Renewable Capacity Research Articles

A study on the renewable power generation capacity of microalgae microbial fuel cells for powering GIoT sensor nodes

Microalgae-Microbial Fuel Cell (mMFC) is a novel and attractive green renewable energy source for bio-electricity generation. Its capacity to generate energy is of particular interest for the design of sustainable green internet of things (GIoT) sensor networks. However, this capacity needs to be assessed due to critical limitations in their low-level output voltage and possible bioelectrochemical disturbances. This study investigates the renewable energy generation capacity of an mMFC-harvester system for powering low-power wireless sensor nodes. A two-chamber mMFC prototype is designed as a proof of concept using the CMI7000 membrane and the BQ25570 circuit to harvest the energy. A sensor node based on Nordic nRF52840 ultra-low-power microcontroller implements a uniform power management strategy and the energy capacity is analyzed in terms of the number of Bluetooth low energy (BLE) transmissions. Experimental results show that after an initial cold-start period in the harvester circuit, the system stores the energy in a 0.1 F supercapacitor in 6.25 h, representing 3.26 J. The maximum power density generation is 80.10 mW/m2, and the energy harvested is suitable to perform up to 9 continuous transmissions using BLE.

Freedom of contract: prerequisites for development in the conditions of digitalization of the economy

Digital technologies influenced the development of civil-law relations in the field of trade, financial, educational, consulting services, entertainment, etc., leading to the emergence of remote forms of offer and acceptance. The development of "business on the network" initiated the practice of applying the principle of freedom of contract by participants in civil-law relations in this renewed capacity. The acquired experience needs to be studied and understood in order to take into account in the legislation the needs of participants in civil-law relations in the world of Internet technologies. The purpose of the paper is to study the prerequisites for the development of the principle of freedom of contract in the digitalized economy. Based on the research materials, it was determined that the main prerequisites for the development of the principle of freedom of contract in the conditions of digitalization of the economy are: 1) increasing the availability of goods, works and services that are ordered (provided) through network technologies; 2) individualization of the provisions of the public offer by e-commerce entities in order to achieve more favorable conditions; 3) provision of timely and complete information to the counterparty before accepting the offer. The results of research into the activities of e-commerce entities show that there is a widespread practice of individualizing essential conditions for categories of unregistered users, which differ based on the frequency of visits to the entity's website, their geolocation, or other technological parameters. Considering the fact that the subjects act on the basis of a public offer (public contract), this practice contradicts the requirements of civil legislation. However, taking into account the requirements of reasonableness and justice, which are the basis of the principle of freedom of contract, we consider it appropriate to consider such a practice (if such an entity operate in a competitive market) as appropriate. We consider it justified to place on the side of the contract developer of the public offer an additional duty to assist the other party in conscious participation in contractual relations. Such an obligation as a legal means of ensuring freedom of will is necessary to ensure the good faith of counterparties in the digital economy.

Power grid load frequency control based on Fractional Order PID combined with pumped storage and battery energy storage

With the increasing proportion of installed renewable energy power generation capacity and the introduction of quantitative energy storage policies for new energy power generation. In view of the influence of intermittent and volatility of distributed generation on the safe of power grid, it is​ particularly important in the future to equip reasonable energy storage to ensure the flexibility of power system. In this paper, a load frequency control (LFC) strategy of hybrid energy storage based on fractional order proportion integral derivative (FOPID) is proposed to solve the frequency modulation problem of battery energy storage system (BESS) and pumped storage station (PSS) participating in the interconnection network. Firstly, the LFC model is established under the nonlinear factors such as regulator dead zone and generation rate constraint on a two-area reheat steam turbine. Secondly, a FOPID controller is designed. Furthermore, the combined LFC simulation is carried out by adding BESS under the two working operations of PSS generating and pumping. Finally, the influence of demand response is considered in the hybrid energy storage control.

Existing Stature and Possible Outlook of Renewable Power in Comprehensive Electricity Market

The massive growth in power demand and the sharp decay in the availability of conventional energy sources forces society to move toward renewable power consumption. The rise in renewable energy utilization is one of the greatest strategies involved in making the environment clean, green, and emission-free. The investment cost is slightly high for this kind of resource, but their running costsare very minimal, which encourages power producers to invest in renewable power plants. Power producers always focus on their economic profit and possible feasibilities before the investment in a new power plant setup. Wind, small hydro, and solar photovoltaics have been considered the foremost efficient and feasible renewable sources. In 2021, the worldwide renewable power capacity had grown to 17%, despite supply chain disturbances and surges in prices. The renewable power market set a target of achieving a 95% increment in global power capacity by 2026. Hence, humankind should consider wind, hydro, and solar photovoltaics as the main energy sources, and there is a need to increase use of such sources. This paper highlights the latest developments, enormous technologies, and upcoming aspects of wind power, hydropower, and solar photovoltaics in India, as well as around the globe. The present status of renewable energy can motivate global power producers to spend their money on the installation of a new renewable power plant to obtain more economic benefits and give societal economic and environmental payback to humans.

