-grid power connection. The establishment of independent hybrid power systems has seen as a method of improving energy security. Our main goal is to ensure that energy is produced efficiently. To accomplish this objective, we have suggested a detailed simulation system in which the solar energy factor is considered as the main source. The system also incorporates energy storage devices to ensure safe energy distribution and recovery (Fuel Cell/Ultra-Capacitor). An Intelligent Energy Management System is developed and discussed to ensure that the system operates properly using a precise multi-agent system. The recommended power management system is designed to identify Multi-Agent tasks and to understand possible scenarios by the energy characteristics and energy demands. The reached results proved that the proposed system reaches the goals defined for Intelligent Energy Management System about an experimental database extracted from Tunisian climate services using Matlab/Simulink Software.

A convexification technique for optimal thermal-wind-photovoltaic coordination dispatch incorporating energy storage system

A convexification technique for optimal thermal-wind-photovoltaic coordination dispatch incorporating energy storage system

Adaptive Distance Protection for Transmission Lines Incorporating SSSC With Energy Storage Device

A Static Synchronous Series Compensator incorporating energy storage device (SSSC-ES) at the DC bus enables the exchange of true power with the system in addition to line reactance compensation. This facilitates improved control of real and reactive power in a transmission system. However, the four-quadrant operation of SSSC presents additional problems for the accurate operation of conventional transmission line protection. In this paper, an in-depth analysis of the effect of emulated reactance and resistance by SSSC-ES installed at the center of a hybrid series compensated line on the performance of distance relay is carried out. An investigation is performed with all possible operating modes and control strategies of SSSC-ES, and the possibility of mal-operation of distance protection are explored. A novel adaptive setting based on constant reactance and constant resistance emulation control strategy of SSSC is proposed for quadrilateral distance relay to prevent the mal-operation. MATLAB / SIMULINK is used for the simulation study.

Hybrid Energy Storage System (HESS) optimization enabling very short-term wind power generation scheduling based on output feature extraction

Incorporating Energy Storage System (ESS) with wind farm to establish Wind-Storage Combined Generation System is a promising solution to improve the dependability of integrated wind power. Hybrid Energy Storage System (HESS) is designed based on wind power fluctuation and ESS features. The optimization of system sizing and very short-term generation scheduling are the key points affecting system effectiveness and reliability of wind power. This paper proposes a novel real-time model prediction control (MPC) -multi objective cross entropy (MOCE) based energy management algorithm (MMEMA) to coordinate an HESS based on power output feature extraction. The proposed algorithm includes the SOC regulation strategies considering practical issues including charge/discharge power. Firstly, based on Wavelet Package Decomposition (WPD) and Hilbert Huang Transform (HHT) respectively, the fluctuation feature of real-time wind power output is studied to propose a HESS model aiming to obtain the economic capacity as well as maximum charging/discharging power in every generation scheduling period (10 min). Thus, according to case study, the sizing approach can reduce invest cost by 25.7–47.0%. Then, HESS data is taken as parameters and constraints for the proposed model prediction control (MPC) –multi objective cross entropy (MOCE) algorithm to minimize the deviation between generation scheduling plan and real-time integrated power. The optimization results from case wind farm show that the proposed MMEMA algorithm performs better in smoothing out the fluctuation and managing the SOC of HESS than Non-dominated Sorting Genetic Algorithm II based method (NEMA) by means of evaluating the indexes PD, HSOC and MSE.

Wavelet Transform Based Protection of Transmission Lines with Four Quadrant Operation of STATCOM

This paper proposes a new wavelet transform based relay logic for the protection of transmission lines compensated with a static synchronous compensator incorporating energy storage device (STATCOM – ES). STATCOM with energy storage systems can operate in any of the four quadrants in P – Q plane. A conventional distance relay with standard settings may not be reliable to identify and categorize short circuit faults in such systems. A simple, fast acting and reliable wavelet based relay logic is presented to accurately identify and categorize transmission line faults in shunt compensated lines. The developed relay discriminates between internal and external faults accurately. It provides reliable protection for the transmission line considering the entire four quadrant operating range of STATCOM – ES and is immune to the value of fault resistance.

