Evaluation Of Energy Storage Systems Research Articles

Bidding strategy and economic evaluation of energy storage systems under the time-of-use pricing mechanism

Energy storage systems (ESSs) can smooth loads, effectively enable demand-side management, and promote renewable energy consumption. This study developed a two-stage bidding strategy and economic evaluation model for ESS. In the first stage, time-of-use (TOU) pricing model based on the consumer psychology theory and user demand response function is proposed. In the second stage, the benefits and life cycle costs of ESS were measured, and a bidding strategy optimization model was constructed to maximize profit. Subsequently, based on the environmental, social, and governance (ESG) concept, an integrated value model was constructed to evaluate the economics of ESS. Finally, the economics of ESSs were analyzed using the proposed model in a case study. The results indicate the following: (1) The TOU pricing model can effectively reduce the peak-to-valley load difference; (2) The integrated value of ESS is 249,930 yuan, and economic value of ESS is 22,016 yuan in scenarios 1, implying that the ESS has positive externalities under the TOU pricing mechanism; and (3) The net profit and economics of ESS are positively correlated with the rated power of the storage battery and negatively correlated with its rated capacity.

Techno-economic evaluation of energy storage systems for concentrated solar power plants using the Monte Carlo method

This paper aims to perform a techno-economic evaluation for the sensible heat, latent heat, and combined sensible-latent heat storage systems applied in concentrated solar power (CSP) plants. An analytical model that integrates the uncertainty of input variables is developed to observe the probability distribution of the levelized cost of electricity (LCOE) for various energy storage systems using a combination of Monte Carlo methods and economic indicators. Uncertainty quantification reveals that the combined sensible-latent heat storage system has the least uncertainty. The sensible-latent heat storage system has certainty equivalents of 0.1852 $/kWh and 0.1321 $/kWh for both the Blue Map and Roadmap scenarios, which is approximately 29% less than the two-tank molten salt energy storage system. Under emission trading, the environmental and social benefits of carbon reduction in energy storage systems can reduce the LCOE for CSP plants. This study can provide decision makers with more comprehensive information in determining the economic viability of different energy storage systems.

Multi-Dimensional Value Evaluation of Energy Storage Systems in New Power System Based on Multi-Criteria Decision-Making

The power sector may reduce carbon emissions and reach carbon neutrality by accelerating the energy transition and lowering its reliance on fossil fuels. However, there are limitations on the new power system’s ability to operate safely and steadily due to the randomness, volatility, and intermittent nature of renewable energy supply. The key to solving this issue is to harness the flexible resources that energy storage systems (ESSs) represent; however, ESSs have more than a value for providing system flexibility. Thus, this study suggested a flexible, technical, economic, and environmental value index system based on multi-criteria decision-making models for evaluating the multi-dimensional value of ESSs. First, the objective and subjective weights are obtained using the CRITIC model and best–worst method; then, the weights are combined using the minimum relative entropy model. The complete values of five typical ESSs are then evaluated using the TOPSIS model. Three scenarios that reflect the traits of the new power system are then created and analyzed. The outcome demonstrates the following: (1) as the new power system continues to grow, the value of ESSs’ flexibility has become ever more crucial; (2) as the need for system flexibility increases, the value of electrochemical ESSs gradually manifests.

Research on Smart Power Sales Strategy Considering Load Forecasting and Optimal Allocation of Energy Storage System in China

With the deepening reform of the power system, power sales companies need to adopt new power sales strategies to provide customers with better economic marketing solutions. Customer-side configuration of an energy storage system (ESS) can participate in power-related policies to reduce the comprehensive cost of electricity for commercial and industrial customers and improve customer revenue. For power sales companies, this can also attract new customers, expand sales and quickly capture the market. However, most of the ESS evaluation models studied so far are based on historical data configuration of typical daily storage capacity and charging and discharging scheduling instructions. In addition, most models do not adequately consider the performance characteristics of the ESS and cannot accurately assess the economics of the energy storage model. This study proposes an intelligent power sales strategy based on load forecasting with the participation of optimal allocation of ESS. Based on long short-term memory (LSTM) artificial neural network for predictive analysis of customer load, we evaluate the economics of adding energy storage to customers. Based on the premise of the two-part tariff, the ESS evaluation model is constructed with the objective of minimizing the annual comprehensive cost to the user by considering the energy tariff and the savings benefits of the basic tariff, assessing the annualized cost of ESS over its entire life cycle, and the impact of battery capacity decay on economics. The particle swarm optimization (PSO) algorithm is introduced to solve the model. By simulating the arithmetic example for real customers, their integrated electricity costs are significantly reduced. Moreover, this smart power sales strategy can provide different sales strategies according to the expected payback period of customers. This smart sales strategy can output more accurate declared maximum demand values than other traditional sales strategies, providing a more economical solution for customers.

