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Variable power outputs are one of the largest challenges facing the widespread adoption of renewable energy systems. The inherent variability of solar resources makes it challenging to integrate large amounts of solar energy into the electric grid. However, the weather factors that influence solar production are often local in nature. In this study, eleven solar photovoltaic systems with publicly available historical data were identified for analysis. The systems are located within a circle with a diameter of approximately 130 km. The historical power output data for each system were acquired, and quality control measures were applied. A comparison is made between the variability of the time-varying power output from individual systems compared to the variability of the aggregated output of the eleven systems combined. Next, the effect of increasing the geographical spread of the aggregated systems is investigated. This is done by comparing the variability of the aggregated time-varying power output from closely-spaced systems against the variability of the aggregated time-varying power output from systems spread out over a large geographical area. Next, the correlations between the outputs from each of the individual systems are explored. The data show that the correlation decreases by approximately 0.1 for each 80 km of separation distance. Finally, the historical solar output data is used to define the “expected output”, and the deviation from this expected output is compared for individual systems and various sets of aggregated systems. The four aggregated systems located far apart are 31% more likely to have a combined output that is close to their expected output, defined as having a normalized power output deviation less than or equal to 0.2 kW/kW. Furthermore, the four aggregated systems located far apart are 54% less likely to have a combined output that is significantly different from their expected output, defined as having a normalized power output deviation greater than or equal to 0.4 kW/kW.

Renewable energy sources (RESs) such as wind and solar are frequently hit by fluctuations due to, for example, insufficient wind or sunshine. Energy storage technologies (ESTs) mitigate the problem by storing excess energy generated and then making it accessible on demand. While there are various EST studies, the literature remains isolated and dated. The comparison of the characteristics of ESTs and their potential applications is also short. This paper fills this gap. Using selected criteria, it identifies key ESTs and provides an updated review of the literature on ESTs and their application potential to the renewable energy sector. The critical review shows a high potential application for Li-ion batteries and most fit to mitigate the fluctuation of RESs in utility grid integration sector. However, for Li-ion batteries to be fully adopted in the RESs utility grid integration, their cost needs to be reduced.

As a research result, characteristic indicators of the efficiency of using various heat sources in combined heat supply systems were determined. During the study, various schemes for integrating heat accumulators in heat supply systems were considered. Water was used as a battery, which also acts as a coolant. Mathematical modeling of processes in combined heat supply systems using intermittent heating is carried out. The characteristic operating modes of the elements of heat supply systems that take into account the operating modes of heat consumers are determined. Mathematical modeling was carried out using a software package that allows to obtain the distribution of heat power of the heat supply system by its main elements and its characteristic operation modes. According to the research results, a coefficient of thermal power reduction and a coefficient of efficiency of using the heat accumulator volume were proposed. These coefficients allow to evaluate the efficiency of heat sources and the efficiency of using the volume of the heat storage tank. Based on the obtained data, the task was set to optimize the daily load of the heat source, taking into account the installation of the storage tank. The research results can be used for the reconstruction of heat supply systems of buildings with a two-period operation mode (operation duty) using both traditional and renewable heat sources. This will significantly increase the efficiency of the use of elements of the heat supply system, even out the daily heat generation schedule and increase the service life of the main equipment

An economic and environmental evaluation of active distribution networks containing lithium ion batteries (Li-ion), sodium sulfur batteries (NaS) and vanadium redox flow batteries (VRB) was carried out using the EnergyPLAN software. The prioritization schemes of the combination of energy storage systems and intermittent energy systems were studied technically and economically based on some specific situations of the grid integrated with wind power. The results suggest that the technical and economic optimal intermittent energy-storage capacity ratio was 2:1 in predetermined energy system scenarios. Li-ion batteries storage system performed the best in critical excess electricity production (CEEP) absorption, energy saving and emission reduction while NaS batteries storage system was the most competitive among the three due to its cheaper costs.

Planning electricity supply is important because power demand continues to increase while there is a concomitant desire to increase reliance on renewable sources. Extant research pays particular attention to highly variable, low-carbon energy sources such as wind and small-scale hydroelectric power. Models generally employ only a simple load levelling technique, ensuring that generation meets demand in every period. The current research considers the power transmission system as well as load levelling. A network model is developed to simulate the integration of highly variable non-dispatchable power into an electrical grid that relies on traditional generation sources, while remaining within the network’s operating constraints. The model minimizes a quadratic cost function over two periods of 336 hours, with periods representing low (summer) and high (winter) demand, subject to various linear constraints. The model is numerically solved using Matlab and GAMS software environments. Results indicate that, even for a grid heavily dependent on hydroelectricity, the addition of wind power can create difficulties, with system costs increasing with wind penetration, sometimes significantly.