Ancillary Services Provision Utilizing a Network of Fast-Charging Stations for Electrical Buses

Fast-charging stations that supply energy to electrical vehicles at high power rates may incorporate energy storage to avoid high currents to the grid and reduce peak-demand costs. We demonstrate the potential for utilizing such infrastructure for the provision of ancillary services (AS) to power grids. The main challenge we address is the coordination between the stochastic demand for the real-time delivery of AS while charging the randomly arriving electrical vehicles. The method presented here, employing two-stage stochastic optimization, calculates both the maximum capacity of AS the system can provide and handles optimally the real-time delivery of control-energy to the grid upon request by integrating intraday trades. To showcase our concept we have employed the ABB TOSA electrical bus charging network and demonstrated, through simulation studies, with realistic models and energy prices, that the method is technically feasible, can deliver a considerable level of control energy, offers substantial economic benefits, and has only a minor impact on the lifetime of the storage system.

Adequacy Assessment of Generating Systems Incorporating Storage Integrated Virtual Power Plants

This paper investigates the impacts of incorporating energy storage devices (ESD) into a virtual power plant (VPP) model and subsequently using it for performing generating system adequacy studies. A two-step linearized optimization formulation is proposed for developing the overall VPP model featuring the aggregated characteristics and capacities of several distributed generators (DG), ESDs and loads together with distribution network information like topology and constraints. While the first step determines the (charging or discharging) operating mode of the batteries, the second step outputs the optimal dispatch schedules for the DGs and ESDs in accordance with a fair energy allocation based operating strategy adopted in this paper. The VPP is modeled using an augmented IEEE 69-bus distribution network, and the overall generation adequacy studies incorporating the VPP are carried out on the IEEE Reliability Test System using a sequential simulation algorithm. Several indices are presented for quantifying the impacts of the ESDs’ incorporation on the VPP model’s performance. Finally, sensitivity studies conducted for investigating the effects of variations in the ESD rated capacities and charging/discharging periods on the VPP performance and system adequacy indices are also described.

Energy and economic assessment of solar Organic Rankine Cycle for combined heat and power generation in residential applications

The installation of solar heating systems for new buildings is currently imposed by regulation in different European countries. An interesting option to improve the use of solar thermal systems is its integration with an Organic Rankine Cycle to generate electricity, what would potentially increment the utilization factor of existing solar installations. The objective of the paper is to evaluate technically and economically the integration of solar thermal and ORC to conform a residential microCHP system able to cover a significant amount of the energy requirements of a standard house. Moreover, several strategies are analyzed to incorporate energy storage within the microCHP system. Two operation modes of the system are evaluated, isolated and integrated within the grid network: i) Solar energy for producing domestic hot water and electric power production in the ORC auxiliary power system; ii) Reversible micro-scale ORC with a scroll compressor to run as a scroll expander. An economic analysis is done under different scenarios. Results show the appeal of the implementation of these systems at small scale for residential applications in locations with specific climate conditions. IRR values above 15% with short payback periods from 3.1 years and positive NPV are obtained.

Incorporating energy storage and user experience in isolated microgrid dispatch using a multi‐objective model

In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment and users, a practical multi-objective dynamic optimal dispatch model incorporating energy storage and user experience is proposed for isolated microgrids. In this model, besides Microturbine units, energy storage is employed to provide spinning reserve services for microgirds; and furthermore, from the perspective of demand side management, a consumer satisfaction indicator is developed to measure the quality of user experience. A two-step solution methodology incorporating multi-objective optimization (MOO) and decision analysis is put forward to address this model. First, a powerful heuristic optimization algorithm, called the {\theta}-dominance based evolutionary algorithm, is used to find a well-distributed set of Pareto-optimal solutions of the problem. And thereby, the best compromise solutions (BCSs) are identified from the entire solutions with the use of decision analysis by integrating fuzzy C-means clustering and grey relation projection. The simulation results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab microgrid test system demonstrate the effectiveness of the proposed approach.

