ESS Operation Research Articles

Smart Management of Energy Storage in Microgrid: Adapting the Control Algorithm to Specific Industrial Facility Conditions

The article introduces a method for optimizing energy storage system scheduling in industrial microgrids. It employs a PSO-based heuristic algorithm using daily generation and load forecasts. The objective is economic optimization, minimizing energy costs, and maximizing profits. Market energy prices and distributor tariffs are the base of the objective function. An algorithm maintains the plan by controlling storage power based on real-time microgrid measurements, aligning with the intended power exchange curve. Due to PSO’s ability to perform multidimensional optimization, it is possible to find the global optimum of the objective function. To validate the practical applicability of this approach, it is exemplified through its implementation within a real-world industrial microgrid setting. The presented results indicate the method’s effectiveness but also show its weaknesses. For the two considered cases, a decrease in operating costs of 6.7% and 10.8% was achieved, respectively. On the other hand, the best results are obtained for shorter forecasts, which is why the algorithm, despite long planning periods, revises the ESS operation plan whenever there are significant deviations between the forecast and the actual power.

인공지능을 활용한 디지털 트윈 기반 ESS 최적 운영 계획 모델 수립에 관한 연구

Recently, due to the digitalization of power systems, the convergence technology of power systems and ICT has become important, and with the development of operational technologies, the importance of intelligent energy management is increasing. The importance of energy management through intelligent operating technology is emerging. In this paper, a digital twin model simulated by empirical simulation was constructed using the empirical ESS measurement data information collected from the power system. An optimal operation plan model for ESS was established by simulating the state and environment of the system in the virtual space of the digital twin similar to the actual system. It aims to improve the stable operation and efficiency of ESS through rapid situational awareness and correct decision-making by applying a data-based machine learning model rather than an existing optimization-based operation model.

An Operation Strategy of ESS for Enhancing the Frequency Stability of the Inverter-Based Jeju Grid

As environmental pollution deteriorates, the acceleration of decarbonization worldwide is underway. Several countries, including Korea, are incorporating new and renewable energy into existing systems, and various methods of decarbonization are being researched. With changes in the control environment, the expansion of the system linkage of new and renewable energy can cause system instability problems. This paper introduces an operation plan that uses the fast response characteristics of energy storage system(s) (ESS) to improve stability and review system stability as a result of the expansion of new and renewable energy on Jeju Island. Frequency stability was ensured through an analysis of frequency response characteristics in the event of a system accident, and an efficient ESS operation plan was simulated by changing the ESS parameters. Through this simulation, stable ESS operation and hunting in the frequency recovery process were minimized through cooperation between the existing and new ESS via a wide dead-band range and speed adjustment rate correction, and the lowest frequency was improved.

도시철도 부하 패턴 기반 ESS 최대 용량 산정 및 동작 알고리즘 연구

In this paper, we introduce the method of reducing only the morning peak of the ESS and the method of calculating the maximum ESS capacity according to the method of reducing the entire day by using the characteristic that the load of the urban railway substation shows a different load pattern depending on weekdays, weekends, and holidays. Furthermore, an operation method suitable for urban railroad is introduced using the operation algorithm for each of the five points of time of the ESS according to the load pattern. To verify the introduced maximum capacity calculation method and ESS operation algorithm, power analysis program, PSCAD/EMTDC was used.

에너지믹스 및 에너지저장장치를 이용한 제주지역 재생에너지 수용증대 방안

The conversion of renewable energy to global climate change is a desirable change, but the intermittent characteristics of renewable energy create many difficulties in the operation of power systems. In particular, as the share of renewable energy increases and the output of renewable energy is restricted due to imbalance in supply and demand, there are many difficulties not only for system operators but also for renewable energy companies. The increase in the share of offshore wind power, which is highly utilized, is expected to aggravate these difficulties. In particular, in Jeju, where demand for electricity is limited and isolated, many output restrictions have been imposed due to the imbalance in supply and demand due to the increase in renewable energy share. This paper proposes a plan to increase renewable energy consumption in Jeju power system by predicting renewable energy curtailment from 2023 to 2025, and easing output curtailment through energy mix and ESS operation.

