Share Of Renewable Power Generation Research Articles

CO2 Capture Cost Reduction Potential of the Coal-Fired Power Plants under High Penetration of Renewable Power in China

With a significant share of renewable power generation integrated into the power supply, it is crucial to timely adjust the regulating peak load for coal-fired power plants equipped with CO2 capture to ensure the stable operation of the multi-energy supply system. In this paper, the effects of varying boiler loads on the techno-economic performance of the retrofitted power plant were studied. Furthermore, the potential for reducing the cost of CO2 capture was investigated, and early opportunities for demonstration were discussed. Results showed that when the boiler load decreased from 100% turbine heat acceptance condition to 50% turbine heat acceptance condition, the cost of CO2 capture increased from 37.0 $/t CO2 to 57.0 $/t CO2, cost contribution of energy penalty and extra capital investment also increased from 20.6 $/t-CO2 to 25.7 $/t-CO2, and from 16.4 $/t-CO2 to 31.3 $/t-CO2, respectively. Furthermore, by improving separation efficiency from 0.15 to 0.5, a 25% to 30% reduction in CO2 capture cost can be achieved. The cost of CO2 capture could decrease by 42.2–50.5% when the cumulative capacity reaches 250 GW under the high investment learning rate scenario. According to the distribution of coal prices and renewable energy sources in China, the early demonstration projects of multi-energy supply systems should prioritize the northern region. The results of this work can provide informative references for making roadmaps and policies for CO2 emission reduction toward carbon neutrality.

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.