Levelized income loss as a metric of the adaptation of wind and energy storage to variable prices

Classifying and categorizing generators according to their financial efficiency is necessary to compare the degree of competitiveness of a generating technology. The levelized cost of energy (LCoE) is arguably the most relevant index for that purpose. It relates the capital and operating expenses to the expected energy output, to encapsulate the financial efficiency into an €/MWh. It is technology-independent, meaning that it can be used for comparing different generator types in a fair basis. However, the LCoE is defined to provide a cost figure under the assumption of a fixed-tariff. It does not make any difference when comparing the performance of an intermittent generating technology in different spot markets. The LCoE does not inherently account for the variability of prices.This paper details a different approach to classify intermittent renewable generators operating under variable-price tariffs. It shows a levelized income loss as a figure of how the generator allocates the available energy. Ideally, a generator with a production allocated in low-price times would have higher LIL than other with the same production responding to high-price times. Generator location, characteristics, and the market to which the generator delivers the energy make a difference.This paper shows a methodology to not only obtain the index under uncertain market prices and energy production, but also details a dynamic program to incorporate energy storage systems (ESS). The idea behind this additional investigation is that the re-allocation of the limited energy of a renewable generator might well improve the economic performance. The dynamic program approaches the ESS switching decisions from a stochastic perspective, offering a rigorous evaluation.Finally, this paper describes the dynamic linear models of several European day-ahead markets and wind datasets to offer a broad valuation of the LIL, and of its possible improvement through the use of ESS.

Optimizing Size of Variable Renewable Energy Sources by Incorporating Energy Storage and Demand Response

The electricity sector contributes to most of the global warming emissions generated from fossil fuel resources which are becoming rare and expensive due to geological extinction and climate change. It urges the need for less carbon-intensive, inexhaustible Renewable Energy Sources (RES) that are economically sound, easy to access and improve public health. The carbon-free salient feature is the driving motive that propels widespread utilization of wind and solar RES in comparisons to rest of RES. However, stochastic nature makes these sources, variable renewable energy sources (VRES) because it brings uncertainty and variability that disrupt power system stability. This problem is mitigated by adding energy storage (ES) or introducing the demand response (DR) in the system. In this paper, an electricity generation network of China by the year 2017 is modeled using EnergyPLAN software to determine annual costs, primary energy supply (PES) and CO2 emissions. The VRES size is optimized by adding ES and DR (daily, weekly, or monthly) while maintaining critical excess electricity production (CEEP) to zero. The results substantiate that ES and DR increase wind and solar share up to 1000 and 874 GW. In addition, it also reduces annual costs and emissions up to 4.36 % and 45.17 %.

Incorporating energy storage into probabilistic security‐constrained unit commitment

System operators still rely on deterministic criteria such as the N - 1 (i.e. the system would be able to withstand the outage of any single component without any load shedding) to hedge the system against contingencies. While simple and practical, this criterion miscalculates the actual amount of reserve required since it ignores the probability of contingency occurrence. Therefore, this criterion may lead to suboptimal reserve procurement and economic performance of the system. This study presents a multiperiod probabilistic security-constrained unit commitment (UC) model that includes the probabilities of generation and transmission contingencies for optimal reserve sizing, sourcing, allocation, and timing. The ability of energy storage systems (ESS) to provide contingency reserve is explicitly modelled. Benders' decomposition and linearisation techniques are applied to solve the proposed probabilistic UC, which would be intractable otherwise. The impact of ESS on the contingency reserve procurement and deployment in post-contingency states are analysed on a modified version of the IEEE One-Area Reliability Test System.

Optimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage

Wind and solar energy based hybrid systems incorporating energy storage can often provide cost effective and reliable energy alternatives to the conventional systems commonly used by remote consumers. To integrate a high level of variable wind and solar energy, energy storage is important. The primary contribution made by the present article is the development of a new efficient methodology for modeling and optimally sizing a hybrid system for renewable energy considering two energy storage devices: hydrogen (as a form of chemical storage) and batteries (as a form of electrochemical storage). To optimize the decision variable values, modified versions of the simulated annealing algorithm-based chaotic search and harmony search are developed. This is dedicated to the optimization of the supply of residential electrical load via stand-alone hybrid energy systems, so as to achieve the minimum life cycle cost of the system by continuous and integer decision variables. The proposed modified approach is used to size optimally the components of six schemes for a remote area in Iran: wind/hydrogen, solar/hydrogen, solar/wind/hydrogen, wind/battery, solar/battery, and solar/wind/battery. To determine the methodology quality, the performance of the proposed hybrid algorithm is contrasted with that for simulated annealing and hybrid harmony search and simulated annealing algorithms. The optimization results demonstrate that a wind and solar energy based hybrid system with electrochemical storage offers more cost effective and reliable energy than a hybrid system for renewable energy with chemical storage. Also, among hybrid systems, the wind/battery system is clearly advantageous economically for supplying power. The portions of life cycle cost of the wind turbine, batteries, and converter/inverter are 67%, 5%, and 28%, respectively. The relative errors between the Mean index of are shown to be at most 11%. Finally, a comparison of the Min., Max., Mean, and Std. values, in the six hybrid systems, shows that the proposed hybrid algorithm is more robust than the others considered since it has lower index values.

