Excess Renewable Power Research Articles

Storing electricity in the low-rank coal: The heat-upgrading carnot battery concept and a comprehensive thermodynamic analysis

Promoting the energy/exergy performance of Carnot batteries is beneficial for future applications. This work proposed a Carnot battery concept deeply integrated with the low-rank coal (LRC) power plant (LCPP) for (1) enhancing the energy/exergy performance and (2) reducing LCPP's carbon emission and the minimum technical output (to adopt excess renewable power). The enhancement is attributed to the heat-upgrading effect of LRC pre-drying process and the energy complementarity between the subunits. A thermodynamic model based on the typical LCPP and Carnot battery cases is established to assess and analyze the proposed system. As the results show: (1) Daily average round-trip/exergy efficiencies reach 70.92 % and 54.28 %, and 3.36 % of carbon emission (126.52 ton/day) is reduced in 24 h, significantly higher than the conventional HP-ORC Carnot battery integrated with LCPP. (2) The performance of the proposed Carnot battery cannot be directly predicted from the subunits' performance due to the discharge during the charging periods; however, as long as the integrated charging capacity is not too small, the energy/exergy performance can maintain an elevated level. (3) For a generalized HP-ORC Carnot battery, low exergy input of discharging cycle limits the performance improvement; however, in the proposed system, the energy-upgrading effect compensates for this shortcoming.

Flexibility provision in the Swiss integrated power, hydrogen, and methane infrastructure

The renewable energy transition hinges on balancing energy supply and demand across seasons. This paper investigates the potential flexibility of Switzerland’s integrated power, hydrogen, and methane infrastructure to balance temporal mismatches while complying with national energy policies for sustainability and security. It develops an optimization method for energy system expansion and operation planning, filling crucial research gaps by (1) explicitly modeling power and gas transmission networks to guide technology placement and pinpoint network expansions, and (2) incorporating flexibility in power demand via shedding and shifting and in hydrogen and methane demands via price elasticity. The findings suggest that a 6.7-fold capacity expansion of variable renewables (i.e., photovoltaic, wind, run-of-river) by 2050 offsets nuclear phase-out and demand growth. The winter power gap is filled by power imports, hydropower generation, and gas turbines fueled by cost-effective hydrogen or methane imports. However, fuel embargoes escalate winter hydrogen and methane prices, reducing demand by 3.8%–10.4% and increasing domestic fuel production from biomass and excess renewable power in summer. To bridge the seasonal hydrogen and methane supply–demand gaps, up to 1.9 terawatt-hours of gas cavern storage is deployed in geologically viable locations, while costly tank storage plays a minor role. Power-to-gas requirements and power trade restrictions necessitate further renewable expansion, including 8.0 to 9.5 gigawatts of wind installations.

Multi criteria decision making for the most suitable combination of energy resources for a decentralized hybrid energy solution with green hydrogen as the storage option

Decentralized hybrid renewable energy systems are emerging as possible solutions for remote locations not feasible for grid power. However, such systems always need a storage device to bridge the gap between demand and supply during its operation. Electrochemical storage systems are currently the most common devices for this purpose. An alternative novel process to meet this gap between the demand and supply of power may be to generate hydrogen with excess renewable power during off-peak load. Produced green hydrogen may be used by fuel cells to generate electricity subsequently to compensate for the gap during peak load. However, practical suitability of acceptance of these alternative options will depend on economic feasibility including risk in return on investment. This is explored through comparative evaluation of these options with relative assessment of a few indicative parameters including uncertainties. These parameters are fuel consumption, cost of electricity, net present cost, financial risk and renewable fraction with full load meeting. As projects with new technologies have generally associated risk with return on investment, a Monte Carlo Simulation is also done to assess and compare the uncertainties of different options. As the five different evaluation criteria do not converge to the same best solution, finally a multi-criteria decision-making approach is adopted to decide the acceptable solution. The sensitivity analysis is also performed to examine the robustness of the decided solution. The analysis results show that the combination of photovoltaic-wind-generator-Lithium-ion is techno-economically acceptable with a moderate risk and a significant renewable share. Corresponding values of different parameters are: cost of electricity-$0.159/kWh, net present cost - $4,24,568, fuel consumption- 2628L/year, renewable fraction- 96.5%, and standard deviation–0.45% respectively. Though the methodology is generic, the study is demonstrated with data of a remote Indian village.

