Mathematical modeling of resilient and sustainable renewable energy integration with hybrid energy storage, emission constraints, and extreme weather conditions

An allocative method of hybrid electrical and thermal energy storage capacity for load shifting based on seasonal difference in district energy planning

<p>The viability of low carbon power systems (LCPS) is becoming more realistic. However, such energy systems present serious challenges in becoming a reality. One of the most important problems is related to the inherent variability of renewable sources, which represent a risk for these systems. Although these systems may include methods to minimize these risks (backup plants, improved interconnection, etc.), these solutions may not be sufficient in extreme weather conditions, in particular, in the so-called compound extreme events. These events are characterized by the simultaneous occurrence of several hazards, generally associated with complex interactions between a wide range of meteorological processes acting on different temporal and spatial scales. In the context of LCPS analysis, compound events can be associated with periods with below normal solar and/or wind power generation and above normal demand. The occurrence of such events may overwhelm the capacity of LCOP systems in the future, thus causing socially significant impacts. In this work, the occurrence of compound extreme weather events related to wind and solar power generation in Spain are identified and the meteorological conditions that cause them described. The study is part of the MET4LOWCAR Spanish project, that aims at demonstrating the benefits of the design of the LCPSs that accounts for the regional weather and climatic patterns of both solar and wind renewable resources, using the Spanish territory as a testbed.</p><p> </p><p>The study is carried out based on real data on daily demand, wind and solar generation provided by the Spanish TSO and corresponding to the 2008-2020 period. Three different types of events were analyzed: compound solar/wind events (below normal solar/wind and above normal demand) and compound solar and wind events (below normal wind and solar and above normal demand). Specific threshold were used to identify these events. The study is conducted using normalized time series, at different periods (1, 5 and 15 days) and separately for each season of the year. The weather patterns associated with the compound events were analyzed using composite analysis by means of ERA-5 reanalysis data.  Results showed firstly, that while compound events are relative frequent for short periods (1 and 5 days), very long events (15 days) are much rarer. In addition, a marked seasonality of the events occurrence is observed, with a peak during the winter season. It was also found that compound event related to wind power generation anomalies are more frequent and intense. Many events were found associated with the presence of negative/positive centers of geopotential heights anomalies roughly located over Portugal/Great Britain, although the intensity and location of the centers varies along the year. Finally, some conclusion regarding the optimal design of a reliable LCPS for Spain are derived and discussed.</p><p> </p><p> </p>

An analytical method for identifying synergies between behind-the-meter battery and thermal energy storage

A multi-objective resilience-economic stochastic scheduling method for microgrid

Battery electric vehicles suffer from significant range reduction in extreme cold weather conditions, largely due to the requirement of cabin heating and reduced battery performance. Since heating can require as much energy as the powertrain itself, improving the vehicle thermal energy management can have a substantial impact on range in cold driving conditions. In this paper, sensible and latent thermal energy storage (TES) methods are analyzed in order to improve heating performance and vehicle range in mild to cold weather conditions. To investigate the benefits of TES in electric vehicles, a model was developed in AMESim to simulate cabin heating and its transient interaction with the vehicle's energy systems during a given drive cycle. A thermal energy storage system was developed in the powertrain coolant loop which was integrated with an electric heater and a heat exchanger used for cabin ventilation. In addition to sensible storage, latent thermal storage was also investigated due to its ability to store energy at near constant temperatures. According to the simulation results, a thermal storage can increase the range close to 25%. This benefit is heavily dependent on the storage volume, storage initial temperature, and ambient temperature.

Hybrid energy storage can enhance the economic performance and reliability of energy systems in industrial parks, while lowering the industrial parks’ carbon emissions and accommodating diverse load demands from users. However, most optimization research on hybrid energy storage has adopted rule-based passive-control principles, failing to fully leverage the advantages of active energy storage. To address this gap in the literature, this study develops a detailed model for an industrial park energy system with hybrid energy storage (IPES-HES), taking into account the operational characteristics of energy devices such as lithium batteries and thermal storage tanks. An active operation strategy for hybrid energy storage is proposed that uses decision variables based on hourly power outputs from the energy storage of the subsequent day. An optimization configuration model for an IPES-HES is formulated with the goals of reducing costs and lowering carbon emissions and is solved using the non-dominated sorting genetic algorithm II (NSGA-II). A method using the improved NSGA-II is developed for day-ahead nonlinear scheduling, based on configuration optimization. The research findings indicate that the system energy bill and the peak power of the IPES-HES under the optimization-based operational strategy are reduced by 181.4 USD (5.5%) and 1600.3 kW (43.7%), respectively, compared with an operation strategy based on proportional electricity storage on a typical summer day. Overall, the day-ahead nonlinear optimal scheduling method developed in this study offers guidance to fully harness the advantages of active energy storage.

Multi-stage distributionally robust optimization for hybrid energy storage in regional integrated energy system considering robustness and nonanticipativity

Digitalization is not only a source of development and innovation, but also carries a risk related to the growing number of threats in cyberspace—so-called cyber risk. Any significant disruption in cyberspace, whether global or local, will have an impact on the security of business transactions, a sense of security for citizens, the efficiency of public sector institutions, the course of production processes and services, and consequently on national security in general. Modeling extreme events in the area of cyber risk may be used in determining the level of capital necessary to cover financial losses resulting from low-probability high-impact (LPHI) events. We conduct an analysis of the tail distributions, using univariate extreme value theory. In particular, we adopt the peak-over-threshold (POT) by Generalized Pareto Distribution (GPD) approach for exceedances (tails). Moreover, we applied another approach to extreme risk modelling—fitting a spliced distribution. The splicing of a Mixed Erlang distribution for the body and an extreme value distribution (Pareto or GPD) for the tail as well as mixtures of gamma/log-normal/Weibull distributions with GDP are considered. This approach overcomes the subjectivity of manual threshold selection, because it can be estimated as a parameter. We compare the results of fitted distributions and draw conclusions based on VaR’s estimates for each analyzed models. We found that the GPD model has proven its superiority over spliced distributions in terms of goodness-of-fit and accuracy of VaR estimations. Therefore we conclude that the GPD is the most recommended distribution to model extreme risk measures (VaR, ES). VaR and ES indicate the level of risk capital that should be carried by a company in case of LPHI cyber event.