Reliability improvement in smart grid through incorporating energy storage systems in service restoration

Reliability improvement in smart grid through incorporating energy storage systems in service restoration

Theoretical Performance Limits of an Isobaric Hybrid Compressed Air Energy Storage System

The desire to increase power production through renewable sources introduces a number of problems due to their inherent intermittency. One solution is to incorporate energy storage systems as a means of managing the intermittent energy and increasing the utilization of renewable sources. A novel hybrid thermal and compressed air energy storage (HT-CAES) system is presented which mitigates the shortcomings of the otherwise attractive conventional compressed air energy storage (CAES) systems and its derivatives, such as strict geological locations, low energy density, and the production of greenhouse gas emissions. The HT-CAES system is investigated, and the thermodynamic efficiency limits within which it operates have been drawn. The thermodynamic models considered assume a constant pressure cavern. It is shown that under this assumption the cavern acts just as a delay time in the operation of the plant, whereas an adiabatic constant volume cavern changes the quality of energy through the cavern. The efficiency of the HT-CAES system is compared with its Brayton cycle counterpart, in the case of pure thermal energy storage (TES). It is shown that the efficiency of the HT-CAES plant is generally not bound by the Carnot efficiency and always higher than that of the Brayton cycle, except for when the heat losses following compression rise above a critical level. The results of this paper demonstrate that the HT-CAES system has the potential of increasing the efficiency of a pure TES system executed through a Brayton cycle at the expense of an air storage medium.

A non-linear convex cost model for economic dispatch in microgrids

This paper proposes a convex non-linear cost saving model for optimal economic dispatch in a microgrid. The model incorporates energy storage degradation cost and intermittent renewable generation. Cell degradation cost being a non-linear model, its incorporation in an objective function alters the convexity of the optimization problem and stochastic algorithms are required for its solution. This paper builds on the scope for usage of macroscopically semi-empirical models for degradation cost in economic dispatch problems and proves that these cost models derived from the existing semi-empirical capacity fade equations for LiFePO4 cells are convex under some operating conditions. The proposed non-linear model was tested on two data sets of varying size which portray different trends of seasonality. The results show that the model reflects the trends of seasonality existing in the data sets and it minimizes the total fuel cost globally when compared to conventional systems of economic dispatch. The results thus indicate that the model achieves a more accurate estimate of fuel cost in the system and can be effectively utilized for cost analysis in power system applications.

Optimal cogeneration and scheduling of hybrid hydro-thermal-wind-solar system incorporating energy storage systems

This paper optimizes cogeneration of a hydro-thermal-wind-solar system. In the proposed hybrid system, the energy storage systems are also incorporated to smooth out the fluctuations of renewable energies. The uncertainties of wind and solar powers are included, and stochastic programming is adopted to deal with the uncertainties. The hydro system comprises two cascade reservoirs. The optimal scheduling of both reservoirs is presented, and the electricity generated by each reservoir is optimized. The optimal scheduling of thermal unit is also determined. The optimal location, capacity, power, and charging-discharging pattern are determined for battery energy storage systems. The simulations are carried out using an IEEE 69-bus distribution network, and the model is implemented in GAMS software and solved as a mixed integer linear programming. The objective of the problem is to minimize energy cost in the network. The results demonstrate that the proposed stochastic model can successfully optimize cogeneration of hydro-thermal-wind-solar system. The planning moreover optimally utilizes energy storage systems for damping the fluctuations of renewable energies and minimizing energy cost.