Optimization research on energy-saving and life-cycle decarbonization retrofitting of existing school buildings: A case study of a school in Nanjing

Given the continuous urbanization, many old buildings urgently need retrofitting. Considering the impact on student health, carbon peaking and carbon neutrality policies, the retrofitting of school buildings has become a focus for researchers. This paper presents a complete optimization method for energy-saving and life-cycle decarbonization retrofitting of existing school buildings. Through this method, a target building is first evaluated from three aspects: envelope, energy system and occupation information, and the weak links of the retrofit project are analyzed through combining measurement and simulation. The study describes the evaluation indicators of two optimization objectives (energy-saving and life-cycle decarbonization) and analyzes the constraints and optimization variables in the retrofit from the aspects of site layout, geometry, structure, envelope and energy system. Consequently, an efficient optimization method is introduced. The proposed method is applied to a school retrofit case in Nanjing, China. The results show that through the optimization of energy-saving, the retrofitted school can produce 102,786 kWh (14.36 kwh/m2) of excess renewable power per year. Upon applying the life-cycle decarbonization optimization, the retrofitted school can achieve zero carbon emissions throughout its life cycle and save 1,920,853.3 kg of carbon emissions in the region.

Review of underground hydrogen storage: Concepts and challenges

The energy transition is the pathway to transform the global economy away from its current dependence on fossil fuels towards net zero carbon emissions. This requires the rapid and large-scale deployment of renewable energy. However, most renewables, such as wind and solar, are intermittent and hence generation and demand do not necessarily match. One way to overcome this problem is to use excess renewable power to generate hydrogen by electrolysis, which is used as an energy store, and then consumed in fuel cells, or burnt in generators and boilers on demand, much as is presently done with natural gas, but with zero emissions. Using hydrogen in this way necessitates large-scale storage: the most practical manner to do this is deep underground in salt caverns, or porous rock, as currently implemented for natural gas and carbon dioxide. This paper reviews the concepts, and challenges of underground hydrogen storage. As well as summarizing the state-of-the-art, with reference to current and proposed storage projects, suggestions are made for future work and gaps in our current understanding are highlighted. The role of hydrogen in the energy transition and storage methods are described in detail. Hydrogen flow and its fate in the subsurface are reviewed, emphasizing the unique challenges compared to other types of gas storage. In addition, site selection criteria are considered in the light of current field experience. Cited as: Hematpur, H., Abdollahi, R., Rostami, S., Haghighi, M., Blunt, M. J. Review of underground hydrogen storage: Concepts and challenges. Advances in Geo-Energy Research, 2023, 7(2): 111-131. https://doi.org/10.46690/ager.2023.02.05

Optimized Electrical Stimulation Period Facilitated Microbial Electromethane Generation with CO2 Conversion

In order to improve microbial electromethane generation (mEMG) with CO2 conversion using excess renewable power, an electrical stimulation period was optimized to enrich active microorganisms on a biocathode and directionally strengthened electron transfer with a start-up mode of stepwise-promoted intermittent voltage. A highly adaptive microbial community was enriched on the biocathode for an electrical stimulation period of 1 h with the highest population abundance and diversity of archaea and bacteria. The living cell density and average coverage area ratio on the biocathode were 81.37 and 22.07%, respectively. The tryptophan, fulvic acid, and humic acid substances with peak fluorescence intensities in extracelluar polymers effectively improved electron transport in the mEMG system. The highest area capacitance of the biocathode was 13.96 mF/cm2. The biofilm and solution resistances first decreased to valleys (102.3 and 1.541 Ω) and then increased. The highest faradaic efficiency (95.37%) of CH4 was obtained with 2.35 μmol/L coenzyme F420, leading to an increased CH4 production rate by 39.68%.

