Non-dispatchable Renewable Energy Research Articles

Enhancing micro grid sustainability: Genetic-driven reptile search algorithm based carbon emission and cost reduction strategy

Grid architecture is continuously changing in response to modern energy rules that ensure the integration of more renewable sources to lower the carbon footprint. The integration of non-dispatchable renewable energy sources (RESs) using low voltage grids is a possible alternative to a centralized method. Due to a recent trend, microgrids (MGs) are reducing their reliance on the primary grid by incorporating localized sources of electricity including energy storage devices, micro turbines, and fuel cells. Due to the expanding number of spread generating sources with diverse features, power dispatching schedule for distribution micro grids is becoming more challenging. This study offers a dispatch scheduling method from the perspective of an operator. The primary objective of this study is to employ the Genetic-driven Reptile search algorithm (G-RSA) for the dual purpose of minimizing carbon emissions and reducing costs within each microgrid. Additionally, fewer sale and purchase are made from the primary grid. Transmission losses are consequently reduced.

Geothermal energy exploitation in an island-based 100% renewables strategy. Case study of Tenerife (Spain)

The large-scale integration of non-dispatchable renewable energy must be carefully planned, especially in poorly robust electrical energy systems. Tenerife is the most populated of the islands in the Canary Archipelago (Spain) and has an isolated electrical system. It is envisaged for the horizon of 2040 that the island will have a high contribution of non-dispatchable renewable energies (fundamentally wind and solar photovoltaic). Tenerife also has exploitable high enthalpy geothermal resources. An energy planning model is implemented in this paper based on which different scenarios with high non-dispatchable renewable energy penetration in the island's electrical system are simulated. Geothermal energy is also incorporated in the simulations as a dispatchable renewable energy source, with the power required sized according to the hypotheses of each scenario. The results are compared according to different technical and economic parameters. An evaluation is also made of the influence that the capacity of the electrical system to take on higher non-dispatchable renewable power and the presence of energy accumulation systems might have on the minimization of losses in the non-dispatchable renewable energy capacity factor. The results of the simulated scenarios show that geothermal energy could meet up to 28.8% of the island's electrical energy demand, increasing the stability, flexibility and supply guarantee of system. A 100% renewable system could be possible through the incorporation of this energy source and the planning of energy accumulation systems. In the case study, the economic saving for Spain's electrical system could exceed 400 €million per year.

Beyond price taker: Conceptual design and optimization of integrated energy systems using machine learning market surrogates

Future electricity generation systems must be optimized to provide flexibility that counteracts the variability of non-dispatchable renewable energy sources and ensures the reliability and safety of critical infrastructure, including the electric grid. The current state-of-the-art is to co-optimize the design and operation of integrated energy systems (IES) treating historical or predicted time-series electricity prices as fixed parameters. Recent literature has shown the limitations of this price taker assumption, which neglects how IES optimization decisions influence market outcomes. As such, this paper proposes a new optimization formulation that uses machine learning surrogate models, trained from a library of annual market operation simulations, to embed IES market interactions into the co-optimization problem directly. Using a thermal generator example built in the open-source IDAES computational environment, we show that the price taker approach routinely over-predicts annual revenues by 8% or more compared to a validation simulation, where the proposed approach has a typical relative error of 1% or less.

Correlation Between Costs of Congestion Management and Share of Renewables in the ENTSOE Continental Europe Synchronous Area

The presented research is dedicated to estimation of the correlation between the level of renewable energy sources and the costs of congestion management in electric networks in selected European countries. Data of six countries in North-West European area (Italy, Spain, Germany, France, Poland and Austria) were investigated. Factors considered included grid congestion costs including re-dispatching costs as well as countertrading costs, gross electricity generation, installed capacity of electric generating facilities, installed capacity of electric non-dispatchable renewable energy sources and total electricity consumption. Special attention is paid to the share of renewable energy sources. It is found that the grid congestion costs are not clearly affected by penetration of non-dispatchable renewables in all the analysed countries and therefore a clear mathematical correlation cannot no be extrapolated with the available data. The results of this research show in general a loose dependency of the grid congestion costs on the penetration of renewables and a strong dependency on the total electrical consumption of the country.

