Available Renewable Energy Sources Research Articles

Optimal integration of renewable energy sources for autonomous tri-generation combined cooling, heating and power system based on evolutionary particle swarm optimization algorithm

Renewable energy (RE) sources can be integrated to serve autonomous tri-generation combined cooling, heating and power (CCHP) systems, so that the advantages of zero environmental emissions as well as higher energy efficiencies in generation and consumption are realized simultaneously. However, to override the inherent intermittent availability of RE sources and to enhance the performance of RE-CCHP systems, it is necessary to include thermal and electrical storage mechanisms. The objective of this study is to develop a simulation model for optimization of different configuration alternatives of autonomous RE-CCHP system for meeting cooling, heating and electrical loads, based on photovoltaic-thermal (PVT) panel, wind turbine (WT), thermal energy storage (TES), electrical energy storage (EES), absorption chiller (CHABS), electric chiller (CHELEC) and electric heater (EH). For operation of autonomous RE-CCHP system, two operational strategies, namely, following electric load (FEL) and following thermal load (FTL), are used. For optimization, a newly developed evolutionary particle swarm optimization (E-PSO) algorithm is examined and validated. It is demonstrated that the most cost effective configuration alternative of the autonomous RE-CCHP system is PVT+WT+EES+TES+CHABS+EH operating based on FTL operational strategy, where utilization of CHELEC is not needed.

Decentral Control Strategies for Demand-side Management by Industrial Heating and Cooling Devices with Discontinuous Operation Mode

In future energy systems with a high share of fluctuating energy sources like wind and solar power, keeping the balance between power generation and consumption will be a challenge. In this context, cost-efficient solutions for moving the electrical energy demand to times with a high availability of renewable energy sources are needed. In this paper, a decentral control approach for demand-side management by a multi-agent system of industrial supply technologies for heating and cooling with discontinuous operation mode is presented. By this approach, the devices are enabled to stabilize the power system without a central control unit, which calculates the individual operation strategy of each device. Furthermore, no process-specific internal information has to be revealed and no direct remote control of devices is required from external service providers.

Algorithmic process synthesis and optimisation for multiple time periods including waste treatment: Latest developments in p-graph studio software

Food, water and domestic energy demands changes seasonally as well as the availability of renewable energy sources. One of the challenging questions of utilizing renewable resources is its synchronization with the periodically varying demands. Only those methods can estimate the economic feasibility, which can explicitly take into account the pairing of demands with potential resources in multiple time horizons as well as the potential storage options. Moreover, waste treatment cannot be neglected in any long-term technology planning procedure. The P-graph framework provides appropriate formal and algorithmic basis for process synthesis, including structural modelling and model validation (Friedler et al., 1992), generation of alternative network structures (Friedler et al., 1995), determination of the optimal and N-best design alternatives (Friedler et al., 1996). By the help of the P-graph framework and its software implementation, i.e., the P-graph Studio developed at the University of Pannonia, process-network synthesis problems can be modelled and solved in general (Bertok et al., 2013), and optimization of multiperiod operation (Heckl et al., 2014), as well as multiperiod system design (Aviso et al., 2016) and waste treatment optimization (Friedler et al., 1994) in particular. Thanks to the built-in algorithm RCABB (Bartos et al., 2015) not just the best, but the list of N-best structurally different alternative network configurations can be generated utilizing the computational power of the computers executing. In the present work, recent additions to the software is to be introduced for multiperiod process-network synthesis including the design of waste treatment system, and computer aid for answering questions about the sensitivity of a configuration to the actual economic environment are to be shown.