System value evaluation of energy storage system in distribution networks: Theory and calculation model

With the proposal of the “carbon peak and neutrality goals”, energy storage system (ESS), as an emerging power technology, has great potential to promote the green transformation of energy in power systems. To further promote the development of the ESS industry and realize its commercialization, it is necessary to measure the multiple value that ESS brings to power systems. In this paper, the evaluation theory of system value is firstly explained, and two methods for calculating system value of ESS in power systems are proposed. Then, models for system value evaluation of ESS are established using the cumulative approximation method and the difference method, respectively. The former is the superposition of multiple value, and the latter is the difference between the value of the original system and the new system. The value benefits considered are: arbitrage benefit, network loss benefit, increased wind power consumption benefit, and emission reduction benefit. Finally, using the IEEE 33-node distribution network as a test system, the data results show that the cumulative approximation method can be applied to scenarios with fewer value domains, while the difference method is more suitable for quantitative value evaluation in the regional grid.

Evaluation of energy storage systems for sustainable development of renewable energy systems—A comprehensive review

Energy storage systems (ESSs) have acquired enhanced importance with the extensive growth and development of renewable energy systems (RESs) to accomplish the increasing demand of power without causing adverse effects on environment. The ESSs help to eliminate the effects of intermittent nature of RESs by either injecting power into the RESs or extracting power from RESs depending on whether the RESs is in shortage or excess of power, respectively. In the present study, an elaborate review is presented, which gives the recent perspective of the ESSs technologies, their comparative analysis, and various specifications as well as evaluation through S-Strength, W-Window of opportunity, I-Intimidation, F-Failing, and T-Technical maturity analysis. Divergent ESSs, capable of power regulation, power quality maintenance, and enhancement of the grid reliability, have had huge significance in sustainable development of RESs, which is highlighted in this Review. In addition, this Review also brings out the recent research trends on ESSs, which include novel and significant innovations, achievements, and developments around ESSs.

The analysis of innovative design and evaluation of energy storage system based on Internet of Things

The analysis of innovative design and evaluation of energy storage system based on Internet of Things

Performance evaluation of energy storage system coupled with flat plate solar collector using hybrid nanofluid of CuO+Al2O3/water

Charging of energy storage system using flat plate solar collector (FPSC) is very popular in recent years. FPSC for the thermal energy storage system (TESS) using hybrid nanofluid was discussed in this manuscript. Hybrid nanofluid of CuO+ Al2O3/water was used as heat transfer fluid (HTF) for solar collector which is coupled with thermal storage and analysis carried out. To predict the thermal performance of energy storage system using hybrid nanofluid, a stainless steel container was used for thermal storage. CuO+Al2O3/water hybrid nanofluid were used to investigate the thermal performance of the solar collector and energy storage system. The FPSC is used for experimental investigation on the stainless steel container TESS. The flat plate solar collector is found more efficient than the other conventional type solar collector using hybrid nanofluid. The temperature of stainless steel container thermal energy storage system was reached to 87°C by using hybrid nanofluid in FPSC.

Optimal sizing and placement of energy storage system in power grids: A state-of-the-art one-stop handbook

• Critical review on ESS planning covering ESS selection, modelling and algorithms. • Thorough discussion on requirements of ESS techniques in different sub-systems. • Systematic methodology of problem formulation for optimal ESS planning. • Comparison of algorithms focusing on optimization and uncertainty management. • Research directions on ESS planning considering demands in future grid. Energy storage system (ESS) has been expected to be a viable solution which can provide diverse benefits to different power system stakeholders, including generation side, transmission network (TN), distribution network (DN) and off-grid microgrid. Prudent ESS allocation in power grids determines satisfactory performance of ESS applications. Optimal sizing and placement of ESS are crucial for power quality improvement of DN and transmission system protection setting. To solve this issue, considerable researches have been done either in modelling or algorithms. However, various options and complex characteristics in different sub-systems make it difficult to appraise a specific method for an ESS application, while the existing reviews only focus on ESS applications in DN. This paper provides a critical one-stop handbook related to one hundred and four methods in six categories covering all kinds of networks and tailored applications. Meanwhile, a systematic methodology is presented with an extensive latest literature review, including ESS selection, evaluation criteria, modelling and solution methods. Particularly, different technical requirements and modelling methods of different sub-systems are outlined. Besides, pros and cons of optimization methods are thoroughly analysed and compared to reveal state-of-the-art studies. Finally, key points in optimal ESS sizing and placement are concluded along with recommendations for future research.