Dynamic hierarchical modeling and control strategy of high temperature proton exchange electrolyzer cell system

High temperature proton exchange membrane electrolyzer cells (HT-PEMECs) show faster reaction kinetics than the low temperature PEMECs (LT-PEMECs) and are suitable for utilizing waste heat from the industry. However, dynamic modeling and control of HT-PEMECs are still lacking, which is critical for integrating the HT-PEMECs with fluctuating renewable power. In this study, hierarchical models are developed to investigate the transient behavior of the HT-PEMEC system with hydrogen recirculation. It is observed that the maximum efficiency point of the reference power can be reached by cooperatively adjusting the current density and anode inlet gas flow rate, and the application of artificial neural networks can accurately predict the operating conditions at the points of maximum efficiency. Moreover, the proposed cooperative model predictive control strategy not only improves the efficiency (about 1.2%) during dynamic processes but also avoids the problem of reactant starvation. This study provides useful information to understand the dynamic behaviors of HT-PEMECs driven by excess renewable power.

Multi-objective optimizations of solid oxide co-electrolysis with intermittent renewable power supply via multi-physics simulation and deep learning strategy

Solid oxide electrolysis cell (SOEC) is a novel approach to utilize excess renewable power to produce fuels and chemicals. However, the intermittence and fluctuation of renewable energy requires more advanced optimization strategy to make sure its performance in safety and cost-effectiveness. Here, we propose a hybrid model for the precise and quick optimization of the co-electrolysis process in the SOEC for syngas production, based on the multi-physics simulation (MPS) and deep learning algorithm. The hybrid model fully considers electrochemical/chemical reactions, mass/momentum transport and heat transfer, and presents a small relative error (<1%) in most the cases (>96%). Various targets including the single-objective, dual-objective and multi-objective optimizations are evaluated with particular attentions on the reactant conversion rate and energy efficiency at different temperatures. The electrolysis efficiency is negatively correlated with the power supply in all strategies and thermal neutral condition (TNC) can be achieved at different temperatures, where 1023 K, 1053 K, 1083 K and 1113 K are corresponded to the TNC power range of 10–16 W, 14–23 W, 18–29 W and 22–37 W, respectively. This theory can be flexibly applied in the sustainable manufacturing and circular economy sectors and energy according to the optimization targets.

Modeling and Evaluating Beneficial Matches between Excess Renewable Power Generation and Non-Electric Heat Loads in Remote Alaska Microgrids

Many Alaska communities rely on heating oil for heat and diesel fuel for electricity. For remote communities, fuel must be barged or flown in, leading to high costs. While renewable energy resources may be available, the variability of wind and solar energy limits the amount that can be used coincidentally without adequate storage. This study developed a decision-making method to evaluate beneficial matches between excess renewable generation and non-electric dispatchable loads, specifically heat loads such as space heating, water heating and treatment, and clothes drying in three partner communities. Hybrid Optimization Model for Multiple Electric Renewables (HOMER) Pro was used to model potential excess renewable generation based on current generation infrastructure, renewable resource data, and community load. The method then used these excess generation profiles to quantify how closely they align with modeled or actual heat loads, which have inherent thermal storage capacity. Of 236 possible combinations of solar and wind capacity investigated in the three communities, the best matches were seen between excess electricity from high-penetration wind generation and heat loads for clothes drying and space heating. The worst matches from this study were from low penetrations of solar (25% of peak load) with all heat loads.

A Comparison of Instantaneous and Extension p-q Methods for Current Controlled Voltage Source Inverter in Microgrid

ABSTRACT With the advancement in technology and population growth, the motivation of integrating utility grid with the microgrid through power electronic converters increases. This paper presents the control of power electronic converter connected at the grid side. This converter regulates the power flow between renewable energy system (RES), load and grid in addition to the compensation of harmonic and reactive power. The reference currents are generated to decide the power flow from RES to the load and to suppress the harmonic and reactive power in the grid making grid current sinusoidal. In this paper, the reference current generation techniques like instantaneous p-q method and extension p-q method are implemented and compared. Linear Quadratic Regulator (LQR) is used to track the reference current. The control law of LQR is designed in a simple way using simplified equivalent circuit of a three-phase grid integrated renewable energy system. The system is tested experimentally under balanced and unbalanced conditions in two different modes such as insufficient renewable power and excess renewable power. The supremacy of extension p-q method over instantaneous p-q method is proved by getting low total harmonic distortion and better power factor under balanced and unbalanced conditions experimentally.

