Spatial optimization of solar PV and wind power capacity in Finland and correlation analysis

There is an imminent electricity demand/supply crisis in Nigeria. Many citizens of the country only have access to few hours of electricity daily. However, the renewable energy (RE) and fossil fuel resources in this country is enormous but these are underutilized for electricity generation. In this study, the used of solar PV and wind power plants to solve Nigeria electricity problem will be investigated. The aim of this research is to determine the maximum penetrable capacity of solar PV and wind power with/without critical excess electricity production (CEEP). The simultaneous integration of solar PV and wind power into the electricity network from the generation side is also considered. From the analysis, solar PV and wind power maximum integration into the current electricity system without CEEP are 12,000MW and 11,000 MW respectively. Economic analysis results indicate that integration solar PV is slightly cheaper compared to the use of onshore wind power plant.

Abstract. With an increased share of solar and wind energy e.g. in the German and European energy systems it is becoming increasingly important to analyze the impact of weather variability on the reliability of the energy production. In this study, we calculate solar PV and wind power capacity factors using two recently developed climatological datasets that provide information with high spatial and temporal details on the continental (European) scale and are of sufficient length for assessments at climatological time scales: Surface radiation derived from meteorological satellites (SARAH-2) and wind speed from a high-resolution regional reanalysis (COSMO-REA6). Balancing effects are analysed: On average, the seasonal cycles of PV and wind power production complement each other in Germany as well as in Europe. The frequency of events with a risk of low electricity generation is analyzed under different assumptions. When using wind energy over German land areas as a reference case, the results illustrate that the number of low production events is reduced when Germany's Exclusive Economic Zone is included into the analysis, or when a combined system of PV and wind energy is considered. A European-wide analysis also leads to a distinct reduction of such events.

Given the intensifying debates on whether governments should promote particular renewable energy technologies, the main objective of this study is to investigate the long- and short-run effects of policy-induced expansion of renewable solar and wind technologies on economic growth and employment in 15 European Union (EU) member states during 1990-2013 by using panel-data time-series econometric techniques. Instead of relying on renewable energy consumption or generation as commonly done in the literature, we focus on the capacity for solar and wind power generation, which is largely a consequence of the EU’s renewable energy policies. In summary, we find that, to date, renewable energy policy- induced wind and solar power capacity promotes growth and/or employment in the short run, but these capacity increases do not stimulate economic growth in the long run in the EU-15 region. In fact, our results tend to support the opposite relationship: increases in wind and solar power capacity are associated with negative economic growth, at least at the total economy level.

Renewable power, especially wind and solar integration to the power grid is gaining more attention nowadays. However, the contribution of wind and solar generators to the power system reliability is significantly low due to the diurnal and seasonal variations and intermittency of solar irradiance and wind speed. Capacity credit provides an idea of actual solar PV or wind capacity contribution to the power system reliability. In this paper, the non-sequential Monte Carlo simulation is used to obtain reliability curves to evaluate the capacity credit of solar PV and wind power facilities situated in Sri Lanka (SL). Moreover, SL capacity values are compared with capacity values of wind and solar generation in Brussels, Belgium which has a temperate maritime climate. The impact of power system reliability level and seasonal renewable power variations on capacity credit values are explored using several case studies. Results show that for SL, the wind capacity value significantly varies with seasons whereas the solar PV capacity value remains the same throughout the year.

To mitigate and adapt to the ongoing climate change, the decarbonization of the economy requires a radical change in our energy production and consumption patterns. A robust finding of existing studies is that renewable energy sources - and more specifically wind and solar power generation - are expected to represent a major share of the power mix in the future. Due to their higher dependency on meteorological variable a better understanding of the variability of VRE outputs across different temporal and geographical scales thus becomes critical. Of particular interest is the study of tight grid conditions with periods of coincidence between low wind and solar output because they will condition flexibility requirements. Our work addresses these research questions based on an analysis of the variability of solar PV and wind power generation capacity factors provided by the Copernicus service C3S energy. The Copernicus C3S energy service deals with the transformation of climate variables (reanalysis, seasonal forecast and climate projection) into energy variables (wind, PV, hydro and energy demand principally). To take into consideration the dependance between the solar and wind resource the combined variability has been evaluated for different wind to PV share. In addition, the coupling of different kind of storage technologies has been anticipated by evaluating the variability on different time scales ranging from hour to month. Finally, focusing on extreme conditions, the results of the variability analysis was synthesized in a couple of boundary conditions that capture the impact of the meteorological variability on estimated joint wind and solar power output. The added value of the proposed methodology will be illustrated for a simple case in France.