Green hydrogen is a necessary component of a grid with an increasing non-dispatchable renewable energy supply

It is very well-known that wind and solar energy are supplied when there are resources, which are continuously changing, and not when demanded by the grid. Thus, in a grid without the supply of dispatchable electricity burning carbon and hydrocarbon combustion fuels, it is indispensable to include very large energy storage and given the variability not only short term within the day but from day to day following seasonality additional to weather, the large energy storage has to be mostly hydrogen. Extremely misleading are the cost assessment of prices of electricity to consumers through a Levelized Cost of Energy (LCOE) without factoring in dispatchability, as dispatchable and non-dispatchable electricity has a different value. Without energy storage, the production by wind and solar in the defect of the grid demand has to be supplied by other energy sources. Similarly, the production in excess would be wasted. This inconvenient truth has already produced increasing prices of electricity for customers. The Australian National Electricity Market data shows as phased with the uptake of wind and solar, in the absence of adequate energy storage, the price of energy supply has grown enormously. Without addressing the energy storage issue, mission net zero is incompatible with having cheap and abundant electricity.

Analyzing the impact of demand response and reserves in islands energy planning

Small Islands usually rely on fossil fuels for their energy supply and face common challenges such as high energy costs and carbon dioxide emissions. For these reasons they represent interesting cases for analysing the transition towards a clean and secure energy system. Nevertheless, integrating non-dispatchable Renewable Energy Sources in the power grid causes stability issues and this is particularly true for island grids. Such issue is not fully considered in long-term energy planning; indeed, an important factor that should be considered in order to ensure the reliability of the grid are Reserves. There are different types of Reserves depending on the reactiveness/response time and the duration of the service. In this paper, primary and secondary reserves have been analysed in order to plan the long-term energy transition of the small island of Favignana, Italy by means of the new version of H2RES, a Linear Programming single-objective optimisation model able to provide a long-term capacity investment and dispatching optimisation. It has been found that biomass generators are favoured to both photovoltaic and wind turbines for their ability to provide reserves and also decrease the unpredictability of the supply. Batteries and Electrolysers are also used mostly for reserve provision.

Multi-Area Frequency Restoration Reserve Sizing

Frequency Restoration Reserves are traditionally sized using deterministic methods. The constant growth in non-dispatchable renewable energy, however, is increasing the importance of probabilistic methods for reserve sizing. In addition, as the geographical scope of reserve sizing expands, overall power imbalance stochasticity is reduced. In this paper, we propose a probabilistic method for shared cross-border frequency restoration reserve commitment and sizing, based on the concept of system generation margin and employing mathematical optimization. The aim is to reduce overall reserve volumes and costs. The cross-border interconnection capacities among countries are taken into account, and the shared uncertainty across interconnections is addressed via a novel robust approach. The method is tested on the cross-border system of south-east Europe that includes 9 countries. 5 different operational scenarios are used and a detailed calculation of the uncertainty distributions in each country is employed. Results show that cross-border shared sizing can significantly reduce overall reserve volumes and costs in a secure way.

Unlocking the Hidden Capacity of the Electrical Grid Through Smart Transformer and Smart Transmission

Power systems are experiencing a rapid and dramatic transformation driven by the massive integration of nondispatchable renewable energy sources, such as wind and solar, and highly variable loads, such as electric vehicles and air conditioning. This challenges existing grid assets, eventually leading to updating them, which, in turn, increases significantly the costs of sustainable technologies. Power electronics is a pivotal technology for electrical power processing for renewable energies and sustainable transportation. By means of “smart” functionalities, power electronics converters already embedded in such applications can also contribute to guaranteeing the overall system’s stable operation. Anyway, this cooperative contribution from distributed devices may be not enough leading to the need for the voltage transformation and power transmission of “system-level” power electronics solutions. In the case of large charging stations, a smart transformer (ST), while, in the case of large solar and wind parks, integration medium- or high-voltage direct current (HVdc) transmissions are system-level solutions. This article wants to review the potential of using such infrastructures to increase the capacity of existing grid assets, avoiding or deferring their upgrade and, hence, reducing the overall costs of renewables integration and the electrification of the transport sector. In fact, the power converters embedded in ST and HVdc can provide fast frequency and voltage response, and precise control of power flow acting at the system level much more effectively and feasibly for system operators as the distributed power converters embedded in several small sources and users. This article reviews, for the first time, these two key power electronics “system-level” solutions together—ST and HVdc—starting from their basic functionalities and showings how they can go beyond them, showing how, with grid-forming functionalities, they can offer new “smart grid” tools to enhance the capability of the existing electric grid infrastructures.

