Assessing the Regional Redistributive Effect of Renewable Power Production Through a Spot Market Algorithm Simulator: The Case of Italy

2021 ◽  
Author(s):  
Silvia Concettini ◽  
Anna Créti ◽  
Stanislao Gualdi
Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3259 ◽  
Author(s):  
Carlos Miguel ◽  
Adélio Mendes ◽  
Luís Madeira

Energy policies established in 2005 have made Portugal one of the top renewable power producers in Europe, in relative terms. Indeed, the country energy dependence decreased since 2005, although remaining above EU-19 and EU-28 countries in 2015 (77.4% vs. 62.4% vs. 54.0%, respectively). Data collected from governmental, statistical, and companies’ reports and research articles shows that renewables and natural gas assumed a growing importance in the Portuguese energy mix along time, while oil followed an opposite trend. Recently, the country remarkably achieved a full 70-h period in which the mainland power consumed relied exclusively on renewable electricity and has several moments where power production exceeds demand. Currently, the main option for storing those surpluses relies on pumped hydro storage plants or exportation, while other storage alternatives, like Power-to-Gas (PtG), are not under deep debate, eventually due to a lack of information and awareness. Hence, this work aims to provide an overview of the Portuguese energy sector in the 2005–2015 decade, highlighting the country’s effort towards renewable energy deployment that, together with geographic advantages, upholds PtG as a promising alternative for storing the country’s renewable electricity surpluses.


Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3459 ◽  
Author(s):  
Xianxun Wang ◽  
Lihua Chen ◽  
Qijuan Chen ◽  
Yadong Mei ◽  
Hao Wang

Small hydropower (SHP) and pumped hydropower storage (PHS) are ideal members of power systems with regard to integrating intermittent power production from wind and PV facilities in modern power systems using the high penetration of renewable energy. Due to the limited capacity of SHP and the geographic restrictions of PHS, these power sources have not been adequately utilized in multi-energy integration. On the one hand, rapidly increasing wind/PV power is mostly situated in remote areas (i.e., mountain and rural areas) and is delivered to core areas (i.e., manufacturing bases and cities) for environmental protection and economic profit. On the other hand, SHP is commonly dispersed in remote areas and PHS is usually located in core areas. This paper proposes a strategy to take advantage of the distribution and regulation features of these renewable energy sources by presenting two models, which includes a remote power system model to explore the potential of SHP to smooth the short-term fluctuations in wind and PV power by minimizing output fluctuations as well as a core power system model to employ PHS to shift the surplus power to the peak period by maximizing the income from selling regenerated power and minimizing output fluctuations. In the proposed first model, the cooperative regulation not only dispatches SHP with a reciprocal output shape to the wind/PV output to smooth the fluctuations but also operates the reservoir with the scheduled total power production by adjusting its output in parallel. The results of a case study based on a municipal power system in Southwestern China show that, with the proposed method, SHP can successfully smooth the short-term fluctuations in wind and PV power without influencing the daily total power production. Additionally, SHP can replace the thermal power production with renewable power production, smooth the thermal output, and further reduce the operation costs of thermal power. By storing the surplus power in the upper reservoir and regenerating the power during the peak period, PHS can obtain not only the economic benefit of selling the power at high prices but also the environmental benefit of replacing non-renewable power with renewable power. This study provides a feasible approach to explore the potential of SHP and PHS in multi-energy integration applications.


