Share Of Renewable Generation Research Articles

Temporal regulation of renewable supply for electrolytic hydrogen

Electrolytic hydrogen produced using renewable electricity can help lower carbon dioxide emissions in sectors where feedstocks, reducing agents, dense fuels or high temperatures are required. This study investigates the implications of various standards being proposed to certify that the grid electricity used is renewable. The standards vary in how strictly they match the renewable generation to the electrolyser demand in time and space. Using an energy system model, we compare electricity procurement strategies to meet a constant hydrogen demand for selected European countries in 2025 and 2030. We compare cases where no additional renewable generators are procured with cases where the electrolyser demand is matched to additional supply from local renewable generators on an annual, monthly or hourly basis. We show that local additionality is required to guarantee low emissions. For the annually and monthly matched case, we demonstrate that baseload operation of the electrolysis leads to using fossil-fuelled generation from the grid for some hours, resulting in higher emissions than the case without hydrogen demand. In the hourly matched case, hydrogen production does not increase system-level emissions, but baseload operation results in high costs for providing constant supply if only wind, solar and short-term battery storage are available. Flexible operation or buffering hydrogen with storage, either in steel tanks or underground caverns, reduces the cost penalty of hourly versus annual matching to 7%–8%. Hydrogen production with monthly matching can reduce system emissions if the electrolysers operate flexibly or the renewable generation share is large. The largest emission reduction is achieved with hourly matching when surplus electricity generation can be sold to the grid. We conclude that flexible operation of the electrolysis should be supported to guarantee low emissions and low hydrogen production costs.

A Spatial Multicriteria Analysis for a Regional Assessment of Eligible Areas for Sustainable Agrivoltaic Systems in Italy

Agrivoltaics’ share of renewable generation is relevant for countries to achieve their energy transition targets. Agrivoltaics is the dual and synergistic use of the land by agricultural crop production and photovoltaic (PV) systems. For their development around a country, a fundamental step is to determine which areas are suitable. This research work has developed a methodological framework for a reliable agrivoltaic land eligibility analysis at regional scale based on a spatial multicriteria analysis (i.e., GIS/MCDM-AHP). The challenging step has been to select a set of relevant criteria, also based on experts’ knowledge, able to capture the factors that can affect both the solar PV potential and agriculture-oriented factors. On the basis of these criteria, properly weighted, a 30 m-resolution land eligibility map for agrivoltaic systems has been generated for the NUTS-2 regions of Italy. We have found that Italy has an eligible area of 10.7 million hectares and a capacity potential of 6435 GW, assuming an installed power density of 0.6 MW/ha. Thus, a land coverage of only 1.24% of this area would allow to reach the national 80 GW target of new renewable capacity to achieve the country’s decarbonisation and energy transition objectives by 2030. The potential of installed capacity results at GW scale for the main land categories of arable land and permanent crops if they are just covered by only 5% with agrivoltaic systems. Thus, the impact of agrivoltaic systems development on land occupation can be considered marginal especially in relation to benefits generated for both the energy and agricultural sectors. Such a method is essentially targeted to regional authorities for planning the sustainable development of agrivoltaic systems at the local level.

Metals at the nexus: renewable vs. nuclear energy systems, metal import requirements, and energy security in the European Union

This study examines the compatibility of the EU’s current 2050 clean energy transition plan, aiming to increase the share of renewable power generation to 80%, with mineral and energy security in the EU, acknowledging the interplay between these security aspects when dealing with metal-intensive energy systems. It also explores the potential advantages of an alternative electricity mix that combines the existing renewable generation share with expanded nuclear energy capacity. The results demonstrate that the planned renewable-intensive electricity mix requires substantially higher quantities of metals to increase and sustain electricity production capacity than the alternative nuclear-intensive system. This is not only the case in terms of volume requirements, which is already evident from the existing literature, but also in terms of value and import requirements. Further, our results reveal that the bottleneck risks in the planned renewable-intensive system are primarily associated with insufficient mining of essential metals inside the EU. In contrast, the bottleneck risks in the nuclear-intensive system are primarily associated with lack of processing inside the EU. Based on the assumption that acquiring relevant mineral reserves and mining capabilities may be more challenging than acquiring new processing capacities, this suggests that the planned renewable-intensive system may come with more serious bottleneck risks than an alternative nuclear-intensive system. Overall, this study leads to the conclusion that a nuclear-intensive electricity mix could offer greater metal-related energy security than the planned renewable-intensive system.