Microgrid Optimal Dispatch Based on Distributed Economic Model Predictive Control Algorithm

A microgrid cluster is composed of multiple interconnected microgrids and operates in the form of cluster, which can realize energy complementation between microgrids and significantly improve their renewable energy consumption capacity and system operation reliability. A microgrid optimal dispatch based on a distributed economic model predictive control algorithm is proposed in this paper. Firstly, the control task of the microgrid power generation system is defined, which is required to meet the load demand while reducing the economic loss of the system and realize dynamic economic optimization. The global objective function is designed based on the control task, and the detailed design method of the distributed economic model predictive controller is given. The control law is obtained by an iterative calculation using the Nash optimal method, which can effectively reduce the amount of data in the communication network. Finally, a microgrid group composed of four microgrids is used as an example for simulation verification. The simulation results show that the distributed economic model predictive control algorithm proposed in this paper has good economic benefits for microgrid dispatching.

Climate Change Policy of India: G20 Presidency and Climate Action

One of the greatest challenges for humanity is how to address climate change, in a coordinated manner globally. Address this catastrophe requires a massive effort that needs to be undertaken now, not later. IPCC report suggests two step that would be necessary to avoid this disastrous trend of climate change, first, industrialized nations would have to reduce CO2 emissions by half by 2030, and second is to stop adding CO2 to atmosphere altogether by the early 2050s. So, the world needs to consciously uncouple from fossil fuel to more toward a low carbon future. Much of the intended transition far from fossil fuel depends on G20 countries, which accounts for 80% of global GDP, avails 75% of international trade, and collectively consume 85% of the world’s coal, oil, and natural gas annually. Recently, India has been ranked amongst top five countries in the world, and the best among the G20 countries, based on its Climate Change Performance. India jumps two spots higher, and is now ranked 8th as per Climate Change Performance Index (CCPI), 2023 published by German Watch, New Climate Institute and Climate Action Network International based in Germany. The aggressive policies of India towards climate change, and rapid deployment of renewables and robust framework for energy efficiency programs have shown considerable impact. As per CCPI report, India is on track to meet its 2030 emission targets. Currently, India has hosting its presidency toward G20 meeting 2023, and it will be an opportune time to show the world, about its climate mitigation policies such as deployment of renewable sources of energy and other energy transition programmes. The top 10 rank globally reflects that India is implementing energy transition programmes such as renewable capacity installation at much faster rate than anywhere in the world.

New insights from the STIPART model on how environmental-related technologies, natural resources and the use of the renewable energy influence load capacity factor

The rapid development in environmental-related technologies, economic growth and natural resources has promoted many undesirable environmental influences that affect living standards and human health. Consequently, the present research employed an inclusive indicator to quantify ecological eminence known as the load capacity factor. Considering this view, the existing body of literature has not provided a sufficiently supportive indication to discover the factors influencing the load capacity factor in terms of ecological excellence. To do this, the present study employs various panel data estimators and causality tests considering cross-sectional dependence and slope heterogeneity for the period 1990–2019 to analyze the environmental impacts of environmental technologies, economic growth, natural resources, renewable energy consumption, and urbanization for 17 Asian-Pacific Economic Cooperation (APEC) countries. The study results suggest that economic growth reduces environmental quality.In contrast, natural resources, technological development, urbanization, and renewable energy increase the load capacity factor, which indicates environmental sustainability while considering nature's supply and demand aspects. Based on these findings, APEC policymakers should take advantage of technological development, urbanization, and renewable energy. They should transform their current economic growth models into an environmentally friendly structure to achieve their environmental goals and contribute to a sustainable world order.