Value of deterministic day-ahead forecasts of PV generation in PV + Storage operation for the Australian electricity market

During the last decade, numerous solar forecasting tools have been developed to predict the energy generation of photovoltaic (PV) farms. The quality of solar forecasts is assessed by comparing predictions with measured solar data. However, this methodology does not consider the added value of the forecasts for their applications. As a consequence, what value could be given to the improvement of forecasts considering this evaluation framework?To answer this question, this work compares the value of different operational solar forecasts for a specific application. The aim is to look for relationships between the economic value and the error metrics defined to evaluate the forecast quality.A new generation of large-scale PV plants integrates ESS. The aim is to add flexibility to the injection of the production into the grid and thus to maximize the profit by taking advantage of the possibilities offered by the electricity market, such as energy arbitrage. To optimize the operation of these specific ESS, forecasting of the solar production is of paramount importance. The study case considered in this work is a large-scale PV farm of several megawatts associated with Li-ion batteries in the Australian energy market context.For this specific case study, the results show that the metrics used to evaluate the forecast quality based on the mean absolute error (MAE) have an almost linear relationship with the economic gain brought by applying the forecast. More precisely, an improvement of 1% point in MAE results approximately in an increase of 2% points in economical gain.

A Study on Cloud-based Safety ESS Watchdog System Using Ultra-Compact Wireless Sensor

Background/Objectives: Safety matters are being discussed and countermeasures to prevent various breakdowns/accidents are urgently required. Therefore, we propose a safety management solution for ESS fire monitoring.
 Methods/Statistical analysis: BLE 5.0-based ultra-compact wireless sensor-based edge that can detect off-gas early, as well as measure the temperature, humidity, vibration, and smoke in the golden time of approximately 10 minutes from the occurrence of thermal runaway inside the ESS to a fire. This paper proposes a safety system and an ESS-integrated safety management solution. Findings: It is known that the ESS currently in operation is installed without an integrated control method and a systematic protection system between facilities in order to connect new and renewable energy and to quickly supply the site, so there are many problems. For this reason, various accidents such as reactor failure and fire are occurring in the ESS installed at the actual site. Recently, 22 fires occurred in ESS facilities installed nationwide in 2019, and the government has urgently stopped ESS operation and formed a joint public-private investigation committee to clarify the cause. Among the various causes of ESS fires that have been raised, the ESS design should be considered. This paper reported an edge safety-based on BLE 5.0 that is capable of detecting off-gas and detecting temperature, humidity, vibration, and smoke early in the golden time of approximately 10 minutes from the occurrence of thermal runaway inside the ESS to a fire. A system and ESS integrated safety management solution were proposed. In this study, internal monitoring of an ESS was possible by integrating directly with existing and new ESS. The administrator can observe all conditions on the web through the cloud-based ESS integrated safety management system. Improvements/Applications: This paper analyzed and developed a cloud-based ESS integrated safety management system. It will be helpful in ESS fire management in the future and will be useful in designing artificial intelligence-based safety management solutions.

Aging Cell Detection Method of ESS Base on Operating Data

Lithium based ESS is consist of many battery cells series. Ideally, when many cells degrade at the same rate of life, safety can be maintained when operating the facility. In reality, it shows a difference in internal resistance and capacity for each cell, and it is difficult to estimate the deterioration state for each cell. So it includes a passive cell balancing function based on the BMS voltage to manage the battery, but it is not a fundamental solution. Differences in cell deterioration fundamentally degrade ESS performance and, if used excessively, may lead to fire due to a runaway temperature of the lithium battery.In this paper, proposed a method that can detect a cell with a relatively high deterioration rate among a number of cells and diagnose it step by step based on limited ESS operation data. it is possible to accumulate location information based on a maximum minimum voltage value stored every second by classifying when charging, discharging, and stopping, and extracting a statistically based deterioration cell when a lot of data is accumulated. It is intended to define the IR Ratio and monitor the risk in advance and improve the safety of the ESS when current flows and through preemptive degradation cell detection.