A correct perspective for hydrogen from engineered diagenesis

Wind and solar photovoltaic electricity production have already reached very low levels of levelized cost of energy (LCOE). Electrolyzers have already reached high efficiencies which are further improving, while costs are dramatically reducing. They are commercial products. Green hydrogen (H2) is the product of excess wind and solar electricity, specifically electricity that will be otherwise wasted, without the huge energy storage needed presently almost completely missing. By growing the installed capacity of wind and solar power plants, there will be a non-dispatchable production by wind and solar more often in excess, but sometimes also in defect, of the grid demand, in presence of limited energy storage. H2 is one of the key energy storage technologies needed to ensure grid stability. Production of H2 above what is needed to stabilize the grid significantly helps in applications such as land, and sea but especially air transport where the storage of energy onboard in a fuel is preferable to the storage of energy as electricity into a battery. The engineered diagenesis for H2 is unlikely better than green hH2. Apart from being a nice idea to be proven workable, with a technology readiness level (TRL) presently of zero, and thus impossible to be objectively compared with commercial products, the engineered diagenesis for H2, even if possible, also does not help with non-dispatchable renewable energy production. The concept may also have negative environmental aspects similar to fracking which have not been considered yet, and also bear huge economic costs in addition to environmental. Here we review the pros and cons of this novel technology, which once proven workable, which is not the case yet, should be considered as a possible way to complement rather than replace green H2 production.

A thermodynamic-based mixed-integer linear model of post-combustion carbon capture for reliable use in energy system optimisation

Assessing the role of carbon capture in energy systems dominated by non-dispatchable renewable energy sources requires a reliable and accurate model. However, carbon capture models used in complex systems optimisation are often very simplified. Therefore, we developed a mixed-integer linear model of post-combustion carbon capture starting from rigorous thermodynamic modelling in Aspen Plus. The final model decides the size and the operation of the capture process and returns the cost and energy requirements as a function of the CO2 concentration and the flow rate of the treated flue gas. Validation against actual plant data (Petra Nova) showed excellent accuracy with a deviation in total CO2 captured of just 2%. By applying the model to an exemplary case study, we show that it allows for co-optimising renewables deployment and carbon capture design and operation for a gas turbine, thus opening opportunities to explore new system designs of practical added value.

Butane-based heat pump for advanced GTCC applications: static and dynamic model validation