Market Evaluation of Energy Storage Systems Incorporating Technology-Specific Nonlinear Models

A generic constant-efficiency energy flow model is commonly used in techno-economic analyses of grid energy storage systems. In practice, charge and discharge efficiencies of energy storage systems depend on state of charge, temperature, and charge/discharge powers. Furthermore, the operating characteristics of energy storage devices are technology specific. Therefore, generic constant-efficiency energy flow models do not accurately capture the system performance. In this work, we propose to use technology-specific nonlinear energy flow models based on nonlinear operating characteristics of the storage devices. These models are incorporated into an optimization problem to find the optimal market participation of energy storage systems. We develop a dynamic programming method to solve the optimization problem and perform two case studies for maximizing the revenue of a vanadium redox flow battery (VRFB) and a Li-ion battery system in Pennsylvania New Jersey Maryland (PJM) interconnection's energy and frequency regulation markets.

Performance Evaluation of Energy Storage Systems for Different Drive Cycles in Hybrid Electric Vehicle

The important control parameters for the hybrid electric vehicle are the lower and upper limit of state of charge (SOC). The vehicle’s onboard energy system defined the fuel economy and the electric range thus during the period at which the power demand is less, we will allow the ESS to get charged and they will get discharged during the period of high-power demand. ESS acts as the catalysts as they help in boosting the energy requirements. In HEVs, maintaining high energy density is a necessity while demanding higher peak power as well thus this results in doubling the incremental cost of the vehicle if approx. 15 % of all electric range is demanded. The SOC of the vehicle directly affects the economy and the emission rates. In this work the parallel HEV is modelled by using ADVISOR and Different SOC limits are taken for testing the performance and fuel economy for the same designed driving cycle. With the simulation results we will be able to specify best upper and lower limits of SOC such that vehicle will achieve best fuel economy and emission performance. The simulation is performed by taking repetitive velocity profiles (drive cycles) of four different curves i.e. UDDS, ECE, FTP and HWFET. The SOC and emission curves are observed for these different drive cycles and the results having emission rates for HC, CO and NOx (in g/miles) are tabulated.

A Study on Capacity Credit and ESS Evaluation for WTG and Multi-ESS in Power System

This paper proposes a new method for evaluating Effective Load Carrying Capability (ELCC) and Capacity Credit (CC) of a power system including Wind Turbine Generator (WTG) combined with Multi Energy Storage System (ESS). The WTG can only generate electrical power when the wind is available. Because of the fluctuation of wind speed, WTG generates intermittent power. In the reliability viewpoint of power system, the intermittent power of WTG is similar to the probabilistic characteristics based on the on-off power due to the mechanical availability of conventional generators. Therefore, high penetration of WTG will cause difficulties in power system operation. The high penetration of numerous and large capacity WTG can risk the power system adequacy, quality, and stability. This study develops a new method to assess how much the penetration of WTG can be extended when WTG is combined with ESS. This paper demonstrates various case studies of ELCC and CC of a power system containing WTG combined with Multi ESSs using a model system similar to Jeju island power system in Korea.

Economic Evaluation of ESS in Urban Railway Substation for Peak Load Shaving Based on Net Present Value

In this paper, we estimate the economic benefits of Energy Storage Systems (ESSs) for peak load shaving in an urban railway substation using the annual cost. The annual investment cost of ESSs is estimated using Net Present Value (NPV) and compared with the cost reduction of electricity by the ESS. The optimal capacities of the battery and Power Converting System (PCS) are determined for peak load shaving. The optimal capacity of the ESS and the peak load shaving is determined to maximize the profit by the ESS. The proposed method was applied to real load data in an urban railway substation, and the results show that electric power costs can be reduced. Other aspects of the ESS, such as the lifetime and unit price of the battery, are also investigated economically.

Specific duties and economic evaluation of energy storage systems in electric power systems

Specific duties and economic evaluation of energy storage systems in electric power systems