Optimal scheduling and management of pumped hydro storage integrated with grid-connected renewable power plants

Pumped hydro-energy storage will become a fundamental element of power systems in the coming years by adding value to each link in electricity production and the supply chain. The growth of these systems is essential for improving the integration of renewables and avoiding dependence on fossil fuel sources, such as gas or oil. This paper presents the modeling and application of an optimal hourly management model of grid-connected photovoltaic and wind power plants integrated with reversible pump-turbine units to maximize the monthly operating profits of the energy system and meet electricity demand. The techno-economic dispatch model is formulated as a mixed-integer optimization problem. To assess the proposed model, it is applied to a Spanish case study system, and the results are obtained for an entire year. The combination of renewable energy and pumped hydro energy storage reduces energy dependence by decreasing energy costs by 27 % compared with a system without storage to satisfy the required electricity demand. The findings confirm that storage plays a key role in energy transition to ensure the security and stability of power systems with a higher share of renewable generation.

Emission reduction pathways for satisfying Türkiye's future electricity demand: A cross-country dynamic panel analysis with linear programming scenarios

This paper studies whether feasible and plausible pathways exist for Türkiye to meet its growing electricity demand while reducing its emissions, by relying more on renewables, instead of increasing the use of its local coal resources. Our quantitative analysis proceeds in two stages. In the first stage, we determine the future electricity demand of Türkiye from 2020 to 2040 with the use of a dynamic panel data model. A 41-country balanced panel data set that comprises of five-year interval data, between 1990 and 2015. In the second stage, we develop linear programming models to generate realistic and reasonable scenarios representing three probable future pathways to meet the econometrically estimated electricity demand. The scenarios we have designed are business-as-usual (BAU), which includes the nuclear power plant, minimize GHGs (minGHG), and maximize local resources (MaxLocal). The latter scenarios omit the possible completion of the nuclear power plant in the next ten to twelve years. The generated scenarios are compared in terms of investment requirements and CO2e emissions. The model results of minGHG and MaxLocal both show that the share of renewable generation should reach around 65% to satisfy the projected demand by 2040. However, the difference in CO2e emissions (Mton/TWh) between the two cases is enormous: 0.408 for MaxLocal vs. 0.180 for minGHG! Moreover, required annual investment under minGHG is USD 0.19 billion cheaper on average (per year), which corresponds to a 21-year cumulative difference of USD 3.99 billion in current dollars. Therefore, a secure low-carbon pathway with a lower investment requirement is possible for Türkiye without nuclear power or new coal plants, while also phasing-out the existing coal plants under a moderate transition plan with a minimum amount of stranded assets.

Well-to-Wheels for Light-Duty Vehicle Powertrains by Segments in Isolated Systems

The transportation sector has the highest energy demand worldwide and bears the primary responsibility for CO2 emissions. Electromobility has emerged as the most feasible way to alleviate this problem. However, its potential depends heavily on the development of renewable energies. Island regions raise additional barriers to electromobility due to their heavy dependence on fossil fuels. This article addresses this challenge by presenting a comprehensive well-to-wheel framework to assess the levels of efficiency and CO2 emissions of electromobility options such as battery and plug-in electric vehicles (BEVs and PHEVs). The results were compared with those for internal combustion engine vehicles (ICEVs). The framework proposed takes account of various factors including the extraction, refining, and transport of oil, different segments of land vehicles, and electricity system operations. The framework is demonstrated with a case study of the Spanish Canary archipelago. The results show that BEVs improve efficiency and CO2 emissions by around 30% compared to ICEVs on islands where the share of renewable energies is higher than 21%. In contrast, limited renewable generation may lead to BEVs polluting up to 15% more than ICEVs. PHEVs should be considered as a suitable alternative if the share of renewable generation is higher than 35%.