Validation of and Simulations using a High-Temperature Electrolysis Model

Efforts for increasing the share of renewable power generation are dramatically boosted since electrical power from fossil fuels has been used as weapon [1]. Therefore, efficient conversion systems are of great importance to conserve most of the delivered power by nature. High-temperature electrolysis is such an efficient type of energy conversion system compared to similar technologies [2-4]. To bridge the gap to an industrial scale application, the electrochemical and chemical processes have to be understood in detail which is enlightened by some publications from our group [5-8]. In this contribution, a multiphysics model for three types of electrolysis processes (steam, CO2 and co-electrolysis) is presented and evaluated. Relevant parameters like the exchange current density or the anodic / cathodic transfer coefficient including parameter variations for the inlet gas stream, flow rate of the gas, temperature and applied current are investigated. For the microscale properties in the functional layer, Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) is used with the “Slice and View” technique [9,10]. Extracting information like the Triple Phase Boundary Length (TPBL), the fraction of electronic and ionic phase in mixed ionic-electronic conducting (MIEC) materials or the porosity and tortuosity of the (La,Sr)CoO3-δ (LSC) air electrode and the Ni / 8 mol% yttria stabilized zirconia (Ni-8YSZ) fuel electrode help in enhancing the modeling quality of high-temperature SOC model. A conversion from the TPBL (s. Figure 1) to an active area to volume ratio for the computation is needed.Calculated iV-characteristics and experimental curves are compared and serve as a validation for (I,V) data points at higher currents. Depending on the degree of agreement, the (missing) main contributions to loss mechanisms can be identified and initiate a feedback loop for material optimization. Sensitivity analyses are carried out for parameters that are difficult to vary in experiments (e.g. porosity). Porosity and tortuosity parametrize the porous structure for a homogeneously distributed property assumption across the material layers. The ratio between electronic and ionic phase fine-tunes the positioning of iV-characteristics within the potential regime of Ohmic and polarization losses. Calculated electrochemical impedance spectra (EIS) enhance the insight into the theoretical system and may be compared to experimental spectroscopy data via Equivalent Circuit Models (ECM). Calculated data from the model are acquired as in the used experimental setup. As an example, calculated EIS data from steam electrolysis show good agreement with a R-(RQ)4 ECM which as well describes most of the corresponding experimental data in our group. Effects of degradation are envisioned to be incorporated into the model as well.[1] Hosp, G.; Höltschi, R.; Keusch, N.; Schürpf, T.: https://www.nzz.ch/wirtschaft/rohstoffe-als-waffen-die-neusten-entwicklungen-ld.1681268 (28th October 2022, 2.13 pm)[2] Foit, S.R.; Dittrich, L.; Duyster, T.; Vinke, I.; Eichel, R.-A.; de Haart, L.G.J. (2020): Direct Solid Oxide Electrolysis of Carbon Dioxide: Analysis of Performance and Processes. In: Processes 8 (11), 1390[3] Foit, S.R.; Vinke, I.C.; de Haart, L.G.J.; Eichel, R.-A. (2017): Power-to-Syngas: An Enabling Technology for the Transition of the Energy System? In: Angew. Chem. Int. Edit. 56 (20), 5402–5411[4] Tanaka, Y.; Hoerlein, M.P.; Schiller, G. (2016): Numerical simulation of steam electrolysis with a solid oxide cell for proper evaluation of cell performances. In: Int. J. Hydrogen Energ. 41, 752–763[5] Wolf, S.E.; Dittrich, L.; Nohl, M.; Duyster, T.; Vinke, I.C.; Eichel, R.-A.; de Haart, L.G.J. (2022): Boundary Investigation of High-Temperature Co-Electrolysis Towards Direct CO2 Electrolysis. In: J. Electrochem. Soc. 169, 034531[6] Unachukwu, I.D.; Vibhu, V.; Vinke, I.C.; Eichel, R.-A.; de Haart, L.G.J. (2022): Sr Substituted La2-xSrxNi0.8Co0.2O4+ d (0 ≤ x ≤ 0.8): Impact on Oxygen Stoichiometry and Electrochemical Properties.In: Energies 15, 2136[7] Mebrahtu, C.+; Nohl, M.+; Dittrich, L.; Foit, S.R.; de Haart, L.G.J.; Eichel, R.-A.; Palkovits, R. (2021): Integrated Co-Electrolysis and Syngas Methanation for the Direct Production of Synthetic Natural Gas from CO2 and H2O. In: ChemSusChem 14, 2295 – 2302[8] Dittrich, L.; Nohl, M.; Jaekel, E.E.; Foit, S.R.; de Haart, L.G.J. (Bert), Eichel, R.-A. (2019): High-Temperature Co-Electrolysis: A Versatile Method to Sustainably Produce Tailored Syngas Compositions. In: J. Electrochem. Soc. 166 (13), F971 – F975[9] Wilson, J.R.; Kobsiriphat, W.; Mendoza, R.; Chen, H.; Hiller, J.M.; Miller, D.J.; Thornton, K.; Voorhees, P.W.; Adler, S.B.; Barnett, S.A. (2006): Three-dimensional reconstruction of a solid-oxide fuel-cell anode. In: Nat. Mater. 5, 541–544[10] Gostovic, D.; Smith, J.R.; Kundinger, D.P.; Jones, K.S.; Wachsman, E.D. (2007): Three-Dimensional Reconstruction of Porous LSCF Cathodes. In: Electrochem. Solid St. 10 (12), B214–B217Figure 1: Histogram of the TPBL from a 400 image sample set of a FIB-SEM cut of a Ni-8YSZ electrode. Figure 1

Power system coherency recognition and islanding: Practical limits and future perspectives

AbstractElectrical power systems are continuously upgrading into networks with a higher degree of automation capable of identifying and reacting to different events that may trigger undesirable situations. In power systems with decreasing inertia and damping levels, poorly damped oscillations with sustained or growing amplitudes following a disturbance may eventually lead to instability and provoke a major event such as a blackout. Additionally, with the increasing and considerable share of renewable power generation, unprecedented operational challenges shall be considered when proposing protection schemes against unstable electro‐mechanical (e.g. ringdown) oscillations. In an emergency situation, islanding operations enable splitting a power network into separate smaller networks to prevent a total blackout. Due to such changes, identifying the underlying types of oscillatory coherency and the islanding protocols are necessary for a continuously updating process to be incorporated into the existing power system monitoring and control tasks. This paper examines the existing evaluation methods and the islanding protocols as well as proposes an updated operational guideline based on the latest data‐analytic technologies.