The Thermochemical Power Group (TPG) of the University of Genoa is investigating innovative solutions to increase the flexibility of gas turbine combined cycles (GTCC) and extend their operative range by integrating large size high performance heat pumps. Achieving this goal would make GTCCs more competitive in the future energy market, which will be characterized by a heavy presence of non-dispatchable renewable energy sources.Within this framework, the authors designed and built a new experimental facility to emulate advanced GTCCs at laboratory scale, integrating a 100 kWel micro gas turbine (MGT), a 10 kWel heat pump (HP) and a 180 kWh cold thermal energy storage (TES), with scale-up equations and dynamic models, capable of hardware-in-the-loop tests.The focus of this article is on the HP, which uses n-butane (R600) as working fluid and can be used both to heat and cool down the MGT compressor intake. The HP features one superheater and a 6-cylinder reciprocating compressor, which rotational speed can be continuously varied from 900rpm to 1800rpm.A dynamic model of the HP was developed in TRANSEO, with dedicated Matlab-Simulink® models. This model includes all the components of the HP closed loop, making it possible to simulate its performance and monitor all the main process parameters, such as compressor operation and condensing pressure. This model can be used to simulate the HP in various conditions, including part-load and transient operations, and to aid the design of the advanced GTCC control system. The evaporator and condenser models solve a system of non-linear equations to compute pressure, temperature, and distribution of the different phases of the working fluid along the heat exchangers. Such phase distribution is computed following a moving boundary approach.An experimental campaign was carried out to collect data regarding the stationary performance of the HP. Values of COP and thermal power were analysed as a function of compressor speed and pressure at the condenser, keeping the conditions at the evaporator constant. Then, its transient behaviour was characterized, observing its response to step changes of both evaporator and condenser thermal loads. The model was then successfully calibrated and validated on both stationary and transient data, showing good accuracy.Based on these results, it will be possible to integrate the HP model within larger system simulation tools. Having an accurate digital twin of the whole GTCC integrating HPs and TES will make possible to develop and verify complex control logics on many different scenarios, relying on a safe model-in-the-loop setup, before actual implementation in the field.

The Status Quo and Future of Hydropower in Slovenia

Slovenia is a Central European country with a long history of hydropower. This paper gives a brief introduction to the current status of hydropower utilization and informs about some selected successful examples of hydropower plant operation. One such example is fish passage and flood risk reduction on the lower reaches of the Sava River at the Brežice hydroelectric power plant, taking into account a complex of morphological, hydrological, hydraulic, and anthropogenic factors. Future development is considered against the background of the National Energy and Climate Plan, which does not envisage any significant expansion in the capacity or function of the hydropower sector. The envisaged capacity increase is from the current 4430 GWh to around 4580 GWh by 2030. It is shown that the current energy storage capacity of Slovenia’s only pumped storage plant will be sufficient to offset the introduction of new non-dispatchable renewable energy sources by 2030. By around 2028, the country will have a need for electrical energy storage from renewable energy sources, reaching a modest total of only 6140 MWh per year. However, by sticking to the unambitious National Energy and Climate Plan, Slovenia will miss the opportunity to remain self-sufficient in electricity generation and significantly increase its share of renewable energy sources. The National Energy and Climate Plan aims to increase the share of renewable energy in total energy generation from 25% in 2020 to 27% by 2030.

Biosynthesis of zinc oxide-cobalt oxide nanocomposite as electrode material and its performance evaluation for the sustainable hybrid supercapacitor energy storage devices

Novel energy storage techniques and systems have gained increasing importance in recent times to overcome the variability in the output of non-dispatchable renewable energy sources. Supercapacitors are energy storage systems that have attracted considerable attention from various stakeholders. However, the performance of an effective supercapacitor energy storage system depends mainly on the electrochemical behavior of the electrodes, and the methods used to fabricate the electrode materials. Sustainable methods for the fabrication of electrode materials such as green synthesis have recently attracted researchers. In this work, a method is proposed to synthesize zinc oxide and cobalt oxide nanocomposite using green synthesis to take advantage of their superior electrochemical properties and stability. Evaluation of the morphological and electrochemical performance of the fabricated nanocomposite showed good results. Further, the electrode material fabricated using the synthesized nanocomposite has shown energy density values in the range of 3.8 Wh/kg to 9.54 Wh/kg for the power density values of the range 3000 W/kg to 375.3 W/kg for the different chosen current densities. A retention capacity of approximately 85% was observed even after 5000 cycles which is one of the most important features of supercapacitors. Thus, green synthesis with its intrinsic advantages over chemical methods is expected to be a promising approach for the fabrication of electrode materials for supercapacitors in sustainable energy storage applications in the future.