Welfare optimal reliability and reserve provision in electricity markets with increasing shares of renewable energy sources

We develop an analytical model to derive the competitive market equilibrium for electricity spot and reserve markets under uncertain demand and renewable electricity generation. The first-best market equilibrium of the model resembles the result of a centralized co-optimization of the markets involved. We then derive the welfare-optimal provision of reserves. At first-best, cost of reserve capacity is balanced against expected cost of outages. Comparative statics and a numerical application based on German secondary reserve provision imply an increase of reserve provision with a growing share of renewable generation. Furthermore, a growing share of renewable generation decreases the level of reliability as measured in energy not served since required reserves to balance higher expected deviations will be more expensive, resulting in a trade-off between higher reserve costs and costs of energy not served.

Alberta's Renewable Electricity Program: Design, results, and lessons learned

We present a case study and analysis of Alberta's Renewable Electricity Program, one of a suite of policies implemented between 2015 and 2019 to increase the share of renewable generation in the Canadian province's fossil-fuel-dominated electricity system. The program consisted of a series of reverse auctions for contracts-for-differences which provided successful proponents with a project-specific guaranteed price for power generation. We find that the Renewable Electricity Program was successful in three important ways. First, it contracted for new renewable generation at prices in the range of CA$30 to CA$43/MWh (US$23 to US$33/MWh), well below expectations and among the lowest procurement costs globally at the time. These contracts have resulted in gains to the government of CA$75.5 million (US$60 million) to date. Second, the program ushered new entrants into Alberta's power market, including through mandated Indigenous equity participation in one round of auctions. Third, we find that price discovery and the incentive to develop new projects provided by the program spurred privately-financed development. While the program was a success, we argue that its design did not adequately reward high-value generation, which could have become an issue in future auction rounds. We analyse design alternatives that would have improved the program's dynamic efficiency.

Reviewing local and integrated energy system models: insights into flexibility and robustness challenges

The electrification of heating, cooling, and transportation to reach decarbonization targets calls for a rapid expansion of renewable technologies. Due to their decentral and intermittent nature, these technologies require robust planning that considers non-technical constraints and flexibility options to be integrated effectively. Energy system models (ESMs) are frequently used to support decision-makers in this planning process. In this study, 116 case studies of local, integrated ESMs are systematically reviewed to identify best-practice approaches to model flexibility and address non-technical constraints. Within the sample, storage systems and sector coupling are the most common types of flexibility. Sector coupling with the transportation sector is rarely considered, specifically with electric vehicles even though they could be used for smart charging or vehicle-to-grid operation. Social aspects are generally either completely neglected or modeled exogenously. Lacking actor heterogeneity, which can lead to unstable results in optimization models, can be addressed through building-level information. A strong emphasis on cost is found and while emissions are also frequently reported, additional metrics such as imports or the share of renewable generation are nearly entirely absent. To guide future modeling, the paper concludes with a roadmap highlighting flexibility and robustness options that either represent low-hanging fruit or have a large impact on results.

Stability Improvement of a Transmission Grid With High Share of Renewable Energy Using TSCOPF and Inertia Emulation

This paper proposes a Transient Stability Constrained Optimal Power Flow (TSCOPF) formulation that models non-synchronous renewable generation equipped with synthetic inertia. The proposed optimization problem calculates the optimal operating point of the system, accommodating high shares of non-synchronous renewable generation while ensuring transient stability in the event of critical incidents. Synthetic inertia controllers are used to improve the dynamic stability of the system in cases of very high share of renewable generation. The proposed tool is tested in the North-West Spanish system, a network with a high penetration of wind energy that causes a reduction in the total system inertia. The results of the study show that 1) synthetic inertia in renewable power plants can diminish electromechanical oscillations after a severe contingency, reducing the cost of ensuring transient stability; 2) using synthetic inertia the system becomes more stable when conventional generation is decommissioned following de-carbonization and renewable promotion policies; and 3) the proposed model can be used to calculate the parameters of the synthetic inertia control.