Research on frequency modulation capacity configuration and control strategy of multiple energy storage auxiliary thermal power unit

Magnesium sulphate hybrids with silica gel and activated alumina for thermal energy storage

Building a Renewable Energy System (RES) is a viable way to address resource depletion and accomplish decarbonization. This study presents a hybrid power system that combines wind, solar, battery, and thermal energy storage. It also examines the co-optimization of scheduling and operation for multiple objectives. The hybrid system combines the affordability of thermal energy storage (TES) with the adaptability of batteries to effectively address the issue of intermittent RES. A new approach for integrated operation is offered, which relies on the electrical block's operation limit. The planning-operation co-optimization system considers minimizing the Net Present Cost (NPC) and reducing power supply likelihood todetermine the best operation limit and sizing decision factors. The co-optimization issue is addressed using novel multi-objective decision-making (MO-DM). This approach incorporates the Decision-Maker (DM) preferences data to direct the evolutionary process toward the desired area. In addition, a data-driven prediction model captures the risks and losses associated with wind generation. The case study's findings indicate the following: (1) The data-driven system has a higher level of precision in wind power projection when compared with commonly used physical simulations. (2) The suggested MO-DM exhibits superior integration, variety, and robustness achievement in the DMchosen area compared to others. (3) The combined battery-thermal energy storing structure achieves improved economy and dependability through the optimum organized operation approach, in contrast to using a single energy storage system under various testing constraints.

Electric/thermal hybrid energy storage planning for park-level integrated energy systems with second-life battery utilization

Energy systems are dynamic and transitional because of alternative energy resources, technological innovations, demand, costs, and environmental consequences. The fossil fuels are the sources of traditional energy generation but has been gradually transitioned to the current innovative technologies with an emphasis on renewable resources like solar, and wind. Despite consistent increases in energy prices, the customers’ demands are escalating rapidly due to an increase in populations, economic development, per capita consumption, supply at remote places, and in static forms for machines and portable devices. The energy storage may allow flexible generation and delivery of stable electricity for meeting demands of customers. The requirements for energy storage will become triple of the present values by 2030 for which very special devices and systems are required. The objective of the current review research is to compare and evaluate the devices and systems presently in use and anticipated for the future. The economic and environmental issues as well as challenges and limitations have been elaborated through deep and strong consultation of literature, previous research, reports and journal. The technologies like flow batteries, super capacitors, SMES (Superconducting magnetic energy storage), FES (Flywheel Energy Storage), PHS (Pumped hydro storage), TES (Thermal Energy Storage), CAES (Compressed Air Energy Storage), and HES (Hybrid energy storage) have been discussed. This article may contribute to guide the decision-makers and the practitioners if they want to select the most recent and innovative devices and systems of energy storage for their grids and other associated uses like machines and portable devices. The characteristics, advantages, limitations, costs, and environmental considerations have been compared with the help of tables and demonstrations to ease their final decision and managing the emerging issues. Thus, the outcomes of this review study may prove highly useful for various stakeholders of the energy sector.

Renewable energy resources curtailment problem can be alleviated by utilizing energy storage systems. However, electric energy storage and thermal energy storage are always designed separately, which leads to improper sizing and undesired cost. In order to improve the performance of seaport integrated energy system (SIES) and increase the integration of wind power in seaport microgrid, this paper proposes an optimal algorithm for a hybrid energy storage. In this optimization problem, the economic cost, including the investment cost of energy storage, the electricity purchasing cost, the wind curtailment cost, and the maintenance cost of electric conversion device, is considered with various operation constraints. Furthermore, a mathematical model of SIES is established based on the coupling subsystem with wind power generation, electricity loads and thermal loads. A comparative study of four different scenarios is conducted to ensure the optimal strategy of SIES operation by using the particle swarm optimization algorithm. Numerical results indicate that the proposed method can optimally determine the size of hybrid energy storage system. With the help of optimization algorithm, the total cost of the seaport microgrid is reduced.

As the demand for affordable pollution-free energy goes on increasing, the need for energy storing devices is also escalating rapidly. Energy storage requirements are expected to triple by 2,040. Energy storage systems should be developed using innovative technologies. The current review aims at comparing and assessing energy storage systems, both the current and future systems. Many studies on energy systems discuss economic and environmental challenges and constraints. The storage devices for electrical energy should have high efficiency, high storage time, high capacity, low initial cost, and high energy efficiency. The objective of the current review research is to compare and evaluate the devices and systems presently in use and those anticipated in future. The technologies such as flow batteries, supercapacitors, SMES (superconducting magnetic energy storage), FES (flywheel energy storage), PHES (pumped hydroelectric energy storage), TES (thermal energy storage), CAES (compressed-air energy storage), and HES (hybrid energy storage) are compared and discussed. The results of this study can therefore be helpful for various stakeholders in energy storage sector to sustain environment by the use of pollution-free energy storing devices.