Optimal Curtailment of Non-Synchronous Renewable Generation on the Island of Tenerife Considering Steady State and Transient Stability Constraints

The increasing penetration of non-synchronous, renewable energy in modern power systems displaces synchronous generation and affects transient stability. This is just one of the factors that has led to preventive curtailment of renewable energy sources in an increasing number of electrical grids. Transient stability constrained optimal power flow (OPF) techniques provide a tool to optimize the dispatch of power systems while ensuring a secure operation. This work proposes a transient stability-constrained OPF model that includes non-synchronous generation with fault ride-through capability and reactive support during voltage dips. The model is applied it to the IEEE 39 Bus benchmark test case and to the power system of the Spanish island of Tenerife, and solved using the open-source library IPOPT that implements a primal-dual interior point algorithm. The solution of the model makes it possible to optimize the dispatch of conventional plants and the curtailment of non-synchronous generation, as well as to explore methods to reduce generation cost. Fault ride-through capability, synchronous inertia and fault clearing times are identified as useful tools to reduce the curtailment of non-synchronous generation, especially during periods of low load and high availability of renewable energy sources.

Improving the Efficiency of DASC by Adding CeO2/CuO Hybrid Nanoparticles in Water

Solar energy is the abundantly available source of renewable energy with least impact on environment. Direct absorption solar collector (DASC) is the commonly used device to absorb heat directly from sun and make use of it for different heating applications. In the past, many experiments have been done to increase the efficiency of DASC using nanofluids. In this paper, an examination of solar collector efficiency for hybrid CeO2/CuO–water (0.1% by volume) nanofluid under various flow rates and proportions of CeO2/CuO nanoparticles is investigated. The experiments were conducted at flow rates spanning from 20[Formula: see text]cc/min to 100[Formula: see text]cc/min and with CeO2/CuO nanoparticles proportions of 1:0, 1:0.5, 1:1, 0.5:1 and 0:1. The efficiency increases from 16.5% to 51.6% when the flow rate is increased from 20[Formula: see text]cc/min to 100[Formula: see text]cc/min for hybrid CeO2/CuO (1:1)–water nanofluid. The results also showed an increase in efficiency of 13.8%, 18.1%, 24.3%, 24.9% and 26.1% with hybrid combination of CeO2/CuO at ratios 1:0, 1:0.5, 1:1, 0.5:1 and 0:1, respectively, in comparison with water at a flow rate of 100[Formula: see text]cc/min.

Feasibility study, design and implementation of smart polygeneration microgrid at AMU

To confront the challenges associated with the rising of carbon footprint and energy demand, the Renewable Energy Sources (RESs) based smart microgrids are becoming the viable paradigm. In this work, based on cost exploration, greenhouse gas (GHG) emission, and availability of RESs, the feasibility study, design, optimization, and implementation of institutional based smart Polygeneration microgrid is presented. To investigate the most optimal scenario, the detailed analysis of various microgrid topologies in grid connected as well as in off-grid mode with and without the storage system is carried out. The analysis outcome reveals that the solar PV system in grid connected (i.e. G+PV) mode is most preferable. But, the consideration of intermittency as well as the volatile behaviour of the solar PV system forces incorporation of a battery storage system to overcome the fluctuated voltage profile and interrupted power supply, which raises the Cost of Energy (COE), Net Present Cost (NPC), and operating cost to another extent. To obtain the more realistic results, the uncertainty of load demand, as well as RESs, is also taken into account. Further, the comparative analysis of the proposed microgrid topology with existing conventional system is also presented.The result shows that in grid-connected mode, the key cost parameter belongs to PV system (i.e. INR 20.68 million) followed by grid operating cost (i.e. INR7.28 million), battery (i.e. INR 3.11 million) and converter (i.e. INR 2.083 million). While in the off-grid mode the major part of the total system cost is covered by battery storage system (i.e. INR 74.76 million) followed by PV system (i.e. INR 27.96 million) and converter (i.e. 2.385 million). The comparative study shows total system cost associated with proposed microgrid G+PV+B (i.e. INR 33.163 million) is 31.57% of current scenario while the total system cost associated with PV+B (INR 105.036 million) is 95.41% higher than the current scenario. The recommended system mitigated 226.26-kilokg of CO2, 980.93kg of SO2, and 497.73kg of Nitrogen oxides per year.

Adaptive control paradigm for photovoltaic and solid oxide fuel cell in a grid-integrated hybrid renewable energy system.