Increasing Needs and Solutions for Non-Baseload Operation of Nuclear Power Plants

Operation at steady full power, i.e. baseload operation, of nuclear power plants (NPPs) is usually considered to be the most efficient use of capital investment. Therefore, design and operation of most existing nuclear power plants (NPPs) are optimised to operate in baseload mode. Recently, there is an increasing need to operate NPPs in non-baseload mode, specifically performing frequency control and load following. These needs are typically due to a large nuclear generating capacity, increasing share of renewable generation, deregulation or evolution of the electricity supply systems and markets. Re-optimization of NPP design and operation for nonbaseload (flexible) mode of operation necessitates operational, economic and financial rearrangements to maintain the capital investment, in addition the adaptation of technical and regulatory changes. This paper discusses the aspects of design or operation of NPPs in flexible mode based on the existing knowledge and experience and it is primarily based on the recent study that was prepared by the International Atomic Energy Agency (IAEA).

Whole system value of long-duration electricity storage in systems with high penetration of renewables

Energy storage is a key enabling technology to facilitate an efficient system integration of intermittent renewable generation and support energy system decarbonisation. However, there are still many open questions regarding the design, capacity, and value of long-duration electricity storage (LDES), the synergy or competition with other flexibility technologies such as demand response, short-duration storage, and other forms of energy storage such as hydrogen storage. This paper presents a novel integrated formulation of electricity and hydrogen systems to identify the roles and quantify the value of long-duration energy storage holistically. A spectrum of case studies has been performed using the proposed approach on a future 2050 net-zero emission system back-ground of Great Britain (GB) with a high share of renewable generation and analysed to identify the value drivers, including the impact of prolonged low wind periods during winter, the impact of different designs of LDES, and its competitiveness and synergy with other technologies. The results demonstrate that high storage capacity can affect how the energy system will evolve and help reduce system costs.

Урахування використання акумуляційних систем у моделі прогнозування довгострокового розвитку електроенергетичної системи

The rapid growth of renewable generation share in the power systems worldwide, that could be explained by the world community desire for sustainable clean energy, combating the global climate change, has led to widespread use of wind and solar power plants as today’s most productive and competitive. With significant volumes of generation of these RES there are difficulties in the power system balancing due to insufficient flexibility of traditional generation, which limits electricity supply from renewables. The electricity storage is seemed to be a key solution to a number of technical and economic problems of the wind and solar power integration into the power system due to its unique ability to store and re-supply electricity to the grid. Electricity storage can be used to store excess volumes of renewable energy generation, which will be used later, minimizing or removing restrictions on supply of that excesses. The article presents approaches to taking into account the use of storage systems of electricity storage in a partial-integer model for forecasting of the power system generating capacity structure development. The use of storage system for the consumption/supply of electricity in the daily electrical load curves of the power system is modeled taking into account the available storage capacity. For hydropower the limitation of the water resource availability is taken into account. Battery energy storages ensure the transfer of excess power from wind and solar plants to the peaking periods of daily load if there is absent the possibility to ramp-down conventional generation during maximum wind and solar electric power production. Keywords: power system, the long-term development forecasting, mathematical model, energy storage system, load curve