Endonezya'da Tarımın Yenilenebilir Enerji ve GSYİH Payının Artırılması: Tarım Sektörü İstihdamı Üzerindeki Etkilerin Analizi

Renewable energy capacity, agricultural sector GDP, and agricultural employment in Indonesia experienced a downward trend from 1990 to 2019. This trend negatively impacts Indonesia’s target to utilize renewable energy as its energy source, employment in the agricultural sector, and the importance of agriculture to the Indonesian economy. Based on these issues, this research examined the impact of renewable energy usage and agricultural sector GDP on the employment rate of the agricultural sector by implementing the Autoregressive Distributed Lag (ARDL) model. According to empirical findings, total renewable energy supply improves agricultural sector employment in the short and long run; however, agricultural sector GDP improves employment only in the short run and negatively impacts the long run. It suggests that renewable energy has the potency to enhance agricultural employment. The use of renewable energy is expected to be a solution for the decrease in employment in the agricultural sector along with the GDP decrease. Governments can make sure that all funds allocated to an agroecological program or policy are used to increase agricultural renewable energy use. Renewable energy regulations should be assessed based on their ability to reduce pollution while also ensuring a reliable energy supply for the agricultural sector at an affordable price.

Can Bitcoin mining increase renewable electricity capacity?

Proponents of Bitcoin argue that demand for electricity from Bitcoin miners can lead to an increase in renewable electricity capacity. We rigorously evaluate this claim by estimating a Bitcoin electricity demand curve and include this demand curve in a long-run model of the Texas electricity market. We find that while Bitcoin mining can indeed increase renewable capacity, it also increases carbon emissions. When Bitcoin miners provide grid management services in the form of demand response, their emissions impact is largely mitigated.

The role of electricity market design for energy storage in cost-efficient decarbonization

The role of electricity market design for energy storage in cost-efficient decarbonization

Day-ahead multi-objective optimization of CHP unit with heat storage considering flexibility

Nowadays, with the growing number of renewable energy capacities, the flexibility of the energy system has become an indicator that must be considered under the impact of frequent peak regulation. However, more flexibility always means less economy. The purpose of this paper is to tackle the contradiction between flexibility and the economy in the energy system. Based on day-ahead load prediction, a multi-objective optimization method is proposed here considering the objectives of excess of power variation and operation cost. NSGA-II is used to deal with the optimization problem by forming a Pareto frontier containing all the optimized results. We take the microgrid system composed of two combined heat and power units and a molten salt heat storage tank as a case study. Two typical results that emphasize flexibility and economic indicator are analyzed respectively and compared with each other, which reduce general guidance of the operation mode’s selection.

Cooperative multi-agent deep reinforcement learning based decentralized framework for dynamic renewable hosting capacity assessment in distribution grids

Renewable hosting capacity (RHC) means the total renewable power that can be integrated into the power grid without violation of network constraints. In this paper, a cooperative multi-agent deep reinforcement learning (CMADRL) based decentralized method is proposed to assess the dynamic renewable hosting capacity (RHC) of distribution grids, aiming to duly make decisions for renewable energy interconnection requests and ensure consistent power grids reliability simultaneously. According to the time-varying load-generation operation conditions, the proposed CMADRL method can continuously derive multi-timescale operation strategies for volt-var control devices, e.g., static var compensators (SVCs) and on-load tap changer (OLTC), improving the RHC of distribution grids. With three independent agents (SVC, OLTC and renewable agents), the proposed CMADRL method follows the manner of centralized training and decentralized execution, which guarantees the algorithm convergence under time-varying load-generation uncertainties and meanwhile ensures the feasibility of online applications. The case studies are carried out on a modified IEEE 37-node distribution system to demonstrate the effectiveness of the proposed real-time RHC assessment method. Numerical results verify that the proposed CMADRL method has a better performance than conventional optimization methods on computation efficiency.

Comparative analysis of UK net-zero scenarios: The role of energy demand reduction

Final energy demand in the UK has remained relatively constant since the 1970s. However, most of the scenarios that model pathways to achieve the UK's net-zero greenhouse gas emissions by 2050 indicate that energy demand reduction (EDR) will be an important pillar of climate change mitigation. Despite this, the UK Government has no clearly defined strategy to reduce demand. This comparative analysis explores the role of EDR across twelve UK-based climate scenarios from four organisations that estimate changes in carbon emission and energy consumption from 2020 to 2050. We focus on changes in final demand across the economy, assessing the scale of ambition and the implications for the rest of the energy system in the context of net-zero. All the pathways explored achieve reductions of at least 32.8% in total final energy demand from 2020 to 2050, suggesting that this is the minimum level of demand reduction required to achieve the development and rollout of the supply side technologies necessary to decarbonise the energy system. Reductions in total final demand of up to 52% are demonstrated. We find that pathways with higher levels of EDR mitigate against technological challenges, such as scaling up renewable energy capacities, are less reliant on carbon-dioxide removal technologies and require less investment – but are characterised by higher levels of social change.