Combined static and dynamic dispatch of integrated electricity and heat system: A real-time closed-loop demonstration

Coupling the electricity and heating systems introduce opportunities to handle the intermittent nature of an increasing share of renewable power generation. Coordination of units in the coupled systems requires careful static dispatch towards an optimization objective. As the uncertainties in renewable forecasting are reduced towards operation time, operators can perform dispatch numerous times to balance the determined mismatches. With higher shares of renewable, sudden changes in power generation due to changing weather can cause a power imbalance that disturbs the system frequency. To handle such hazards, dynamic dispatch in the form of frequency control is necessary. Recent literature in integrated electricity and heating systems (IEHS) is studied in this work to combine the static and dynamic dispatch of units. A two-stage stochastic day-ahead scheduling method combined with a model predictive control (MPC) -based real-time optimal operation method that allocates both following and regulating reserves is used as the static dispatch of the IEHS. The allocated reserves constrain the performance of the dynamic dispatch by limiting the control capacity. In this work, an MPC coordinated frequency control of small- and large-scale heat pumps is considered as the dynamic dispatch of the IEHS. The performance of the dynamic dispatch is evaluated through a real-time closed-loop simulation platform, where the system conditions of the static dispatch are used as the steady-state conditions. Results show that despite challenging communication conditions, the frequency control of small- and large-scale heat pumps improves frequency nadir conditions after a power imbalance.

Organic Redox Flow Batteries: Insights from Experimental and Numerical Study

Secondary batteries are the key technology for the sustainable development of electrical grids with a high share of renewable power generation. Among different battery technologies, Organic Redox Flow Batteries (ORFBs) are considered one of the most promising solutions for low-cost large-scale energy storage systems thus avoiding the social and environmental issues associated with extraction of raw materials for large batteries. Mathematical modeling of ORFBs, that complements experimental testing, is a key tool that helps to understand and analyze the behavior of particular candidates, including electrolytes, membranes and geometrical parameters, on a battery level at operating conditions that are close to operational.In this study, we present a single-cell zero-dimensional model based on our previous works [1,2] extended for simulation of redox flow batteries with different organic redox-couples. The model is based on the general mass and charge conservation principles. Hence, it can simulate a wide range of RFB systems with different scales and electrolytes. The key feature of the model is the approach for the determination of integral mass-transfer coefficient on the electrode-electrolyte interface that allows describing non-linear polarization behavior at high current densities. Such approach makes the model very flexible and esilty extadable even to the other types of batteries with hybrid configurations (e.g. solid boosters). The kinetic parameters were also fitted for the effective single-step heterogeneous redox mechanisms at positive and negative electrodes in the case when activation losses treatment was needed to reproduce the experimental polarization curves. In addition, the model simulates the dynamic behavior of the cells working with different redox-couples in the wide range of loading currents and electrolyte flow rate and thus allowing to explore their performance at different operating conditions. Validation of the model showed a good agreement with experimental data (average error less than 5%) in the range of current decities of 20 – 150 mA cm-2.The model was also used for investigation of scalability of the considered ORFBs analyzing their performance on the level of industial-scale systems.The influence of internal processes on the battery behavior has been studied and the effect of mass-transport limitations has been estimated. The key parameters (coulombic, voltage, energy efficiencies and electrolyte utilization) of the batteries have been computed for the wide range of current densities and flow rates. The obtained results provide important insights for reserachers and ingeneers to develop reliable and efficient organic RFB systems applicable for grid-scale energy storage systems.

Identification of Overpotentials in Vanadium Redox Flow Battery with Reference Electrodes and Determination of Apparent Electrochemical Rate Constants