Algorithm for optimal pairing of res and hydrogen energy storage systems

The global climate and environmental crisis dictate the need for the development and implementation of environmentally friendly and efficient technical solutions, for example, generation based on renewable energy sources. However, the annually increasing demand for electricity (according to the forecasts of the U.S. Energy Information Administration, the amount of energy consumed for the period 2006–2030 will increase by 44 %) cannot be fully provided by alternative energy. The main reason is not so much the high cost of these technologies, like unstable power generation, which determines the need for an additional reserve of regulated power.The solution to this problem can be the combined use of generation based on renewable energy sources with energy storage units of large capacity. Currently, a promising direction is the use of excess electricity for the production of hydrogen and its further accumulation in hydrogen storage. In this case an additional energy can be generated using industrial fuel cells (electrochemical generators) to compensate for the power shortage.At the same time, the distinctive advantage of hydrogen energy storage systems lies in the ability to accumulate a large amount of energy for long periods of time. This fact makes it possible to increase the reliability of the functioning of the electric power system, to provide power supply with a sufficiently long interruption (in case of faults) or allocation for isolated operation.With an increase in the unit capacity and the share of renewable generation in the total installed capacity, researches that aimed to systematic analysis of the impact of the implemented generation unit and the energy storage system on the parameters of the mode of the electric power system become more relevant. There are a number of tasks can be noted related to determining the optimal location and size of the generation unit and energy storage systems being implemented in terms of reducing power losses and maintaining an appropriate voltage level in the nodes of the electric power system. In this article, a variant of solving the optimization task for a typical 15-bus IEEE scheme is presented by means of software calculation using the bubble sorting method. To achieve this goal, the following tasks were solved: the objective function, which indicates the optimal location and size of the generation unit, and constraints, for example, the available deviation of voltage level, were formed; the software implementation of the algorithm for calculating power flows and power losses using the bubble sorting method was carried out. The results of the work of the program code for two scenarios are presented: for instance, installation of one renewable generation unit with a different range of possible capacities, and are compared with the data obtained in the MATLAB/Simulink software package.

CALCULATION OF OPTIMAL PARAMETERS FOR STORAGE AND RENEWABLE ENERGY SOURCES IN ISOLATED ENERGY SYSTEMS

A detailed substantiation of the use of electric energy storage devices in the presence of generators on renewable energy sources in the power supply system is given. The dependence of the storage parameters on the composition and priority of generation in the system is investigated. The solution of the problem of determining the parameters of electricity storage devices by means of purposeful simulation of generation parameters is considered. The results of the choice of power and capacity of the energy storage using technical and economic indicators are shown. Optimal parameters of electric energy storage devices as one of the most important means of ensuring the activity of isolated power supply systems together with selection of generating devices are determined. The results of calculations of capacity of renewable energy sources in isolated power supply systems in combination with classical energy sources are given. The necessity of using the principle of activity of the distribution electric network and the possibility of its realization is demonstrated. The optimal storage capacity as a function of the share of renewable generation, the non-integrated energy produced by renewable sources and the total storage capacity are plotted for several isolated systems. The main points of the used model of the power supply system of isolated networks are given. In the studied isolated power supply systems, wind power plants and solar power plants, which have significant unpredictability of generation, are used as generation based on renewable energy sources. The problem of undersupply of electricity to the grid by stepwise increase of generation is analysed. The results of the multi-step selection of power and energy consumption of electricity storage are determined by technical criteria.

Achieving long-term renewable energy goals: Do intermediate targets matter?

Policymakers in various countries often determine roadmaps, a sequence of intermediate goals to achieve their long-term renewable energy objectives. We study the influence of roadmaps on regulatory decisions and market functioning using laboratory experiments. We simulate a stylized electricity market with two generation technologies (a renewable “green” technology and a thermal source) whose share of renewable generation must increase over a 40-year period. Investments in thermal capacity are driven by subsidies and profitability, while green capacity investments solely depend on subsidies. Participants act as regulators and decide each year how many MWs of green and thermal capacity to subsidize while managing the trade-off between blackout risk, cost for customers and subsidies. We manipulate the presence and the time granularity of roadmaps.We find that roadmaps impact regulatory decisions and the resulting subsidies, but not the likelihood of achieving the long-term goals, illustrating that a given target can be reached by different trajectories with different costs. Therefore, policymakers should carefully consider the choice of intermediate objectives that impact paths toward greener energy in terms of trade-offs between governmental subsidies and market forces.