Power to gas: an option for 2060 high penetration rate of renewable energy scenario of China.

Replacing conventional fossil fuel power plants with large-scale renewable energy sources (RES) is a crucial aspect of the decarbonization of the power sector and represents a key part of the carbon-neutral strategy of China. The high penetration rate of renewable energy in the electricity system, however, implies the challenges of dealing with the intermittency and fluctuation of RES. Power to gas (P2G), which can convert surplus renewable power into a chemical form of energy (i.e., synthetic gas), can help handle this challenge and supply new energy carriers for various energy sectors. By modeling three potential 2060 energy mix scenarios in China, this paper aims to describe the possible contribution of the high penetration rate of renewable energy combined with P2G in the future sustainable energy system. Different schemes are listed and compared, and the results are used in a basic economic evaluation of the synthetic gas production cost for the P2G plants. Ideally, nearly 18 million tons of carbon dioxide would be recycled and transformed into methane (around 9.37 km3) annually in China. Considering a zero price for the excess renewable power and future costs of the components, the levelized cost of energy (LCOE) of the final production of methane is estimated at 0.86 $/m3SNG.

The mutual benefits of renewables and carbon capture: Achieved by an artificial intelligent scheduling strategy

Renewable power and carbon capture are key technologies to transfer the power industry into low carbon generation. Renewables have been developed fast, however, the intermittent nature has imposed higher requirement for the flexibility of the power grid. Retrofitting carbon capture technologies to existing fossil-fuel fired power plants is an important solution to avoid the “lock-in” of emissions, but the high operating costs hinders their large scale application. The coexistence of renewable power and carbon capture opens up a new avenue that the deployment of carbon capture can provide additional flexibility for better accommodation of renewable power while excess renewables can be used to reduce the operating costs of carbon capture. To this end, this paper proposes an artificial intelligence based optimal scheduling strategy for the power plant-carbon capture system in the context of renewable power penetration to show that the mutual benefits between carbon capture and renewable power can be achieved when the carbon capture process is made fully adjustable. An artificial intelligent deep belief neural network is used to reflect the complex interactions between carbon, heat and electricity within the power plant carbon capture system. Multiple operating goals are considered in the scheduling such as minimizing the operating costs, renewable power curtailment and carbon emission, and the particle swarm heuristic optimization is employed to find the optimal solution. The impacts of carbon capture constraint mode, carbon emission penalty coefficient, carbon dioxide production constraints and renewable power installed capacity are investigated to provide broader insight on the potential benefit of carbon capture in future low-carbon energy system. A case study using real world data of weather condition and load demand shows that renewable power curtailment can be reduced by 51% with the integration of post-combustion capture systems and 35% of total carbon emission are captured by the use of excess renewable power through optimal scheduling. This paper points out a new way of using artificial intelligent technologies to coordinate the couplings between carbon and electricity for efficient and environmentally friendly operation of future low-carbon energy system.

Multiobjective nested optimization framework for simultaneous integration of multiple photovoltaic and battery energy storage systems in distribution networks