Day-Ahead scheduling of centralized energy storage system in electrical networks by proposed stochastic MILP-Based bi-objective optimization approach

Recently, employing environmentally-friendly devices such as Energy Storage Systems (EESs) and Renewable Energy Resources (RERs) has been one of the remarkable ways to reduce electricity generation cost as well as environmental issues. Due to the stochastic nature of injected power through the RERs resulting from variable weather conditions, serving the devices and systems to the electrical grid in order to alleviate the output fluctuations of these resources should be taken into consideration. Installation of energy storage units can be one of the applicable ways that lessens the power variations of RESs by exchanging the required real power into the network through a day. In the current paper, the day-ahead scheduling of ESS in the presence of wind farm uncertainty has been obtained by implementing the proposed stochastic Mixed Integer Linear Programming (MILP)-based bi-objective optimization approach. The suggested objective functions are the daily electricity generation cost and emission pollutants released through the thermal power plants. Based on the presented framework, a simultaneous cost-emission minimization scheme is carried out by deriving Pareto optimal solutions by epsilon-constraint technique. It is noteworthy that one strategy is required to determine optimal ESS operation according to the decision maker's point of view. Thus, the Fuzzy satisfying method as a selection criterion has been exploited to obtain the appropriate solution by compromising between the objective functions. The case study is the IEEE-30BUS system. According to simulation results derived from implementing the proposed framework, it has been concluded that during off-peak periods of the day, the hourly electricity generation cost and emission are increased. On the other hand, the hourly cost and emission have been reduced during on-peak hours. The daily cost and emission are reduced by employing the energy storage unit. Moreover, peak-shaving and peak-shifting resulting from the suitable ESS operation are illustrated in this paper.

Efficacy and safety of pulmicort repulas-impregnated nasal dressing following endoscopic sinus surgery: a randomized, single-blind, placebo-controlled study

Objective:To investigate the efficacy and safety of pulmicort respulas immerse with nasopore as nasal packing after nasal endoscopic surgery on patients with chronic rhinosinusitis with nasal polyps. Method:This single-blind, randomized study recruit 33 patients diagnosed as chronic rhinosinusitis with polyposis. All of them underwent bilateral endoscopic sinus surgery and randomized to receive pulmicort respulas immersed nasopore in one nasal cavity and saline immersed nasopore contralaterally. Both groups were followed up at 2, 4, 8, 12, 24 weeks after operation. Subjective （VAS score） and objective （Lund-Kennedy score） scores are collected at each time point from both sides of nasal cavity. Result:There are 30 enrolled patients in the study completed the 24-week trial. Both the subjective and objective scores of two groups shows a significant reduction after the ESS operation. The VAS score of the two groups remains roughly unchanged during week 2 to week 24. A statistically significant difference of the Lund-Kennedy score can be detected between the groups from week 2 to week 24. Though the serum cortisol reduced （5.97±4.10） mmol/L vs （12.48±4.33） mmol/L after the surgery, neither group shows any clinical symptoms related with the hypothalamic-pituitary-adrenal axis suppression. Conclusion:This study demonstrated a significant improvement in postoperative healing in nasal cavities receiving pulmicort respulas immersed nasopore as nasal packing following ESS. This method of using budesonide is generally safe for patients with chronic rhinosinusitis with polyposis.

최대 수요 전력 저감을 위한 LSTM 기반 ESS 운영 스케줄링 기법

최대 수요 전력 저감을 위한 LSTM 기반 ESS 운영 스케줄링 기법

Simple Free Use Simulation Software for Buildings with Photovoltaic System and Battery

The paper describes proposed techniques used for simple simulation of a hybrid energy system in a building. An interactive software tool is presented that can be downloaded and used for any purpose free of charge. Based on selected household electrical equipment, solar irradiance, PV system design and ESS parameters an annual simulation is made based on hourly time resolution. The outputs presented in charts as well as tables show the distribution of energy sources (grid, PV), the effect of ESS operation, self-sufficiency of PV system and its utilization of PV throughout the year. The simulation is real-time based so the system design can be easily manually optimized to achieve specific goals (e.g. specified self-sufficiency at minimal costs). As the simulation if based on Excel sheets, it can be easily accustomed by users with specific requirements.

