Future Power Sector Research Articles

Pv-load matching based on combination of different consumers: A case study in Swedish contexts

The transition towards sustainability necessitates robust growth of renewable energy, especially solar power. However, increasing the shares of solar power may lead to mismatch of electricity supply and demand, thus worse solar power performance could be received due to lower self-consumption and self-sufficiency. This issue has attracted more attention recently as it also requires additional costs for controlling and battery integration. This study combines several load profiles from consumers having different behaviors with different proportions to find out the optimal shares with higher level of PV penetration and self-sufficiency. A visualizing matching layout is proposed to present the PV-load matching level of all the possibilities at different seasons based on a Swedish context. It is found an 8% improvement of self-sufficiency reaching 70% in summer without additional equipment and scarification of self-consumption. The results could assist in the design and planning of the future power sector. Regarding specific targets, various optimal solutions could be found based on the layout.

Complementary potential of wind-solar-hydro power in Chinese provinces: Based on a high temporal resolution multi-objective optimization model

In the context of carbon neutrality, renewable energy, especially wind power, solar PV and hydropower, will become the most important power sources in the future low-carbon power system. Since wind power and solar PV are specifically intermittent and space-heterogeneity, an assessment of renewable energy potential considering the variability of wind power and solar PV with high temporal resolution in different regions will facilitate more accurate identification of the decarbonization pathway of power system. In this paper, the complementary output potential of wind-solar-hydro power every 15 min in 31 Chinese provinces is evaluated by developing a multi-objective optimization model based on Nondominated Sorting Genetic Algorithm II. The results show that the total annual complementary power generation potential in China is 17.57 PWh, of which the three components account for 47.8%, 25.3% and 26.9%, respectively. Inner Mongolia and Tibet are the major renewable energy source provinces with annual complementary power generation potential of 5330 TWh and 3907 TWh, accounting for 30.3% and 13.7% of the total power generation potential, respectively. The temporal potential of wind-solar-hydro power varies greatly, with daily potential is more volatile than monthly. Seasonal and spatial heterogeneity of the complemental renewable potential makes some provinces suffer power shortage during long-hours period especially in winter. Our findings will encourage a higher penetration of renewable energy, the promotion of multi-energy complementarity, and the development of inter-provincial power transmission and energy storage infrastructure in China's future power sector.

Flexible supply meets flexible demand: prosumer impact on strategic hydro operations

Ambitious climate packages promote the integration of variable renewable energy (VRE) and electrification of the economy. For the power sector, such a transformation means the emergence of so-called prosumers, i.e., agents that both consume and produce electricity. Due to their inflexible VRE output and flexible demand, prosumers will potentially add endogenous net sales with seasonal patterns to the power system. With its vast hydro reservoirs and ample transmission capacity, the Nordic region is seemingly well positioned to cope with such intermittent VRE output. However, the increased requirement for flexibility may be leveraged by incumbent producers to manipulate prices. Via a Nash-Cournot model with a representation of the Nordic region’s spatio-temporal features and reservoir volumes, we examine how hydro producers’ ability to manipulate electricity prices through temporal arbitrage is affected by (i) VRE-enabled prosumers and (ii) the latter plus a high CO_2 price. We find that hydro reservoirs could exploit prosumers’ patterns of net sales to conduct temporal arbitrage more effectively, viz., by targeting periods in which prosumers are net buyers (net sellers) to withhold (to “dump”) water. Meanwhile, a higher CO_2 price would further enhance hydro reservoirs’ market power because flexible price-taking thermal plants would be unable to ramp up production in order to counter such producers’ strategy to target VRE’s intermittency. Hence, in spite of a flexible demand side to complement additional intermittent VRE output, strategic hydro producers may still exacerbate price manipulation in a future power sector via more tailored exercise of market power.

Future demand for electricity generation materials under different climate mitigation scenarios

<h2>Summary</h2> Achieving global climate goals will require prodigious increases in low-carbon electricity generation, raising concerns about the scale of materials needed and associated environmental impacts. Here, we estimate power generation infrastructure demand for materials and related carbon-dioxide-equivalent (CO₂eq) emissions from 2020 to 2050 across 75 different climate-energy scenarios and explore the impact of climate and technology choices upon material demand and carbon emitted. Material demands increase but cumulatively do not exceed geological reserves. However, annual production of neodymium (Nd), dysprosium (Dy), tellurium (Te), fiberglass, and solar-grade polysilicon may need to grow considerably. Cumulative CO₂ emissions related to materials for electricity infrastructure may be substantial (4–29 Gt CO₂eq in 1.5°C scenarios) but consume only a minor share of global carbon budgets (1%–9% of a 320 Gt CO₂eq 1.5°C 66% avoidance budget). Our results highlight how technology choices and mitigation scenarios influence the large quantities of materials mobilized during a future power sector decarbonization.