Unintended consequences of curtailment cap policies on power system decarbonization

As countries pursue power system decarbonization, a well-intentioned strategy being pursued in jurisdictions like China is the strict integration target, often in the form of a curtailment cap. The effects of these curtailment caps have not been systematically studied. Here, we evaluate the effects of these caps on the decarbonization of one provincial power system using a capacity expansion model. Results reveal that curtailment caps yield deleterious effects that do not align with the stated goals of these policies. Capping curtailment significantly increases storage capacity (+43% with a 5% curtailment cap) and reduces renewable capacity (-17%). Even with the increase in flexible storage capacity, the policy still jeopardizes power system reliability by increasing occurrences of over or under generation. It also suppresses power generation from hydropower and reduces energy storage utilization while increasing fossil fuel utilization. Capping curtailment increases economic costs (+6% with a 5% curtailment cap) and CO2 emissions (+7%).

Hybrid Renewable Energy System Design: A Machine Learning Approach for Optimal Sizing with Net-Metering Costs

Hybrid renewable energy systems with photovoltaic and energy storage systems have gained popularity due to their cost-effectiveness, reduced dependence on fossil fuels and lower CO2 emissions. However, their techno-economic advantages are crucially dependent on the optimal sizing of the system. Most of the commercially available optimization programs adopt an algorithm that assumes repeated weather conditions, which is becoming more unrealistic considering the recent erratic behavior of weather patterns. To address this issue, a data-driven framework is proposed that combines machine learning and hybrid metaheuristics to predict weather patterns over the lifespan of a hybrid renewable energy system in optimizing its size. The framework uses machine learning tree ensemble methods such as the cat boost regressor, light gradient boosting machine and extreme gradient boosting to predict the hourly solar radiation and load demand. Nine different hybrid metaheuristics are used to optimize the hybrid renewable energy system using forecasted data over 15 years, and the optimal sizing results are compared with those obtained from 1-year data simulation. The proposed approach leads to a more realistic hybrid renewable energy system capacity that satisfies all system constraints while being more reliable and environmentally friendly. The proposed framework provides a robust approach to optimizing hybrid renewable energy system sizing and performance evaluation that accounts for changing weather conditions over the lifespan of the system.

Reversible Solid Oxide Cells for Energy Storage in the Netherlands: Thermodynamics and Fuel Selection

We investigated a large-scale energy storage system based on reversible solid oxide cells, for a future Dutch electrical grid powered entirely by intermittent renewables. Three fuels — hydrogen, ammonia and methane — were investigated for such a system, to find the most suitable one in terms of minimizing the required fuel storage and renewable power generation capacity. The required sizes of fuel storage and power generation using each fuel were estimated using process models of rSOC systems, and a mathematical model of a storage-supported power grid. The results show that the use of hydrogen would lead to the smallest power generation requirement. It is found that the potential storage capacity in the Netherlands exceeds the requirement for storing any fuel, while the renewable power capacity planned for 2030 is insufficient to meet the demand. Under these conditions and assumptions, we find hydrogen to be the appropriate fuel for the Netherlands.

Guiqi Baizhu prescription ameliorates cytarabine-induced intestinal mucositis by targeting JAK2 to inhibit M1 macrophage polarization

BackgroundIntestinal mucositis (IM) is characterized by damage to the intestinal mucosa resulting from inhibition of epithelial cell division and loss of renewal capacity following anticancer chemotherapy and radiotherapy. Cytarabine (Ara-C), the main chemotherapy drug for the treatment of leukemia and lymphoma, is a frequent cause of IM. Guiqi Baizhu prescription (GQBZP) is a traditional Chinese medicine with anti-cancer and anti-inflammatory effects. PurposeTo determine if GQBZP can ameliorate Ara-C induced IM and identify and characterize the pharmacologic and pharmacodynamic mechanisms. Study design and methodsIM was induced in mice with Ara-C and concurrently treated with orally administered GQBZP. Body weight and food intake was monitored, with HE staining to calculate ileal histomorphometric scoring and villus length/crypt depth. Immunoblotting was used to detect intestinal tissue inflammatory factors. M1 macrophages (M1) were labeled with CD86 by flow cytometry and iNOS + F4/80 by immunofluorescence. Virtual screening was used to find potentially active compounds in GQBZP that targeted JAK2. In vitro, RAW264.7 cells were skewed to M1 macrophage polarization by lipopolysaccharide (LPS) and interferon-γ (INF-γ) and treated orally with GQBZP or potential active compounds. M1 was labeled with CD86 by flow cytometry and iNOS by immunofluorescence. ELISA was used to detect inflammatory factor expression. Active compounds against JAK2, p-JAK2, STAT1 and p-STAT1 were identified by western blotting and HCS fluorescence. Molecular dynamics simulations and pharmacokinetic predictions were carried out on representative active compounds. ResultsExperimental results with mice in vivo suggest that GQBZP significantly attenuated Ara-C-induced ileal damage and release of pro-inflammatory factors by inhibiting macrophage polarization to M1. Molecular docking was used to identify potentially active compounds in GQBZP that targeted JAK2, a key factor in macrophage polarization to M1. By examining the main components of each herb and applying Lipinski’s rules, ten potentially active compounds were identified. In vitro experimental results suggested that all 10 compounds of GQBZP targeted JAK2 and could inhibit M1 polarization in RAW264.7 cells treated with LPS and INF-γ. Among them, acridine and senkyunolide A down-regulated the expression of JAK2 and STAT1. MD simulations revealed that acridine and senkyunolide A were stable in the active site of JAK2 and exhibited good interactions with the surrounding amino acids. ConclusionsGQBZP can ameliorate Ara-C-induced IM by reducing macrophage polarization to M1, and acridine and senkyunolide A are representative active compounds in GQBZP that target JAK2 to inhibit M1 polarization. Targeting JAK2 to regulate M1 polarization may be a valuable therapeutic strategy for IM.

