Modeling and simulation of an isolated hybrid micro-grid with hydrogen production and storage

Abstract This work relates the study of system performance in operational conditions for an isolated micro-grid powered by a photovoltaic system and a wind turbine. The electricity produced and not used by the user will be accumulated in two different storage systems: a battery bank and a hydrogen storage system composed of two PEM electrolyzers, four pressurized tanks and a PEM fuel cell. One of the main problems to be solved in the development of isolated micro-grids is the management of the various devices and energy flows to optimize their functioning, in particular in relation to the load profile and power produced by renewable energy systems depending on weather conditions. For this reason, through the development and implementation of a specific simulation program, three different energy management systems were studied to evaluate the best strategy for effectively satisfying user requirements and optimizing overall system efficiency

Multi-objective thermo-economic optimization of biomass retrofit for an existing solar organic Rankine cycle power plant based on NSGA-II

Non-dominated sorting genetic algorithm (NSGA-II) was deployed in this paper for multi-objective thermo-economic optimization of biomass retrofit for an existing solar organic Rankine cycle (ORC) power plant. The existing plant consists of a field of linear Fresnel collectors (LFC), integrated directly with two-tank thermal energy storage (TES) system, which interfaces with ORC power block. The real solar-ORC plant currently runs at Ottana, Italy, albeit with some technical challenges basically due to inconsistent availability of solar irradiation. In order to upgrade the plant, a novel scheme had been proposed to install a biomass unit in parallel to the solar field, such that both LFC/TES and biomass furnace could directly and independently satisfy fractional thermal input requirement of the ORC. Being a retrofit system, existing design parameters of all the already operating units were imposed as equality constraints in this study, and the combustion excess air, as well as pinch point temperature difference of furnace heat exchangers that optimize the hybrid plant were investigated. Results showed that biomass mass flow rate of 0.133 kg/s and investment cost rate of 57 €/h are optimal for the studied biomass retrofit scheme. At this optimum point, excess air was obtained as 56%, furnace heater pinch point temperature difference as 28.8 °C and air pre-heater pinch point temperature difference as 38.5 °C. More generally, results showed that excess air value of less than 100%, furnace heater pinch point temperature difference of less than 80 °C, and air pre-heater pinch point temperature difference of less than 80 °C would optimize the studied biomass retrofit scheme. Keywords: Solar-Biomass power plant, Organic Rankine cycle, Hybrid renewable energy, Multi-objective optimization, Non-dominated sorting genetic algorithm (NSGA-II), Power plant retrofi

Use of weather forecast for increasing the self-consumption rate of home solar systems: An Italian case study

With the aim of increasing the self-consumption rate of grid-connected Photovoltaic (PV) home systems, two main options can be implemented: the inclusion of an energy storage system, in particular a battery bank, and the adoption of a Demand Side Management (DSM) strategy. However, both the reshaping of the load consumption curve with the displacement of deferrable loads and the optimal management of the battery bank require estimation of the daily PV generation profile. The assessment of the on-site energy production can be carried out based on weather forecast data. However, the latter are characterized by uncertainty, which may affect the achievable self-consumption rate. This work investigates the influence of weather forecast errors on the performance of home PV systems equipped with a battery bank and characterized by a certain share of deferrable loads. Two different weather forecast services are considered, referring to the annual meteorological conditions occurring in Rome, and energy consumption data for 150 different households are analysed. The self-consumption rate is maximized by solving a suitable optimization problem, while different combinations of relative battery capacity, PV-to-load ratio and share of deferrable loads are considered. Two different approachesâ\u80\u94deterministic and stochasticâ\u80\u94are adopted and compared with an ideal approach where the PV generation profile is perfectly forecasted. The results show that the adoption of the deterministic approach leads to a reduction in the achievable self-consumption rate in the range of 0.5â\u80\u934.5% compared to the ideal approach. The adoption of a stochastic approach further reduces the deviations from the ideal case, especially in the case of consumption profiles with a high share of deferrable loads. Finally, a preliminary economic analysis proves that the use of a battery bank is not yet a cost-effective solution and a price reduction of the current battery prices is therefore required

Pumps as turbines for pumped hydro energy storage systems - A small-size case study