Study on ESS Operation Plan for Energy Reduction in Industrial Customer

Study on ESS Operation Plan for Energy Reduction in Industrial Customer

A Study on the Design and Control Characteristics for Optimum Operation of the PV System-based ESS

A Study on the Design and Control Characteristics for Optimum Operation of the PV System-based ESS

국가적 관점에서 용도별 ESS 적정용량 산정을 위한 운전수리모델 수립에 대한 연구

Around the world are increasing the demand for ESS. Currently, the domestic is expected to benefit by operating ESS. In the domestic, it is expected to benefit from operations of the installed ESS because of the introduction of ESS less capacity. However ESS capacity to the maximum profit occurs is unknown. ESS is different from the charge-discharge characteristics and the reserve to replace, depending on the application. Therefore, it should be established in accordance with the ESS optimal capacity according to the purpose used because it can maximize the quality and efficiency of the electric energy. To the ESS optimal capacity estimation by the purpose used, It should compare the investment cost caused by ESS facility installation and operation cost caused by operating ESS. In this paper, the operation mathematical model for estimating marginal operation costs established. In operation mathematical model, operating cost is considered fuel cost and no-load cost start-up cost. Because no-load cost and start-up cost are not related to cost and power plant output, there are expressed an integer variable costs as a step function.

Electric energy storage design decision method for demand responsive buildings

Electric energy storage is one of the most promising and convenient solutions for energy cost management of buildings by shifting electric loads. This paper investigates electric energy storage (EES) size planning to minimize the total electricity cost of buildings, including investment. This study discusses EES planning considering an EES operation, especially focusing on an economically optimized decision of EES capacity. We first formulate a general electricity cost minimization problem with the electricity bill of buildings and EES cost, and decompose the problem into two parts for EES planning and EES operations. The EES planning algorithm based on the iteration process is proposed considering an ESS operation. The simulation demonstrates that the proposed EES planning can perform close to the optimal exhaustive search algorithm.

Increase in the quality of the prediction of a computational wildfire behavior method through the improvement of the internal metaheuristic

Wildfires cause great losses and harms every year, some of which are often irreparable. Among the different strategies and technologies available to mitigate the effects of fire, wildfire behavior prediction may be a promising strategy. This approach allows for the identification of areas at greatest risk of being burned, thereby permitting to make decisions which in turn will help to reduce losses and damages. In this work we present an Evolutionary-Statistical System with Island Model, a new approach of the uncertainty reduction method Evolutionary-Statistical System. The operation of ESS is based on statistical analysis, parallel computing and Parallel Evolutionary Algorithms (PEA). ESS-IM empowers and broadens the search process and space by incorporating the Island Model in the metaheuristic stage (PEA), which increases the level of parallelism and, in fact, it permits to improve the quality of predictions.

A Study on Using Large-Scale Energy Storage Systems in Automatic Generation Control Operations of the Energy Management Systems

KEPCO has completed the installation and demonstration of a 52 MW battery energy storage system (BESS) for frequency regulation. Especially, 24 MW BESS is for Automatic Generation Control (AGC) in Shin-Yongin substation. Recently, KEPCO Research Institute has operated it connected to EMS of KPX. This paper discussed the operation strategy of EMS through a study on using 24 MW BESS in AGC operation and propose the improvement of AGC target. It is expected that this paper helps a safe and reliable operation and control of ESS for AGC through its continuous update.

경제성 분석을 통한 산업용 수용가의 ESS 설치 용량 산정

In this paper, ESS capacity installed in industrial customer is calculated using economic analysis. To do this, electric charge for industrial customer is analyzed and power management system(PMS) of ESS is selected. Reduction of kW cost and kWh cost are set to 'benefit' according to operation of ESS. Also, installation cost and maintenance cost of ESS are set to 'cost'. Proper ESS capacity is determined as a result of benefit-to-cost(B/C) analysis according to the variation of ESS installation cost. In case study, B/C is analyzed for the specific industrial customer and minimum capacity of ESS to make a profit are proposed for the customer.

A study on the voltage calculation method for ESS operation plan in Hybrid Generation System

The designed hybrid generation system (HGS) not only consider the voltage condition of connection point but also do limit output profile by following the transmission system operator's directions. Therefore, when developing large-scaled system including a number of HGS, appropriate compensation strategy based on the system components and impacts should be formulized with considering inner system's characteristics. The ESS operation plan in HGS should be supported by precise voltage expectation method because the system has large physical areas: it includes almost 150m DC section. Especially, since the previous system is not considering power limiting method at the DC section which is integrated with wave generators, an appropriate ESS compensation could provide a lots of solutions such as power control and quality issue. In this paper, an active power control algorithm with expected voltage based on the DC power flow is introduced, and imposed to the simulation process that is performed on EMTDC environment. Further, the comparison with the normal control process is carried out based on the composed layout in ongoing project.