Renewable energy is perceived as a primary ingredient in the world’s transition to a green, clean, low-carbon sustainable economy from a brown, dirty, high carbon unsustainable one. The global renewable energy installed capacity, especially for wind and solar, has increased rapidly in the last decade as countries have adopted laws and policies to mitigate climate change and air pollution, as well as improve energy security. As the sector matures the focus on renewable energy needs to turn to consider system infrastructure design to ensure that the take-make-dispose rationale that contributed to the unsustainable fossil fuel economy is not perpetuated under the guise of a green low-carbon economy. The EU is a leader in installed solar PV and wind energy capacity. It also has a well-established waste management legal framework that is based on hierarchy and producer responsibility principles. This chapter considers how the EU is responding to the future challenges that waste management from end of life cycle solar PV panels and wind turbines poses. It questions whether steps taken to date are in line with the more advanced agenda laid out in the EU’s Circular Economy Action Plan (2015) which calls for a paradigm shift in developing law and policy that pursues holistic sustainability goals in relation to resource management throughout the value-supply chain.

Both solar energy and wind energy are promising renewable sources to meet the world's problem of energy shortage in the near future. In this paper, we identify the complementary relation between solar power and wind power at certain locations of Hong Kong, and aim at studying the hybrid renewable energy investment in the microgrid. We jointly consider the investment and operation problem, and present a two-period stochastic programming model from the microgrid operator's perspective. In the first period, the operator makes optimal investment decisions on solar and wind power capacities. In the second period, the operator coordinates the power supply and demand in the microgrid to minimize the social operational cost. We design a decentralized algorithm for computing the optimal pricing and power consumption in the second period, and based on this solve the optimal investment problem in the first period. With realistic meteorological data obtained from Hong Kong observatory, we numerically demonstrate that the demand response saves 18% of the capital investment, and hybrid renewable energy investment reduces the generation capacity by up to 6.3% compared to a single renewable energy investment.

SummaryTo reduce greenhouse gas emissions, many countries plan to massively expand wind power and solar photovoltaic capacities. These variable renewable energy sources require additional flexibility in the power sector. Both geographical balancing enabled by interconnection and electricity storage can provide such flexibility. In a 100% renewable energy scenario of 12 central European countries, we investigate how geographical balancing between countries reduces the need for electricity storage. Our principal contribution is to separate and quantify the different factors at play. Applying a capacity expansion model and a factorization method, we disentangle the effect of interconnection on optimal storage capacities through distinct factors: differences in countries’ solar PV and wind power availability patterns, load profiles, as well as hydropower and bioenergy capacity portfolios. Results indicate that interconnection reduces storage needs by around 30% in contrast to a scenario without interconnection. Differences in wind power profiles between countries explain around 80% of that effect.

The Spanish energy roadmap aims at producing around 80% of electricity from renewable energy by 2030, while reducing nuclear energy in a scenario of increasing demand. To this end, the target for installed capacity is 50 GW for wind energy (30 GW in 2022), 39 GW for solar PV (20 GW in 2022) and 2.5 GW for battery storage. Plans underway suggest even more ambitious goals.We present the results of an analysis of the optimal spatial distribution of new wind and solar capacities in Spain. The study is carried out using the electrical system model PyPSA-Eur, which allows analyzing the optimal allocation and sizing of new renewable plants, taking into account the variability of generation and demand, energy costs, integration and the transmission issues. Two main scenarios are explored: 1) capital costs and 2) operational nuclear power amount (0/3/7 GW). The study assumes a 20% increase of demand by 2030 and a maximum total installed power of 160 GW. The generation and distribution networks used in PyPSA-Eur includes 9 nodes, homogeneously distributed in the study region. The model is fed with the Spanish High Resolution Renewable Energy and Demand (SHIRENDA) open access database for energy system analyses. Both combined the generation and distribution networks  and SHIRENDA allow adequately accounting for the very high spatial variability of the renewable resources in Spain. The results show that the new capacities should be installed in up to four of the nine regions (nodes) considered, although this strongly depends on the amount of nuclear energy. In particular, for scenarios with low nuclear power (0/3 GW) wind capacities should be installed mainly in the Galicia (northwest of the study area) and Aragón (northeast) regions, and solar PV in the regions of Murcia (southeast) and Aragón. For scenarios with fully operational nuclear energy (7 GW), the region of Andalusia (south) was also selected both for wind and solar PV. The intermediate nuclear power amount scenario (3 GW) is best from the costs standpoint. The curtailment is high (about 10%),  higher for wind, but reduces by 50% when nuclear energy is removed.Overall, the results show that a homogeneous spatial distribution of new solar and wind capacities in the study region is far from optimal and that a better representation of the spatio-temporal variability of the renewable energy resources, as done in this study, is needed. Future work will explore the optimal ratio between solar PV and wind capacity, as well as the role of energy storage and demand management.

Renewable energy curtailment has become a severe problem in some regional power networks of China. To alleviate the curtailment, optimizing the integrated wind and solar power capacities becomes an urgent need. This paper proposes an improved method to optimize the wind and solar power capacity based on the time sequence simulation technology. An optimization model is proposed to maximize the environmental benefit for a regional power network with considering the constraints of system power balance, thermal unit peak load regulation ability, system spinning reserve, power and heating coupling of the co-generation unit and tie-line transmission capacity. To handle the transmission capacity constraint, the regional power network is aggregated for simplicity. The annual wind and solar power time sequences are incorporated as inputs for optimization. By giving a series of scenarios with different proportion of wind and solar energy, the optimal capacities are obtained by comparing the environmental benefit and the curtailment. Case studies are conducted with a provincial power network of China and testing results verify the effectiveness of the proposed method.