Vanadium redox flow battery (VRFB) is an amateur technology that passed pilot stages in fulfilling the stationary applications at the energy storage market with a high share of renewable power generation. The commercial applications of VRFBs require the optimization of their internal losses and developing the optimal control strategies for in-grid operation. This calls for a deep understanding of the internal VRFB processes, which greatly benefit from both the mathematical modeling and experimental testing for the model validation and refinement.However, the available experimental data for VRFBs is usually limited by open-circuit voltage (OCV) and potential (OCP), charge/discharge voltage profiles at constant load current, full cell polarization curves at the fixed state of charge (SOC), and internal stack ohmic resistances. This also complicates the decoupling and accessing the voltage loss sources, with the prevailing ones usually classified as ohmic, concentration, and activation overpotentials. As such, Aaron et al. (1) showed that decoupling of overpotentials at positive and negative half-cell requires the half-cell potentials measurements with reference electrodes (RE) in addition to full cell data. Different configurations of RE incorporation (2–4) were suggested with a limited agreement with full cell experimental data. The alternative approach with extrapolation of parameters presented in the literature is also challenging due to their strong dependence on an experimental protocol (e.g., the electrode material and its pre-treatment procedure, a membrane, and a setup geometry). As an illustration, the comprehensive review Roznyatsovskaya et al. (5) highlights the four orders of magnitude difference in reported surface area-normalized rate constants. Therefore, the development of a self-consistent experimental setup is crucial for understanding and decoupling internal losses for flow batteries. Combined with VRFB modeling, this may extend accurate predictions of its operation at extreme SOCs and load currents, where voltage losses hamper the efficiency of the battery with the dominating ones usually attributed to concentration (mass-transport in solutions) and activation (sluggish kinetics of reactions on electrodes) overpotentials.Herein, we developed the experimental setup adopting a 5cm2 single flow cell equipped with reference electrodes at positive and negative sides. The experiments were performed in symmetric and full cell designs. The polarization curves were measured at different SOCs [10 – 90 %], electrolyte flow rates [5-30 ml min-1], and load currents. The additional effort was made to compare the results of the experiments in symmetric and full cell designs and extract the apparent kinetic rate constants for positive and negative half-cells. The latter was performed within the 0D modeling approach, which is based on general mass and charge conservation principles. The key feature of the model is the approach for the determination of the integral mass-transfer coefficient on the electrode-electrolyte interface that allows describing non-linear polarization behaviour at high current densities. The effective thermodynamically consistent single-step reaction mechanisms were considered at both half cells, thus decreasing the number of free kinetic parameters. Overall, the proposed approach demonstrated the growing impact of the membrane losses at high current densities. The extracted apparent rate constants under conditions of a real flow battery provide important insights for developing reliable and efficient VRFBs applicable for energy storage systems.1 D. Aaron, Z. Tang, A. B. Papandrew and T. A. Zawodzinski, J. Appl. Electrochem., 2011, 41, 1175–1182.2 H. Lim, J. S. Yi and D. Lee, J. Power Sources, 2019, 422, 65–72.3 S. Ressel, A. Laube, S. Fischer, A. Chica, T. Flower and T. Struckmann, J. Power Sources, 2017, 355, 199–205.4 M. Cecchetti, A. Casalegno and M. Zago, J. Power Sources, 2018, 400, 218–224.5 N. Roznyatovskaya, J. Noack, K. Pinkwart and J. Tübke, Curr. Opin. Electrochem., 2020, 19, 42–48.

Smart Grid for Industry Using Multi-Agent Reinforcement Learning

The growing share of renewable power generation leads to increasingly fluctuating and generally rising electricity prices. This is a challenge for industrial companies. However, electricity expenses can be reduced by adapting the energy demand of production processes to the volatile prices on the markets. This approach depicts the new paradigm of energy flexibility to reduce electricity costs. At the same time, using electricity self-generation further offers possibilities for decreasing energy costs. In addition, energy flexibility can be gradually increased by on-site power storage, e.g., stationary batteries. As a consequence, both the electricity demand of the manufacturing system and the supply side, including battery storage, self-generation, and the energy market, need to be controlled in a holistic manner, thus resulting in a smart grid solution for industrial sites. This coordination represents a complex optimization problem, which additionally is highly stochastic due to unforeseen events like machine breakdowns, changing prices, or changing energy availability. This paper presents an approach to controlling a complex system of production resources, battery storage, electricity self-supply, and short-term market trading using multi-agent reinforcement learning (MARL). The results of a case study demonstrate that the developed system can outperform the rule-based reactive control strategy (RCS) frequently used. Although the metaheuristic benchmark based on simulated annealing performs better, MARL enables faster reactions because of the significantly lower computation costs for its own execution.

Power market design choices with high shares of intermittent renewables

The European Commission's long-term strategy envisages a carbon neutrality of the economy by 2050. There is a general consensus that in this context, a high share of renewable power generation will be photovoltaic- and wind-based. This has two implications for the power market functioning: (i) the energy system becomes necessarily more decentralised while current markets, based on a zonal representation of the transmission network, are not able to capture this dimension. This study provides an overview on key choices to be made when designing local markets. (ii) Also the study raises the question whether markets dominated by intermittent renewable energy source can be organised in a decentral way (current reference in European power markets) or whether some level of centralisation (as typically in most of US markets) is required to coordinate market and network operation.