The hybrid power system (HPS) is an emerging power generation scheme due to the plentiful availability of renewable energy sources. Renewable energy sources are characterized as highly intermittent in nature due to meteorological conditions, while the domestic load also behaves in a quite uncertain manner. In this scenario, to maintain the balance between generation and load, the development of an intelligent and adaptive control algorithm has preoccupied power engineers and researchers. This paper proposes a Hermite wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control of photovoltaic (PV) systems to extract maximum power and a Hermite wavelet incorporated NeuroFuzzy indirect adaptive control of Solid Oxide Fuel Cells (SOFC) to obtain a swift response in a grid-connected hybrid power system. A comprehensive simulation testbed for a grid-connected hybrid power system (wind turbine, PV cells, SOFC, electrolyzer, battery storage system, supercapacitor (SC), micro-turbine (MT) and domestic load) is developed in Matlab/Simulink. The robustness and superiority of the proposed indirect adaptive control paradigm are evaluated through simulation results in a grid-connected hybrid power system testbed by comparison with a conventional PI (proportional and integral) control system. The simulation results verify the effectiveness of the proposed control paradigm.

An investigation of renewable certificates policy in Swedish electricity industry using an integrated system dynamics model

Energy policy has a vital impact on the investment in renewable energy capacities and on the decommissioning of traditional ones. Currently Sweden and Norway aim to expand the renewable electricity production by 26.4TWh between 2012 and 2020, and subsequently to reduce CO2 emissions. To achieve this, the Swedish Energy Agency issues to renewable producers electricity certificates, which are sold on an open market to increase revenues. Meanwhile, the electricity is priced based on a marginal cost principle, and the price is highly reliant on the capacity profile and energy balance in the system, and consequently on the expanding and decommissioning decisions. The above price issues, together with the intermittent availability of renewable energy sources and the uncertainty of future fuel costs, will significantly affect the economic performance of the electricity producers. It is only after understanding the interaction of those factors that we can define companies’ business models for achieving a sustainable development in the electricity sector. This study applies a system dynamics approach and presents a model to integrate both strategic decisions such as capacity expansion/decommission, and operational features such as randomness and seasonal factors in electricity production. The model highlights the complex and nonlinear interaction of important factors in the electricity sector. The study results indicate that the energy policy should not be introduced in an isolated manner, but rather need to incorporate the incentives of renewables with other decisions such as nuclear decommission. Additionally, this study predicts an upcoming increase in electricity price, as well as a more volatile price after the capacity profile has been changed and dominated by hydro, biomass and wind. This study provides guidelines for policy makers and managers to make better-informed decisions for a healthy development of their businesses as well as of the entire electricity sector.

Renewable-aware geographical load balancing of web applications for sustainable data centers

The ever-increasing demand for web applications deployed across multiple data centers results in large electricity costs for service providers and significant impact on the environment. This has motivated service providers to move towards more sustainable data centers powered by renewable or green sources of energy, such as solar or wind. However, efficient utilization of green energy to service web applications is a challenging problem due to intermittency and unpredictability of both application workload and renewable energy availability. One possible solution to reduce cost and increase renewable energy utilization is to exploit the spatio-temporal variations in on-site power and grid power prices by balancing the load among multiple data centers geographically distributed. In this paper, we propose a framework for reactive load balancing of web application requests among Geo-distributed sustainable data centers based on the availability of renewable energy sources on each site. A system prototype is developed, its underlying design and algorithms are described, and experiments are conducted with it using real infrastructure (Grid'5000 in France) and workload traces (real traffic to English Wikipedia). The experimental results demonstrate that our approach can reduce cost and brown energy usage with efficient utilization of green energy and without a priori knowledge of future workload, availability of renewable energy, and grid electricity prices.