Pumped Hydro Energy Storage (PHES) technology has been used since early 1890s and is, nowadays, a consolidated and commercially mature technology. PHES systems allow energy to be stored by pumping water from a lower-to a higher-level reservoir. Subsequently, this energy can be released through a turbine placed in a penstock, which connects the two reservoirs, to produce energy. Although these plants have historically been employed at large power scales (in the order of hundreds of MW), in recent years, micro- and small-scale plants are becoming more interesting, due to their possibility of being integrated with renewable energy systems (RES) used in autonomous island grids. Capital costs associated with hydraulic machines used in PHES systems represent the most critical economic factor, which can be mitigated by using commercial centrifugal pumps in reverse mode (Pumps as Turbines, PATs) in place of small hydro turbines. These expected economic benefits must be weighed in each specific case study, with some drawbacks related to the use of PATs, mainly associated to a lower round-trip efficiency with respect to specifically designed pumps and turbines. In this work, a small-scale PHES plant has been studied coupled to an existent photovoltaic system for the integration in the electric grid of a small island in Southern Italy. Two different PHES outlines have been compared based on techno-economic considerations. The former is a typical PHES system composed of both pumps and a turbine, while the latter uses only an array of parallel pumps which work also in reverse mode. The analysis demonstrates the feasibility of integrating a photovoltaic and PHES plant, which results in a lower cost of electricity production, while PHES performance in the PAT-based outline results penalized by the lower efficiency of PATs with respect to the hydraulic turbine

Integration of pumped thermal energy storage systems based on Brayton cycle with CSP plants

In this paper, the integration of Brayton cycle PTES systems with Concentrating solar power (CSP) plants is proposed and investigated. Specific mathematical models were developed to simulate the PTES and CSP sections as well as to calculate the thermal profiles of the different TES storage tanks during the charging and discharging phases. As case study, an integrated PTES-CSP system using argon as working fluid and characterized by a nominal power of 5 MW and a nominal storage capacity of 4 equivalent hours of operation is considered. The influence of the main design parameters on two performance indexes, namely, the charge-to-discharge efficiencies of the sole PTES section and the integrated PTES-CSP plant, have been investigated. The results demonstrate that the use of high values of pressure ratio is beneficial for the charge-to-discharge efficiency of the integrated plant, even if too high operating pressures could be detrimental for the design of the solar receiver and the high temperature storage tank. The low temperature TES is a critical component due to its cryogenic operating conditions, but an increase in the minimum temperature should be achieved by increasing the inlet temperature of the LP compressor. A sensitivity analysis on the compressor and turbine efficiencies, maximum and minimum temperatures, circuit pressure drop and working fluid has been carried out. Finally, a feasible design of the PTES-CSP system with a PTES roundtrip efficiency of nearly 52% and a charge-to-discharge efficiency of the integrated PTES-CSP plant of about 36% was proposed

Operating performance of a Joule-Brayton pumped thermal energy storage system integrated with a concentrated solar power plant.

[EN]The expected performance of an innovative Pumped Thermal Energy Storage (PTES) system based on a closedloop Brayton-Joule cycle and integrated with a Concentrated Solar Power (CSP) plant are analysed in this study. The integrated PTES–CSP plant includes five machines (two compressors and three turbines), a central receiver tower system, three water coolers and three Thermal Energy Storage (TES) tanks, while argon and granite pebbles are chosen as working fluid and storage media, respectively. A sizing of the main components of the integrated plant has been firstly carried out for the design of an integrated PTES-CSP plant with a nominal net power of 5 MW and a nominal storage capacity of 6 equivalent hours of operation. Specific mathematical models have been developed in MATLAB-Simulink to simulate the PTES and CSP subsystem in different operating conditions, and to evaluate the thermocline profile evolution within the three storage tanks during/charging and discharging processes. A control strategy has finally been developed to determine the operating modes of the plant based on the grid service request, the solar availability, and the TES levels. The performance of the system during a summer and a winter day have been analysed considering the integration of the PTES subsystem in the Italian energy market for arbitrage. Results have demonstrated the technical feasibility of the hybridization of a PTES system with a CSP plant and the ability of the integrated system to participate to energy arbitrage, although a lower exergy roundtrip efficiency (about 54 %) has been observed with respect to the sole PTES system (about 60 %)