Inequality in air pollution mortality from power generation in India

India’s coal-heavy electricity system is the world’s third largest and a major emitter of air pollution and greenhouse gas emissions. Consequently, it remains a focus of decarbonization and air pollution control policy. Considerable heterogeneity exists between states in India in terms of electricity demand, generation fuel mix, and emissions. However, no analysis has disentangled the expected, state-level spatial differences and interactions in air pollution mortality under current and future power sector policies in India. We use a reduced-complexity air quality model to evaluate annual PM2.5 mortalities associated with electricity production and consumption in each state in India. Furthermore, we test emissions control, carbon tax, and market integration policies to understand how changes in power sector operations affect ambient PM2.5 concentrations and associated mortality. We find poorer, coal-dependent states in eastern India disproportionately face the burden of PM2.5 mortality from electricity in India by importing deaths. Wealthier, high renewable energy states in western and southern India meanwhile face a lower burden by exporting deaths. This suggests that as these states have adopted more renewable generation, they have shifted their coal generation and associated PM2.5 mortality to eastern areas. We also find widespread sulfur emissions control decreases mortality by about 50%. Likewise, increasing carbon taxes in the short term reduces annual mortality by up to 9%. Market reform where generators between states pool to meet demand reduces annual mortality by up to 8%. As India looks to increase renewable energy, implement emissions control regulations, establish a carbon trading market, and move towards further power market integration, our results provide greater spatial detail for a federally structured Indian electricity system.

Optimal Sizing of Hybrid Energy System Using Random Exploratory Search-Centred Harris Hawks Optimizer with Improved Exploitation Capability

Due to the depletion of traditional energy resources, emissions of greenhouse gases, climate change, etc., renewable energy resources (RER) based power generation is becoming the main source of the present and future power sector. The major RERs, including solar, wind, and small hydro, may provide reliable and sustainable solutions in the smart grid environment. Solar and wind energy-based power generation is more prevalent but varies in nature and is not even very predictable very efficiently. Therefore, it has become necessary to integrate two or more RER and develop a hybrid energy system (HES). The HESs provide a cost-effective and reliable power supply with reduced and/or almost negligible greenhouse gas emissions as well. Due to economic and power reliability concerns, the optimal sizing of components is necessary for the development of an optimum HES. In recent years, metaheuristic evolutionary algorithms have been widely used for optimal sizing of HES. Harris hawk’s optimizer (HHO) is a recently devised metaheuristics search method that has the ability to discover global minima and maxima. However, due to its weak exploitation capacity, the basic HHO algorithm’s local search is pretty slow and has a slow rate of convergence. Thus, to boost the exploitation phase of HHO, a new approach, random exploratory search centered Harris hawk’s optimizer (hHHO-ES), has been developed in the present work for optimal sizing of HES. The suggested approach is validated and compared to existing optimization approaches for a variety of well-known benchmark functions, including unimodal, multimodal, and fixed dimensions. Following this, it is used to develop HES, which will be capable of providing power to remote areas where grid supply is scarce. The objective function is formulated using net present cost (NPC) as a prime function under a set of constraints such as bounds of system components and reliability. The obtained results are compared with those from harmony search (HS) and particle swarm optimization (PSO) and found to be better.

Impact analysis of COVID-19 pandemic on the future green power sector: A case study in the Netherlands

The outbreak of the COVID-19 pandemic has brought significant changes to the power sector. This study proposes general and coherent methodological steps to explore the future impact of lockdown measures on the power sector. In a case study from the Netherlands, two lockdown levels were defined and simulated to identify the influence of the pandemic upon the sector. Moreover, four renewable scenarios were developed to represent the green transition of the Netherlands' power sector up to 2035. For this future power sector, the results show that the green transition can achieve a reduction of 65% in CO2 emissions and 20% in power sector cost. Under the implementation of a simulated lockdown level, electricity demand decreased by 6.3% under Level 1 and 11.9% under Level 2 in 2035. The influences of lockdowns on future power sectors differ with respect to scenario. In addition, Lockdown Level 1 leads to a reduction of 8–12% in emissions and a reduction of 6–8% in cost, and Lockdown Level 2 expands this reduction to 15–21% in emissions and 11–13% in cost. The findings of this exploratory study can elucidate what may happen in the future green power sector if such event arises.

Modeling &amp; Performance Scrutiny of Maximum Power Extraction Strategy in PMSG based Wind Energy Transformation System

Energy from wind is turning out to be a very promising alternative source technology in present and future power sector as it is environment-friendly and long-lasting with technological enhancements. Moreover, it occupies less space and has relative cost competitiveness. In the utility grid, the penetration of wind energy systems is expanding as the research progresses to capture greatest available wind power and operate the wind turbine (WT) with maximum possible aerodynamic efficiency. For this to accomplish a tracking controller is required to extract greatest wind power at all instants in the wide range of wind speeds. This paper presents a simple control technique for optimal power extraction from cut-in to rated wind speed range by sensing the dc-link power. It also embraces mathematical modeling of wind energy conversion system. The proposed algorithm shows excellent tracking capability under fluctuating wind conditions as revealed by power speed characteristic obtained in a wind energy system. The effectiveness of proposed strategy is verified by Matlab simulation

Understanding Technology, Fuel, Market and Policy Drivers for New York State's Power Sector Transformation.