Probabilistic Analysis of Small Signal Stability of Power System with Penetration of Distributed Generation: A Review

The liberalization of electricity markets, continuous increase in power demand, shortage in conventional generating and transmission capacities and the environmental awareness of consumers contribute to the wide application of Distributed Generation (DG) into power systems. The presence of DG presents system operators with new challenges regarding DG availability, integration and impact on system security and stability. Therefore, analysis of renewable energy penetrated power system using probabilistic approaches is of utmost importance in other to ascertain the impact of intermittency of the renewable generation on the power network. This work firstly reviews the problem of instability of power systems with a considerable share of renewable generation and its significant demand for probabilistic analysis, then, provides a critical evaluation of the available probabilistic methods that have been used for the assessment of power system small signal stability. Overview of frequently used methods are presented stressing their advantages and disadvantages with the aim of highlighting their strength and weaknesses. This paper, then proposes a method known as Stochastic Collocation Method that promises to be an effective probabilistic tool for the analysis of renewable energy penetrated power system.

Scalable and Data Privacy Conserving Controller Tuning for Large-Scale Power Networks

The increasing share of renewable generation leads to new challenges in reliable power system operation, such as the rising volatility of power generation, which leads to time-varying dynamics and behavior of the system. To counteract the changing dynamics, we propose to adapt the parameters of existing controllers to the changing conditions. Doing so, however, is challenging, as large power systems often involve multiple subsystem operators, which, for safety and privacy reasons, do not want to exchange detailed information about their subsystems. Furthermore, centralized tuning of structured controllers for large-scale systems, such as power networks, is often computationally very challenging. For this reason, we present a hierarchical decentralized approach for controller tuning, which increases data security and scalability. The proposed method is based on the exchange of structured reduced models of subsystems, which conserves data privacy and reduces computational complexity. For this purpose, suitable methods for model reduction and model matching are introduced. Furthermore, we demonstrate how increased renewable penetration leads to time-varying dynamics on the IEEE 68-bus power system, which underlines the importance of the problem. Then, we apply the proposed approach on simulation studies to show its effectiveness. As shown, similar system performance as with a centralized method can be obtained. Finally, we show the scalability of the approach on a large power system with more than 2500 states and about 1500 controller parameters.

Reinforcement learning in local energy markets

Local energy markets (LEMs) are well suited to address the challenges of the European energy transition movement. They incite investments in renewable energy sources (RES), can improve the integration of RES into the energy system, and empower local communities. However, as electricity is a low involvement good, residential households have neither the expertise nor do they want to put in the time and effort to trade themselves on their own on short-term LEMs. Thus, machine learning algorithms are proposed to take over the bidding for households under realistic market information. We simulate a LEM on a 15 min merit-order market mechanism and deploy reinforcement learning as strategic learning for the agents. In a multi-agent simulation of 100 households including PV, micro-cogeneration, and demand shifting appliances, we show how participants in a LEM can achieve a self-sufficiency of up to 30% with trading and 41,4% with trading and demand response (DR) through an installation of only 5kWp PV panels in 45% of the households under affordable energy prices. A sensitivity analysis shows how the results differ according to the share of renewable generation and degree of demand flexibility.

Exploring the cost implications of increased renewable energy for the U.S. power system

Over the last decade, the fraction of annual U.S. electricity generation for renewable energy has doubled from 10 % to 20 %. This growth has been driven by several factors, including technology cost reductions and policy support. The share of renewable generation is projected to increase over time. Reference case scenarios from four different organizations show least-cost U.S. electricity buildouts with renewable energy generation fractions of 31–36 % by 2030 and 40–65 % by 2050. Using a capacity expansion modeling tool, we investigate how changing the amount of renewable energy from the least-cost solution impacts the cost of building and operating the electricity system. The relationship between system cost and renewable energy generation fraction is non-linear. Small deviations near the least-cost solution have minimal cost impacts (changing the renewable energy penetration by +/- 5% results in system cost changes of less than 1%), while similar deviations that are farther from the least-cost solution can result in large cost changes. Increased levels of RE lead to lower absolute emissions, and we evaluate the trade-offs between emissions savings and system costs for higher and lower levels of RE penetration.