Life Cycle Analysis of a Hydrogen Valley with multiple end-users

This paper aims to evaluate the environmental impact along the overall life cycle of the various components of a Hydrogen Valley with multiple end-users fed by green hydrogen. As case study, a hydrogen valley including a MW-scale electrolyser powered by different percentages of energy supplied by a wind farm and/or a photovoltaic plant, and an H2 storage section is considered. The H2 produced is used to feed a fleet of fuel cell electric vehicles and a stationary fuel cell, while the residue H2 is injected in a natural gas pipeline considering a maximum safety limit of 5%vol. When the safety limit is reached, the H2 overproduction can be used to produce biomethane through a biological hydrogen methanation process. With the aim of analysing the actual contribution of these hydrogen-based ecosystems towards more sustainable energy systems, a Life Cycle Analysis of the hydrogen valley is carried out. The results show that the final use of hydrogen for fuel cell electric vehicles produces the most valuable environmental benefits. Moreover, Hydrogen Valley solutions integrated with photovoltaic plants allows to maximize the use of H2 in fuel cell electric vehicles and therefore are the most valuable choice from an environmental point of view

An innovative two-stage machine learning-based adaptive robust unit commitment strategy for addressing uncertainty in renewable energy systems

Confronting the challenge of intermittent renewables, current unit commitment practices falter, urging the development of novel short-term generation scheduling techniques for enhanced microgrid stability. This study presents an adaptive robust unit commitment approach using machine learning techniques for renewable power systems, computing the Calinski-Harabasz index to identify prediction inaccuracies related to intermittent sources. The uncertainties are subsequently grouped together using the spatial clustering tool, and the average density of the K-means distribution is calculated. The clustering of points in space, considering noise, discrete uncertainty in renewable energy sources, and outliers within the comprehensive uncertainty set, is addressed via a nonparametric algorithm. The implementation of established methodologies and frameworks, in conjunction with density-based spatial clustering of applications with noise, introduces an innovative method for vulnerability clustering. This methodology guarantees that every cluster aligns with data pertaining to vulnerabilities of renewable energy sources. The performance of the suggested method is showcased by conducting experiments on modified IEEE 39-bus and 118-bus test systems that use intermittent wind power. The results demonstrate that the proposed framework may lower the cost of robustness by 8–48% compared to traditional robust optimization techniques. The results of stochastic programming showed that the optimized system with a stable economic organization would have 75 % faster calculations

Robust optimization for the preliminary design of solar organic Rankine cycle (ORC) systems

Organic Rankine cycle (ORC) powered by solar energy is a viable and effective option for a high efficiency conversion of solar thermal energy into electricity at a distributed scale but recurring fluctuations of the thermal energy often force solar-based ORC systems to operate at part-load conditions. With the aim of including the effects of the expected variations of the heat source and heat sink characteristics, even during the design phase, a novel optimization approach for the preliminary design of ORC systems integrated with concentrating solar collectors is presented and analysed. In particular, the minimization of the expected levelized cost of energy (LCOE) of the ORC unit is chosen as an objective function, while the generation of various scenarios is proposed to face the expected fluctuations on the heat source mass flow rate and temperature and cooling inlet temperature. In this way, the expected off-design performances are involved during the design step, giving robustness to the optimal design solution. The proposed methodology is tested by referring to the solar ORC system configuration of the Ottana solar facility. Firstly, the effect of a robust optimization on the preliminary ORC design is investigated by considering an increased number of scenarios for each of the three most significant ORC input variables (heat source mass flow rate and temperature and ambient temperature). Subsequently, the proposed methodology was applied to an ORC design case by considering a concurrent variation of the three variables and three different working fluids. The results of this study demonstrate that a multi-scenario approach drives towards an ORC configuration with lower performance under design conditions, but less sensitive to the variation of the main inputs. Less expensive solutions are therefore achieved by the proposed methodology, but the annual energy production obtained is comparable with those achieved by adopting a single scenario approach, with a consequent reduction of the LCOE