The rapid growth of renewables in modern distribution networks results in the spilling of energy due to the limited hosting capacity of these networks, violation of system constraints, reduced network efficiency, and improper utilization of resources. Battery energy storage system (BESS), in spite of its high cost, a shorter life and complex control, offers a flexible solution for the problem. In this paper, a multiobjective nested optimization framework is developed for the simultaneous optimal allocation of multiple solar photovoltaics (SPVs) and BESSs in the distribution networks. The framework involves a two-layered structure; the outer layer provides tentative planning solutions to the inner layer that optimizes the desired objectives of network operations and then returns the functional values back to the outer layer. The purpose of the inner-layer is to satisfy the operational constraints of the networks and ensure the optimal utilization of BESS capacities, suggested by the outer layer, at the time of planning itself. A new BESS operating strategy is proposed for optimum utilization of BESS. The nested multiobjective optimization problem is handled by suggesting a new weighted sum approach in conjunction with a recently developed swarm intelligence-based algorithm, i.e. moth search optimization. Overall, the proposed deterministic model essentially ensures the high penetration of SPVs and the optimal utilization of BESSs to justify their installation. The optimization model is investigated on a benchmark 33-bus test distribution network. The application results highlight enhanced energy efficiency, peak load shaving, high renewable penetration, voltage profile improvement, and mitigation of reverse power flow while effectively absorbing the excess renewable power generation during light load hours.

Investigation of the Multi-Point Injection of Green Hydrogen from Curtailed Renewable Power into a Gas Network

Renewable electricity can be converted into hydrogen via electrolysis also known as power-to-H2 (P2H), which, when injected in the gas network pipelines provides a potential solution for the storage and transport of this green energy. Because of the variable renewable electricity production, the electricity end-user’s demand for “power when required”, distribution, and transmission power grid constrains the availability of renewable energy for P2H can be difficult to predict. The evaluation of any potential P2H investment while taking into account this consideration, should also examine the effects of incorporating the produced green hydrogen in the gas network. Parameters, including pipeline pressure drop, flowrate, velocity, and, most importantly, composition and calorific content, are crucial for gas network management. A simplified representation of the Irish gas transmission network is created and used as a case study to investigate the impact on gas network operation, of hydrogen generated from curtailed wind power. The variability in wind speed and gas network demands that occur over a 24 h period and with network location are all incorporated into a case study to determine how the inclusion of green hydrogen will affect gas network parameters. This work demonstrates that when using only curtailed renewable electricity during a period with excess renewable power generation, despite using multiple injection points, significant variation in gas quality can occur in the gas network. Hydrogen concentrations of up to 15.8% occur, which exceed the recommended permitted limits for the blending of hydrogen in a natural gas network. These results highlight the importance of modelling both the gas and electricity systems when investigating any potential P2H installation. It is concluded that, for gas networks that decarbonise through the inclusion of blended hydrogen, active management of gas quality is required for all but the smallest of installations.

Hydrogen: Hype or a Glide Path to Decarbonizing Natural Gas—Part 2

As discussed in Part 1 of this series, hydrogen (H2) is being debated across the globe as a means of reducing greenhouse gas (GHG) emissions, specifically in efforts to decarbonize the existing energy and transportation sectors. In these discussions, stakeholders use multiple terms such as hydrogen‐enriched natural gas power (HENG), power‐to‐gas (P2G), green H2, and renewable H2. All of these terms generally mean producing H2 with excess renewable power using electrolyzers, which appears to be the preferred policy option. For the purposes of this article, green H2will be used and to distinguish it from blue H2, which can use natural gas as a feedstock with steam methane reforming.

Multi-functional Microgrid’s Transient-Free Connection: Disconnection with Grid

A wind–solar microgrid synchronization is realized in this work. Such microgrid has the capability to serve the loads in islanded mode, and to connect and disconnect itself with the main grid smoothly using synchronization control. It feeds excess renewable power to the AC mains during high renewable energy generation, and also the power is supplied from the grid to the loads at low renewable generation. The voltage source converter (VSC) of microgrid operates with the voltage control and the current control algorithms. At the DC link of VSC, a battery is attached to provide power leveling. Microgrid multi-functioning aspects (voltage–frequency regulation, power balance, harmonics elimination, synchronization, de-synchronization) under isolated and grid-connected modes with variety of test results are demonstrated. A laboratory prototype of wind–solar microgrid is built to validate the performance through test results.