The impact of both climate change and climate variability on the supply of intermittent renewable energy sources (I-RES) in Europe are assessed based on global climate model simulations. The main driver of climate variability over Europe is the North Atlantic Oscillation (NAO) in winter and its equivalent in summer (sNAO) which determine to a large extent the atmospheric circulation in Europe. Four climate scenarios are constructed distinguished by a moderate and strong increase of the average global surface temperature, and a positive and negative phase of the atmospheric variability over the North Atlantic and Europe. This spans a framework which combines the effects of both climate change and climate variability. Using a 2050 distribution of PV panels and wind turbines, we found that although climate change is likely to have significant impact on future I-RES output in Europe, its effects, especially for wind power, are outweighed by the high and strongly variable impact of the NAO/sNAO phases. Variability in the large-scale atmospheric circulation is able to induce median I-RES yield differences of 20–30% for high wind potential regions. Due to the NAO variability also months were identified with persistent calm conditions over Europe linked to the inflow of frigid arctic air resulting in some regions in a decrease in wind power of up to 75%a accompanied with an increase in heating degree days of up to 30%. The results of the study imply that if requirements for the power system including back up capacity take into account the weather variability, the power system can also cope with the climate change impacts.

Abstract The integration of electrical and heating systems has great potential to enhance the flexibility of power systems to accommodate more renewable power such as the wind and solar. This study was to investigate an optimal way to integrate the energy of both systems in urban areas. The amount of energy conversion between the electrical system and heating system was optimally decided so that the demand within both systems could be met at the least operational cost. Besides, the best node to join with the electrical system and heating system was chosen by consideration of the energy transmission loss. The mathematical formulation of the optimization problem was detailed as a large-scale non-linear program (LSNLP) in this paper. A decomposition–coordination algorithm was proposed to solve this LSNLP. At last, a 6-bus electrical power system with 31-node heating transmission system was studied to demonstrate the effectiveness of the proposed solution. The results showed that coordinated optimization of the energy distribution have significant benefits for reducing wind curtailment, operation cost, and energy losses. The proposed model and methodology could help system operators with decision support in the emerging integrated energy systems.

In order to cut greenhouse-gas emissions and increase energy security, the European Commission stimulates the deployment of intermittent renewable energy sources (IRES) towards 2050. In an electricity system with high shares of IRES implemented in the network, energy balancing like storage is needed to secure grid stability and smooth demand satisfaction. Pumped hydro storage (PHS) is at this moment the best option for large scale storage. Switzerland has strong ambitions to further develop their PHS sector and become the battery of Europe. In this research, the potential of the Swiss PSH plants is explored, whilst taking inflow into the upper reservoirs of the PHS plants into consideration. To simulate electricity imbalance, Germany is used as a case study. Germany already has a high penetration of IRES and has plans to increase installed IRES capacity. By using an energy planning model (PowerPlan), three future scenarios of the German electricity system were designed, each with a different set of IRES installed (solar, mixed and wind). Results show that the Swiss battery ambition offers most benefits to a wind-oriented scenario, reducing both shortages as well as surpluses. Water inflow in Swiss PHS-reservoirs is of minor importance when looking at security of supply, although it was shown that the solar-scenario profits more from inflow in terms of system stability. However, a potential conflict was observed in the solar-scenario between the need for electricity storage and the storage of natural inflow, resulting in more surpluses in the system when inflow was taken into account.

Abstract This paper applies double-uncertainty optimization theory to the operation of AC/DC hybrid microgrids to deal with uncertainties caused by a high proportion of intermittent energy sources. A fuzzy stochastic expectation economic model for day-ahead scheduling based on uncertain optimization theory is proposed to minimize the operational costs of hybrid AC/DC microgrids. The fuzzy stochastic alternating direction multiplier method is proposed to solve the double-uncertainty optimization problem. A real-time intra-day unbalanced power adjustment model is established to minimize real-time adjustment costs. Through comparative analysis of deterministic optimization, stochastic optimization and fuzzy stochastic optimization of day-ahead scheduling and real-time adjustment, the validity of fuzzy stochastic optimization based on a fuzzy stochastic expectation model is proved.