Contribution for the roadmap of hydraulic short circuit implementation: Case of Grand-Maison pumped storage power plant

The objectives of the 2050 energy policy based on the decarbonization of the electric power networks generate drastic changes for grid balancing with a massive integration of non-dispatchable Renewable Energy Sources. Hydroelectric power plants already significantly support electricity power system flexibility with innovative solutions such as variable speed units, fast frequency control, fast generating to pumping modes transition, high ramping rate, inertia emulation, etc.For pumped storage power plants (PSP), a quick solution to increase the flexibility without large investment is to operate the power plant in hydraulic short circuit (HSC) mode. This technological solution is simple to implement, but requires an in-depth study of various technical aspects among which the hydraulic transients of the new operating modes is of high importance from the installation’s safety perspective. In the framework of XFLEX HYDRO H2020 European research project, the exploitation of this solution is under implementation at Grand-Maison PSP. Located in the French Alps, Grand-Maison PSP is equipped with 8 reversible multi-stage Francis pump-turbines and 4 Pelton turbines, for a total installed capacity of 1800MW, thus being the largest PSP in Europe and one of the major PSP in the world. The waterway includes a headrace tunnel, a headrace surge tank, 3 parallel penstocks feeding the 12 units operated under a maximum gross head of 955mWC.In this paper, after a description of the general HSC considerations, the 1D model of the Grand Maison PSP and the related validation are presented. Finally, the most critical load cases in HSC operation are described to identify the potential hydraulic transient issues, such as extreme water levels in the upstream surge tank, maximum static pressure along the pressure shaft and minimum static pressure along the tunnels. The analysis performed for Grand Maison PSP is a contribution to the roadmap for the implementation of HSC operation in pumped storage power plant and will be made available as a public deliverable of the XFLEX HYDRO H2020 European research project.

A Novel Energy Storage System Based on Carbon Dioxide Unique Thermodynamic Properties

Abstract This paper focuses on the thermodynamic performance and techno-economic assessment of a novel electrical energy storage technology using carbon dioxide as a working fluid. This technology, named CO2 battery and recently patented by Energy Dome SpA., addresses an energy market which has a great need for energy storage solutions able to handle the increasing share of nondispatchable renewable energy sources like photovoltaic and wind energy. After a brief introduction, the present study presents the concept of CO2 batteries and their operation. Then the detailed numerical model developed for the accurate calculation of system round trip efficiency is presented with the adopted assumptions and the optimization routine description. Results on the reference case and following sensitivity analysis confirm a round trip efficiency of around 77% (±2%) which makes CO2 batteries a very promising technology with respect to other energy storage systems based on thermodynamic cycles like compressed air and liquid air energy storage thanks to the high performance and the easiness of installation. Finally, calculation of system footprint, capital investment cost and levelized cost of storage are discussed.

Frequency control in standalone renewable based-microgrids using steady state load shedding considering droop characteristic

This paper presents a new systematic scheme for designing optimized robust and efficient steady state load shedding (LS) in standalone inverter-based microgrids (IBMGs) considering uncertainties of the load and renewable generations. In order to incorporate different states of non-dispatchable renewable based-Distributed Energy Resources (DERs) and load demand fluctuations, the scenario tree model is implemented. To reduce the computational burden of the proposed model, a scenario-reduction technique using the Kantorovich distance (or Wasserstein distance) criteria is adopted to extract a sufficiently small number of scenarios. To reflect the system frequency in each opted scenario, a new power flow (PF) procedure, in which the system frequency turns up as a supplementary state variable is adopted. This procedure aims at minimizing the required shed loads to maintain the MG frequency over the critical frequency, when the inverters cannot tolerate any overload. According to the optimal curtailed load for different scenarios, a step-wise LS scheme is proposed for applying to an on-line operation manner. The performance of the proposed scheme is evaluated in two typical MV MG in standalone mode, a medium-scale 21 bus test system and a large-scale 118 bus test system, to ensure the efficiency and reliability of the proposed method in real conditions and systems. The obtained results evidence the effectiveness and the correctness of the presented LS scheme to diagnose power shortages and to maintain system frequency in the desirable range. Furthermore, the obtained results by proposed LS model have been compared with the conventional priority-based LS and the superiority of the proposed model over conventional models is proved.