Techno-Economic Optimization of CO2-to-Methanol with Solid-Oxide Electrolyzer

Carbon capture and utilization are promising to tackle fossil-fuel depletion and climate change. CO2 hydrogenation can synthesize various chemicals and fuels, such as methanol, formic acid, urea, and methane. CO2-to-methanol integrated with solid-oxide electrolysis (SOE) process can store renewable power in methanol while recycling recovered CO2, thus achieving the dual purposes of storing excess renewable power and reducing lifetime CO2 emissions. This paper focuses on the techno-economic optimization of CO2 hydrogenation to synthesize green methanol integrated with solid-oxide electrolysis process. Process integration, techno-economic evaluation, and multi-objective optimization are carried out for a case study. Results show that there is a trade-off between energy efficiency and methanol production cost. The annual yield of methanol of the studied case is 100 kton with a purity of 99.7%wt with annual CO2 utilization of 150 kton, representing the annual storage capacity of 800 GWh renewable energy. Although the system efficiency is rather high at around at 70% and varies within a narrow range, methanol production cost reaches 560 $/ton for an electricity price of 73.16 $/MWh, being economically infeasible with a payback time over 13 years. When the electricity price is reduced to 47 $/MWh and further to 24 $/MWh, the methanol production cost becomes 365 and 172 $/ton with an attractive payback time of 4.6 and 2.8 years, respectively. The electricity price has significant impact on project implementation. The electricity price is different in each country, leading to a difference of the payback time in different locations.

Pitfalls in decarbonising heat: A misalignment of climate policy and product energy labelling standards

There is considerable potential to decarbonise household energy consumption through the electrification of heating systems which can absorb excess renewable power and mitigate power network constraints through intelligent control. However, current standards discourage low carbon electricity sources through outdated assumptions; predicated upon a traditional electricity network which had higher emissions. Consequently, the implementation of product Energy labelling across Europe is biased against electric space and water heating systems in favour of gas. This paper examines the impact of this bias through a case study of the European Union's product labelling directive for domestic hot water systems. Laboratory testing of a market leading electric water tank and an A rated instantaneous gas boiler has demonstrated efficiencies of 87.4% and 72.9% respectively. In spite of this, the labelling directive assigns a C rating to the tank. This is due to a conversion coefficient (CC) within the directive's calculation based on an average electricity generation efficiency of 40% without a similar coefficient for gas. This paper advocates the removal of the CC factor from the directive to normalise the comparison, thus promoting a technology uniquely suited towards absorbing intermittent renewable energy sources with negligible costs.

Dynamic simulation of different transport options of renewable hydrogen to a refinery in a coupled energy system approach

Three alternative transport options for hydrogen generated from excess renewable power to a refinery of different scales are compared to the reference case by means of hydrogen production cost, overall efficiency, and CO2 emissions. The hydrogen is transported by a) the natural gas grid and reclaimed by the existing steam reformer, b) an own pipeline and c) hydrogen trailers. The analysis is applied to the city of Hamburg, Germany, for two scenarios of installed renewable energy capacities. The annual course of excess renewable power is modeled in a coupled system approach and the replaceable hydrogen mass flow rate is determined using measurement data from an existing refinery. Dynamic simulations are performed using an open-source Modelica® library. It is found that in all three alternative hydrogen supply chains CO2 emissions can be reduced and costs are increased compared to the reference case. Transporting hydrogen via the natural gas grid is the least efficient but achieves the highest emission reduction and is the most economical alternative for small to medium amounts of hydrogen. Using a hydrogen pipeline is the most efficient option and slightly cheaper for large amounts than employing the natural gas grid. Transporting hydrogen by trailers is not economical for single consumers and realizes the lowest CO2 reductions.

Economic and environmental cost of self-sufficiency - analysis of an urban micro grid

In this paper we analyze the economic feasibility as well as the environmental ramifications of operating a renewable energy based micro grid for achieving ultimate self-sufficiency. Results show that in the present case ultimate self-sufficiency is neither economically feasible nor environmentally viable due to large overcapacity in storage and generation. Based on the results we propose that economic viability as well as ecological effectiveness of a local micro grid can only be achieved by an optimized combination of storing, curtailing and feeding-in of excess renewable power, all of which should be considered in a new reform of the German Renewable Energy Act (EEG).