Flow tracing as a tool set for the analysis of networked large-scale renewable electricity systems

The method of flow tracing follows the power flow from net-generating sources through the network to the net-consuming sinks, which allows to assign the usage of the underlying transmission infrastructure to the system participants. This article presents a reformulation that is applicable to arbitrary compositions of inflow appearing naturally in models of large-scale electricity systems with a high share of renewable power generation. We propose an application which allows to associate power flows on the grid to specific regions or generation technologies, and emphasizes the capability of this technique to disentangle the spatio-temporal patterns of physical imports and exports occurring in such systems. The analytical potential of this method is showcased for a scenario based on the IEEE 118 bus network.

Power-to-Syngas: An Enabling Technology for the Transition of the Energy System?

Power-to-X concepts promise a reduction of greenhouse gas emissions simultaneously guaranteeing a safe energy supply even at high share of renewable power generation, thus becoming a cornerstone of a sustainable energy system. Power-to-syngas, that is, the electrochemical conversion of steam and carbon dioxide with the use of renewably generated electricity to syngas for the production of synfuels and high-value chemicals, offers an efficient technology to couple different energy-intense sectors, such as "traffic and transportation" and "chemical industry". Syngas produced by co-electrolysis can thus be regarded as a key-enabling step for a transition of the energy system, which offers additionally features of CO2 -valorization and closed carbon cycles. Here, we discuss advantages and current limitations of low- and high-temperature co-electrolysis. Advances in both fundamental understanding of the basic reaction schemes and stable high-performance materials are essential to further promote co-electrolysis.

Decentralized price-driven grid balancing via repurposed electric vehicle batteries

The share of electricity generated from intermittent renewable sources, e.g., wind and solar grows rapidly. This affects grid stability and power quality. If the share of renewable power generation is to be increased further, additional flexibilities must be introduced.Aggregating small, distributed loads and energy storage facilities is a good medium-term option. In this paper, the suitability of decentralized and on-site optimized storage system consisting of repurposed electric vehicle batteries for grid balancing is investigated. Battery operation is controlled via an optimization procedure, which relies on a one-way communicated pseudo-cost function (PCF). Day-ahead electricity stock market prices are used as the PCF.Based on one year simulations, a sequential quadratic programming (SQP) approach is compared to a dynamic programming (DP) and an integer linear programming (ILP) approach with respect to runtime and control objective. All approaches lead to very similar results, however ILP leads to the shortest runtimes. ILP is then used to investigate the grid balancing potential using last decade's hourly day-ahead prices. Higher market data resolutions featuring quarter-hours introduced in 2014 lead to higher earnings. For hourly day-ahead prices the optimal capacity-to-power ratio of the battery is approximately 6 h while for quarter-hourly prices it is about 3 h.

Planning renewable energy in electric power system for sustainable development under uncertainty – A case study of Beijing

An interval type-2 fuzzy fractional programming (IT2FFP) method is developed for planning the renewable energy in electric power system for supporting sustainable development under uncertainty. IT2FFP can tackle output/input ratio problems where complex uncertainties are expressed as type-2 fuzzy intervals (T2FI) with uncertain membership functions. The IT2FFP method is then applied to planning Beijing electric power system, where issues of renewable energy utilization, electricity supply security, and pollutant/greenhouse gas (GHG) emissions mitigation are incorporated within the modeling formulation. The obtained results suggest that the coal-fired power would continue to decrease and the share of renewable energy in gross electricity supply would maintain an increasing trend. Results also reveal that imported electricity plays a significant role in the city’s energy supply. A number of decision alternatives are also analyzed based on the interval solutions as well as the projected applicable conditions, which represent multiple options with sustainable and economic considerations. The optimal alternative that can give rise to the desirable sustainable option under the maximization of the share of renewable power generation has been suggested. The findings can help decision makers identify desired alternatives for managing such a mixed energy system in association with sustainable development. Compared with the conventional optimization methods that optimize single criterion, it is proved that IT2FFP is advantageous in balancing conflicting objectives and reflecting complicated relationships among multiple system factors as well as in tackling various subjective judgments of decision makers with different interests and preferences.