The 2060 carbon neutrality goal announced by President Xi in 2020 sets the tone for the long-term Chinese climate policy. China has made considerable achievements in greening its energy mix in the past decade; solar power and wind power capacity both ranked top as of 2019. The current number of electric vehicles are, moreover, close to half of the total number of EVs in the world. However, there are conflicting signals from the coal power development plan and the increasing dependence on natural gas. There are many questions like these to be answered in a more reasonable and independent way. Discussion of China’s energy transition will start with the energy mix and energy governance structure, supplemented by the interaction of energy transition with climate change and air pollution issues. In particular, the institutional setting for national energy and climate policy will be discussed in this chapter, followed by inclusion of key elements that impact the interaction between energy democracy and energy transition process. Civil society organizations and industrial associations have been playing an important role in achieving a decentralized renewable energy system and accordingly promoting energy democracy. Special focus will be placed on the renewable energy corporates’ involvement in the transition.

With the current global energy crisis renewable energy integration is expected to grow drastically in the near future. However, integrating high amount of renewables to the grid is subjected to various operational challenges. One solution for this challenge is looking for complementing intermittent renewable resources. In this paper solar PV and wind power complementarity analysis was carried out over the three topographic regions of Eritrea based on monthly satellite-based power generation data. Three different approaches (Pearson correlation coefficient, graphical and dimensionless index) were employed to investigate the complementarity of PV and wind power in the chosen sites. The analysis results showed that the southern coastal and central highlands sites have low complementarity behaviour. The solar PV and wind power synergy was however, found to be the maximum in the northern highlands and western lowlands sites of the country. It is interesting to find out that the high wind potential sites in southern coastal region are positively correlated to solar availability with peaks in winter and low in summer with no complementarity pattern.

This study presents a technoeconomic analysis of a hybrid wind‐PV (photovoltaic) power plant (HPP) compared to onshore wind power plants (WPPs) and photovoltaic power plants (PVPPs) in the Nordic electricity market, focusing on locations in Finland and Sweden. Wind power capacity has recently increased significantly in the Nordics, increasing the profit cannibalization of wind power. Renewable energy subsidies have been phased out in Finland and Sweden, thus new wind and PV power value creation is formed from the power market. The PV power capacity has also encountered significant growth in the Nordics. However, the capacity is still relatively low, allowing more revenue for produced PV power compared to wind power. The lower PV power profit cannibalization has increased interest in HPPs instead of WPPs. This contribution studies the economic feasibility of wind and PV power in changing market conditions in the Nordic electricity market. The market operation is modeled with three different configurations including selling all the power into the day ahead spot market and baseload or pay‐as‐produced power purchase agreement (PPA). In addition, a battery energy storage system (BESS) investment is analyzed using the operating strategy of shifting production to more profitable spot price hours. This study shows that due to the profit cannibalization and high cost of capital, the power plants are currently not profitable in the Nordic electricity market except when the bidding area has high average spot prices. The worst profitability was with WPPs when exposed to the market shape risk and with PVPPs when pay‐as‐produced PPA was agreed upon due to the higher levelized cost of electricity. However, the PV power profit cannibalization is expected to increase in the future as more PVPPs operate in the Nordic power market. Thus, the PVPP shape risk may increase in the future as well.

Due to the outputs of wind power and solar power have natural complementarity in time and space, and the combined power of wind and solar can reduce the random, intermittent and volatility of the output, so the establishment of their joint distribution function can improve the level of evaluation of the combined power of wind and solar. Therefore, based on the sequential output data of wind/solar power in jibei grid, this article gets the cumulative distribution function of wind/solar power by kernel density estimation, and structures the two binary joint distribution function by Copula connect function. In view of the new energy accessing area which is constrained by transmission channel, based on the above joint distribution function, this article rational deploys the capacity of wind power and solar power in order to coordinate improve the curtailment of new energy power and the utilization of transmission channel. The example analysis confirmed that the method of calculating optimal proportion of wind and solar capacity is simple and feasible, which can be practically used in the situation of the new energy power curtailment of our country.

This chapter analyses how China and the UK have implemented policies transitioning away from fossil fuels to renewable energy. The UK pioneered renewable energy incentives and various government policy instruments have been applied, including direct subsidies, green certificates and feed-in-tariffs. The country now looks to move away from government incentives towards greater corporate involvement. Policies have also been introduced in transportation and other sectors, to decarbonise the economy by 2050. China represents an example of a government-led, top-down approach to energy transitioning building the world's largest installed capacity of hydropower, solar PV and wind power. In other sectors such as e-mobility, decarbonisation policies and initiatives by local and central government are driving a shift in favour of the use of electric vehicles.