Do green electricity consumers contribute to the increase in electricity generation capacity from renewable energy sources? Evidence from France

In 2019, 3.9 million French residential customers subscribed to 100% green electricity offers. These offers are based on guarantees of origin (GOs), the electricity-tracking system in the European Union. Based on an analysis of the French GO registry, this paper assesses whether French green electricity consumers contribute to the increase of renewable electricity generation capacity. Theoretically, green consumers may have a direct or indirect impact on additional investments. Our results show that, in practice, the GO system benefits almost exclusively to large old French hydro plants. To make the GO system more effective in raising renewable energy capacity, two options are discussed: limiting the issuing of GOs to new production devices only or informing consumers via additionality criteria labelling.

Exploring economic and environmental efficiency in renewable energy utilization: a case study in the Organization for Economic Cooperation and Development countries.

The share of renewable energy has grown significantly in global energy supply, yet the evaluation of renewable energy utilization has remained limited. Hence, this research explored economic and environmental efficiency in renewable energy utilization in 20 OECD (The Organization for Economic Cooperation and Development) countries from 2015 to 2020. The study approached the data envelopment analysis-slack-based measure (DEA-SBM) to evaluate economic efficiency, and the DEA undesirable output to measure environmental efficiency. Four inputs as labor force, gross capital formation, total renewable energy capacity, and share of renewable energy were compared to two desirable outputs as the gross domestic product (GDP), and total energy production in the economic efficiency model. In the environmental efficiency model, the same inputs were evaluated with GDP as the desirable output and CO2 emissions as the undesirable output. The DEA-SBM revealed that Australia, Belgium, Norway, the UK, and the USA were efficient in economic evaluation, whereas DEA undesirable output indicated that Belgium, France, Sweden, the UK, and the USA were efficient in environmental evaluation. The governments are suggested to adjust the resources management since the number of efficient units decreased in the economic assessment while fluctuating in the environmental assessment.

Green financing and resources utilization: A story of N-11 economies in the climate change era

Fossil fuel consumption has witnessed a significant surge in recent decades, resulting in the depletion of nonrenewable energy resources and adverse environmental repercussions. This scenario necessitates addressing the high-energy demands of developing countries’ energy-intensive sectors through an augmentation in renewable energy production capacity. Accordingly, the primary objective of this research is to scrutinize the influence of green finance and natural resource rents on environmental sustainability within the Next Eleven (N-11) countries from 2001 to 2018. To achieve this aim, the study employs several rigorous econometric techniques. Cross-sectional dependency is assessed using second-generation BP-LM, PS-LM, and Pesaran CD tests, while the unit root is examined using CIPS and CADF tests. Moreover, panel cointegration is assessed employing the Westerlund and Edgerton (2008) cointegration test. The most reliable Cup-FM and Cup-BC panel data estimators are utilized to ascertain long-run parameters precisely. The empirical findings of this research reveal that green financing contributes to a substantial reduction in carbon emissions. In contrast, natural resource rents exhibit detrimental effects on environmental sustainability. Consequently, the study advocates for the implementation of green strategies and policies to bolster green financing investments and regulate natural resource extraction. By doing so, the N-11 countries can work towards accomplishing their environmental sustainability objectives.