Stochastic Generation Scheduling of Insular Grids with High Penetration of Photovoltaic and Battery Energy Storage Systems: South Andaman Island Case Study

Insular grids are fragile owing to lower inertia and the absence of interconnection with other grids. With the increasing penetration of non-dispatchable renewable energy sources, the vulnerability of such insular grids increases further. The government of India has proposed several projects to improve the photovoltaic systems (PV) penetration in the Andaman and Nicobar Islands’ grid. This paper investigates joint stochastic scheduling of energy and reserve generation for insular grids fed from diesel and gas-based generators, PV, and battery energy storage systems (BESS). The proposed stochastic scheduling model considers a wide range of probabilistic forecast scenarios instead of a deterministic model that assumes a single-point forecast. Hence, it provides an optimal solution that is technically feasible for a wide range of PV power forecast scenarios. The striking feature of the model developed in this work is the inclusion of stochastic constraints that represent (i) the coordination between PV and BESS, (ii) reserve constraints, (iii) battery charging/discharging limit constraints, and (iv) non-anticipatory constraints that ensure technical viability of scheduling decisions. The proposed model is validated on the dataset for South Andaman Island. Results reveal the applicability and feasibility of the proposed stochastic dispatch model for different generation mix scenarios.

Fully Decentralized Robust Modelling and Optimization of Radial Distribution Networks Considering Uncertainties

Fully decentralized optimization of multi-agent distribution networks considering uncertainties is essential to improving user-side energy utilization efficiency and flexibility, whereas a contradictory centralized coordinator aware of system-level information is inevitably introduced in existing researches. To address the problem, this paper introduces the flexibility boundaries of nodes to express their adjustability under uncertainties and constructs a flexibility transition model to express their neighbourhood relationship. Besides, a robust interval power flow model is established to consider the stochastic impact of generation on nodal voltage through neighbourhood information exchange. Based on the above two models, the robust optimization problem is established to minimize the baseline operation cost and maximize the allowable generation limits of non-dispatchable renewable energy sources. The model involves no global information and is solved with alternating direction method of multipliers(ADMM) in a fully decentralized way. Case study on a modified IEEE 33-bus and a 118-bus system is presented and the proposed method is compared with conventional multi-level robust formulations. The results suggest the effectiveness and correctness of the newly proposed method.

Assessing the influence of solar forecast accuracy on the revenue optimization of photovoltaic + battery power plants in day-ahead energy markets

Energy storage has become a subject of great interest in the last years due to the increasing penetration of non-dispatchable renewable energy power plants, especially solar photovoltaics (PV) and wind. Energy storage systems can add value to the grid in many ways: energy schedule optimization, ancillary services, renewable energy integration at high penetration levels, and so on. However, from the perspective of the asset's owner, it is important that the system regulator provides a regulatory framework and energy prices that stimulate the private plant operator to dispatch its energy storage system to assist the grid and get rewarded by these operations. An optimization problem is presented from the perspective of an asset owner with a PV plant and battery energy storage system. From this perspective, the agent must know the day-ahead spot-market energy prices and predict the day-ahead PV generation to decide on how to dispatch the battery system. We have evaluated 11 forecast accuracies to assess how the forecast accuracy can impact on the agent's total revenue.The findings showed that, if the agent's objective is to use the battery system only to guarantee the contracted energy, the battery system does not add as much value as it could; and higher forecast uncertainties lead to higher revenues, because the battery will then operate closer to the tariff arbitrage strategy, which is the optimal strategy for battery dispatch, independent of PV generation, relying only on the spot-market energy prices.

Approximate Dynamic Programming Decompositions for Economic Dispatch in Microgrids

Three novel approximate dynamic programming algorithms based on the temporal, spatial, and spatiotemporal decomposition are proposed for the economic dispatch problem (EDP) in a distribution energy system with complex topology and many non-dispatchable renewable energy sources and energy storage systems (ESS). Computational efficiency of the proposed algorithms is compared and convergence to the optimal solution is shown in numeric experiments on the example of the two-day hourly EDP for the IEEE 33bw test network having 200+ consumers, 150+ energy storages, and 1000+ consuming devices.