Author(s):  
S. Richards ◽  
H. Perez-Blanco

Renewable power production is both variable and difficult to forecast accurately. These facts can make its integration into an electric grid problematic. If an area’s demand for electricity can be met without using renewable generation, the addition of renewable generation would not warrant a further increase in generation capacity. However, to effectively integrate large amounts of additional renewable generation, it is likely that a more flexible generation fleet will be required. One way of increasing a generation fleet’s flexibility is through the adoption of pumped hydroelectric storage (PHS, see the glossary for definitions of select terms). Like traditional hydropower generation, PHS is capable of quickly varying its power output but it is also capable of operating in reverse to store excess energy for later use. This paper will address many of the operational aspects of combining pumped hydroelectric storage (PHS), which is currently used to store excess energy from traditional generators, with wind and solar power generation. PJM, a grid operator in the Middle Atlantic States, defines capacity value for renewable generation as the percent of installed generating capacity that the generator can reliably contribute during summer peak hours. Existing wind generators inside PJM have an average capacity value of 13% and existing solar generators have a capacity value of 38%. The chief reason for these capacity values is that the renewable power production does not usually coincide with the hours of peak electricity demand during the summer. If PHS were used to firm renewable power generation, it would translate into increased utilization of the renewable generation that would displace the least efficient/most costly generators. A computer model with one minute granularity is constructed in order to study the operational requirements of PHS facilities. PJM electricity demand, power prices, and wind power production data for 2010 were used in conjunction with NREL simulated solar power production as input to the model. Currently, various PHS operational strategies are being tested to ascertain their effectiveness at firming and time shifting renewable generation. Preliminary results show the profound effects of increased penetration of renewable energy on an electric grid. The results also demonstrate a niche for even greater PHS operational flexibility, i.e. variable speed or unidirectional ternary machine (UTM) PHS.


2021 ◽  
Author(s):  
Marianne Zeyringer ◽  
Natalia Sirotko-Sibirskaya ◽  
Fred Espen Benth

<p>The integration of renewable energy sources into the power grid is of the utmost importance for achieving the goal of zero carbon emission. Although there are feasibility studies showing that renewable energy might be able to cover 2050 global energy demand using less than 1 % of the world's land for footprint and spacing, see Jacobson and Delucchi (2011), nowadays renewable energy production is known to be highly intermittent due to substantial uncertainties in the weather conditions. One possibility to reduce such uncertainty (besides storage and employing hydrogen technologies) is spatiotemporally diversified allocation of renewable power capacities which (alongside with the transmission infrastructure) should guarantee that the power demand is met at any given time with a certain (high) probability. We treat the question of spatiotemporal diversification of renewable capacities as a Markowitz portfolio problem with the difference that instead of n = 1, …, N stocks we have geographical locations each with a certain expected level of renewable power production (instead of expected returns for stocks) and the corresponding variance. Another difference to a classical Markowitz portfolio problem is that we require additionally that at each given time point t = 1, …, T, we can reach a predetermined level of renewable power production with a certain probability, i. e. we solve so called chance-constrained problem. Finally, instead of solving one-step problem as it is the case with a Markowitz portfolio we reformulate our problem in the optimal control framework in continuous time and solve it with a reinforcement learning algorithm as suggested in Lillicrap et al. (2019). The advantage of this approach is that the optimal capacities (control) are updated continuously as a response to changing weather conditions (state). We exemplify our approach with the data from ERA5 data, see Hersbach et al. (2020), and suggest possible allocation of renewable energy sources across the European Union.</p>


2018 ◽  
Vol 140 (06) ◽  
pp. 30-35 ◽  
Author(s):  
John Kosowatz

Maintaining grid stability is a challenge as utilities rush to add renewable power to their generating portfolio. The business case for renewables is undeniable: as prices for wind turbines and solar panels keep dropping and the costs of installation go down, renewable electricity becomes some of the cheapest power available. But the inherently inconsistent nature of solar and wind energy has grid operators looking for new ways to seamlessly integrate their output into the system. This challenge is being faced around the world, and in the U.S. it is playing out initially in California.This article takes a closer look at the steps California is taking to smooth out the duck curve, a graph of power production over the course of a day that shows the timing imbalance between peak demand and renewable energy production.


2020 ◽  
Vol 24 (1) ◽  
pp. 472-482
Author(s):  
Gunars Valdmanis ◽  
Gatis Bazbauers

AbstractThe study looks for a correlation between the share of wind power and electricity wholesale prices in the selected regions of the Nordic Baltic power market “Nord Pool Spot”. The aim is to see if and how strong an impact of wind power production has on power market prices. This information would help to perform long-term energy system analysis considering growing wind energy penetration. The actual hourly wind production and power consumption data as well as electricity prices from the year 2019 were used in the analysis. Results of the study revealed that in the analysed dataset there is no correlation between the share of wind power and the power prices, i.e. R-squared value is 0.003 for the Baltic region and 0.0064 for both trading areas of Denmark. In contrast, the R-squared value was almost 0.6 for a positive correlation between power demand and prices. The results mean that expected loss of interest to invest due to falling power prices, as a share of renewable power increases, should be examined more carefully and may not fulfil forecasts of policy makers and industry experts.


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