A thorough understanding of the drivers that affect the emission levels from electricity generation, support sound design and the implementation of further emission reduction goals are presented here. For instance, New York State has already committed a transition to 100% clean energy by 2040. This paper identifies the relationships among driving factors and the changes in emissions levels between 1990 and 2050 using the logarithmic mean divisia index analysis. The analysis relies on historical data and outputs from techno-economic-energy system modeling to elude future power sector pathways. Three scenarios, including a business-as-usual scenario and two policy scenarios, explore the changes in utility structure, efficiency, fuel type, generation, and emission factors, considering the non-fossil-based technology options and air regulations. We present retrospective and prospective analysis of carbon dioxide, sulfur dioxide, nitrogen oxide emissions for the New York State’s power sector. Based on our findings, although the intensity varies by period and emission type, in aggregate, fossil fuel mix change can be defined as the main contributor to reduce emissions. Electricity generation level variations and technical efficiency have relatively smaller impacts. We also observe that increased emissions due to nuclear phase-out will be avoided by the onshore and offshore wind with a lower fraction met by solar until 2050.

India\u2019s potential for integrating solar and on- and offshore wind power into its energy system

This paper considers options for a future Indian power economy in which renewables, wind and solar, could meet 80% of anticipated 2040 power demand supplanting the country’s current reliance on coal. Using a cost optimization model, here we show that renewables could provide a source of power cheaper or at least competitive with what could be supplied using fossil-based alternatives. The ancillary advantage would be a significant reduction in India’s future power sector related emissions of CO2. Using a model in which prices for wind turbines and solar PV systems are assumed to continue their current decreasing trend, we conclude that an investment in renewables at a level consistent with meeting 80% of projected 2040 power demand could result in a reduction of 85% in emissions of CO2 relative to what might be expected if the power sector were to continue its current coal dominated trajectory.

The implications of coal consumption in the power sector for China’s CO2 peaking target

After a three-year trend of flat or slightly decreasing CO2 emissions in China, carbon emissions rose again in 2017. This was mainly driven by the construction of additional coal power plants, resulting in large uncertainties regarding China’s future emission trajectories. This paper focuses on the uncertainties, including potential carbon ‘lock-in’ effects, for the Chinese power sector regarding the development of future coal power plants. This is accomplished through the development and application of a technology-rich bottom-up energy system model. Several scenarios were constructed to investigate the impacts of different future power sector pathways on China’s peak CO2 target. The results show that peaks occur at three different times based on different conditions: (1) If more coal power plants are added in the 13th (2016–2020) and 14th (2021–2025) five-year plan periods, it is likely that China will reach peak CO2 emissions around 2025–2035, (2) if coal power plants operate at higher utilization rates, the emission peak is more likely to occur later, between 2030 and 2035, and (3) if renewables are given more priority in the grid and operate at higher utilization rates, it is likely that China will reach peak emissions between 2025 and 2030. Moreover, if more stringent controls on coal capacity are implemented after 2020 and the rate of utilization of renewable power plants improves considerably, it is likely that the peak will occur earlier (between 2020 and 2025). Based on our results, we suggest that governments should integrate plans for investments in coal power plants into long-term emissions mitigation strategies and implement regulations to optimize their country’s power generation structure.

Benefits, Challenges, and Analytical Approaches to Scaling Up Renewables Through Regional Planning and Coordination of Power Systems in Africa

In light of the urgent need and ambition of African communities to scale up the deployment of renewable energy, this article explores the benefits and challenges presented by regional coordination in Africa, and how recent planning studies are reflecting those aspects in their analysis of future power sector expansion on the continent. Regional approaches to renewable deployment in Africa can reduce overall system costs and improve operation by expanding access to higher quality renewable resources, while unlocking a greater diversity of renewable options. Regional approaches can also provide greater flexibility and stability to national power systems, as well as complementarity that allows countries to scale up development of single sources while still reducing risks related to climate variability and future change. Based on a long history of experience, the benefits of regional approaches to power sector development and operation are now well established. New methodologies using more granular geospatial and temporal data have emerged to make the analysis of these benefits more feasible and more detailed. Novel additions to planning studies are also presenting more nuanced insights into the implications that climate change, technological innovations, and socio-political influences could have on regional renewable energy deployment.

Impacts of Renewable Energy Quota System on China's Future Power Sector

As the biggest carbon emitting sector which produces 44% of current national carbon emission in China, the coal-dominated power sector has a tremendous potential for CO2 mitigation in the next two decades. Renewable energy quota system is currently discussed as a potential future policy instrument for the power sector, which requires certain fraction of renewable energy in total power generation for each province and grid zone. The quantitative studies on renewable energy quota for China are still very limited. Based on a least-cost and technology-rich power generation and transmission expansion model for China, this study examines the impacts of renewable energy quota system and carbon cap policy instruments on the future Chinese power sector. Various scenarios are examined toward 2030 and their future power generation mix, capacity installations and carbon emission are discussed. This study concludes that while the renewable quota alone would be drive significant increase of renewable generation in the long term, with slightly increase of system cost compared with carbon cap policy.