A new approach of clustering operational states for power network expansion planning problems dealing with RES (renewable energy source) generation operational variability and uncertainty

The global drive for integration of RESs (renewable energy sources) means they will have an increasing role in power systems. It is inevitable that such resources introduce more operational variability and uncertainty to system functioning because of their intermittent nature. As a result, uncertainty management becomes a critical issue in long-term TEP (Transmission Expansion Planning) in power systems which feature a significant share of renewable power generation, especially in terms of computational requirements. A significant part of this uncertainty is often handled by a set of operational states, here referred to as “snapshots”. Snapshots are generation—demand patterns that lead to OPF (optimal power flow) patterns in the network. A set of snapshots, each one with an estimated probability, is then used in network expansion optimization. In long-term TEP of large networks, the amount of operational states must be reduced to make the problem computationally tractable. This paper shows how representative snapshots can be selected by means of clustering, without relevant loss of accuracy in a TEP context, when appropriate classification variables are used for the clustering process. The approach relies on two ideas. First, snapshots are characterized by their OPF patterns instead of generation—demand patterns. This is simply because network expansion is the target problem, and losses and congestions are the drivers of network investments. Second, OPF patterns are classified using a “moments” technique, a well-known approach to address Optical Pattern Recognition problems. Numerical examples are presented to illustrate the benefits of the proposed clustering methodology. The method seems to be very promising in terms of clustering efficiency and accuracy of the TEP solutions.

Renewable Power Generation Indian Scenario: A Review

—India is faced with the major challenges of (a) providing energy access to all its citizens, (b) heavy dependence on fuel imports for energy security, and (c) complying with international protocols on climate change mitigation, although the economic and social development is the foremost priority. The increase in energy demand due to growing population and industrialization in the face of depleting fossil fuel resources has stimulated the country's efforts in adopting power generation from renewable energy sources. Starting with 0.34 GW (2%) out of 17 GW of the country's total installed capacity in the year 2002, the share of renewable power generation has reached 31.7 GW (12.5%) of 250 GW as of 2014. In the aspect of total installed renewable power generation, India occupies the fifth position in the world today. While the governmental policies have steadily encouraged the adoption of renewable power generation, there is need and potential for more vigorous engagement in pursuit of achieving power for all citizens along with economic development. This article presents a brief review of emergence and growth of renewable power generation in India, wind and solar sectors in particular.

Modelling renewable energy impact on the electricity market in India

Renewable power generation development, most notably for wind and solar, has taken off at a rapid pace in India especially in the last 4 years. While these developments have many positive aspects, a rapid shift in balance of baseload and intermittent generation must be assessed carefully to ensure the share of renewable power generation increases without compromising system security and economics. Seasonal and spatial variability of wind, and to a lesser extent that of solar, can render these resources to have low availability for a significant part of the year leading to an increase in unserved energy, i.e., deteriorate system reliability. The intermittency of generation also impacts on inter-state power flows and lead to higher congestion in the grid. Climate model results provide a rich set of information on the nature of solar/wind variability that can be embedded in an electricity market simulation tool to assess these impacts on prices, generation dispatch and power flows. We have developed a modelling analysis for the Indian national electricity market informed by CSIRO climate model results. We have assessed the added costs arising from intermittency to put in perspective the true costs and benefits of renewable power. We have focused on the near-term developments in 2017 to show how some of the high renewable growth scenarios included in the Indian National Electricity Plan may imply significant pressure on inter-state/region transfer capability, and lead to a significant worsening of system reliability. The outcome of our modelling analysis suggests that a more orderly and balanced development of renewable and conventional power generation capacity is needed with a stronger focus on system economics and security.

Seasonal optimal mix of wind and solar power in a future, highly renewable Europe

The renewable power generation aggregated across Europe exhibits strong seasonal behaviors. Wind power generation is much stronger in winter than in summer. The opposite is true for solar power generation. In a future Europe with a very high share of renewable power generation those two opposite behaviors are able to counterbalance each other to a certain extent to follow the seasonal load curve. The best point of counterbalancing represents the seasonal optimal mix between wind and solar power generation. It leads to a pronounced minimum in required stored energy. For a 100% renewable Europe the seasonal optimal mix becomes 55% wind and 45% solar power generation. For less than 100% renewable scenarios the fraction of wind power generation increases and that of solar power generation decreases.