Hydropower and Power-to-gas Storage Options: The Brazilian Energy System Case

In this study, a 100% renewable energy (RE) system for Brazil in 2030 was simulated using an hourly resolution model. The optimal sets of RE technologies, mix of capacities, operation modes and least cost energy supply were calculated and the role of storage technologies was analysed. The RE generated was not only able to fulfil the electricity demand of the power sector but also able to cover the 25% increase in total electricity demand due to water desalination and synthesis of natural gas for industrial use. The results for the power sector show that the total installed capacity is formed of 165 GW of solar photovoltaics (PV), 85 GW of hydro dams, 12 GW of hydro run-of-river, 8 GW of biogas, 12 GW of biomass and 8 GW of wind power. For solar PV and wind electricity storage, 243 GWhel of battery capacity is needed. According to the simulations the existing hydro dams will function similarly to batteries, being an essential electricity storage. 1 GWh of pumped hydro storage, 23 GWh of adiabatic compressed air storage and 1 GWh of heat storage are used as well. The small storage capacities can be explained by a high availability of RE sources with low seasonal variability and an existing electricity sector mainly based on hydro dams. Therefore, only 0.05 GW of PtG technologies are needed for seasonal storage in the electricity sector. When water desalination and industrial gas sectors’ electricity demand are integrated to the power sector, a reduction of 11% in both total cost and electric energy generation was achieved. The total system levelized cost of electricity decreased from 61 €/MWh to 53 €/MWh for the sector integration.

Dynamic modeling of natural gas quality within transport pipelines in presence of hydrogen injections

In the near future, the natural gas grid could face an increasing share of alternative fuels (biomethane, hydrogen) injected in addition to the traditional mixture. Indeed, this pathway is particularly promising in order to reach environmental objectives of CO2 emissions reduction, in both thermal and electrical final uses. Biogas is already abundantly produced and could be easily upgraded to biomethane; hydrogen technologies are still under development, but they can help the exploitation of the increasing availability of renewable energy sources. A promising solution to problems due to unpredictable fluctuations of renewable energy production (in particular related to wind parks) or excess energy with respect to the load lies in hydrogen production by electrolysis and further injection in the natural gas grid. In this scenario, the effects on design and management of the transport infrastructure should be investigated, and the compliance with composition limits and quality constraints has to be analyzed in both stationary and dynamic operation, tracking the gas quality downstream the injection point of the alternative fuels. A model was developed to simulate the unsteady operation of a portion of the gas grid; with respect to traditional volume-based approaches, a novel energy-based approach is developed, including variable composition along the pipes and allowing to consider a given energy delivery to customers as a constraint. After the validation against available operational data, a case study considering concentrated realistic domestic and industrial offtakes is simulated. The effects of hydrogen injection, usually not considered in NG grid design and operation analyses, are investigated in terms of composition, flow rate and pressure profiles with comparison to the reference natural gas case. The analysis shows how imposed quality thresholds can be respected, although the effects on calorific value, Wobbe index and density are not negligible; results indicate that the allowed hydrogen fractions are limited and highly sensitive to the profile and size of the offtakes connected to the pipeline. The discussion also evidences the potential impact of hydrogen injection on gas metering and measurements errors.

A useful model for solar radiation

Energy crisis is one of the major issues of our society. There are different forms of renewable energy like wind power, geothermal energy, biomass from plants and solar energy. Solar energy is the only freely available source of renewable energy that comes directly from sun and may be converted into heat or electricity. In this article, we develop a model for solar radiation by considering the laminar flow of an incompressible Oldroyd-B fluid toward a thermally and solutally stratified moving surface with nanoparticles and thermal radiation. The data have been computed by homotopic algorithm. The computed solutions of velocity, temperature and nanoparticle concentration are plotted for multiple values of parameters of interest.

Influence of vegetation canopies on solar potential in urban environments

Solar energy is clearly a promising option among the many available sources of renewable energy, and its market has seen outstanding growth. Careful evaluation to determine suitable locations for photovoltaic installations is needed, however, as their efficiency is highly dependent on exposure to sun. Especially in urban environments, quantifying the shadows cast by other buildings and vegetation canopies may be essential. In the present study, we used light detection and ranging (LiDAR) data and geographic information systems (GIS) to assess the influence of shading vegetation on solar irradiation estimates in five European towns. The fraction of annual solar irradiation lost to shading by existing vegetation ranged between 3% and 11%. The fraction lost was higher in winter and lower in summer. Due to greater incoming solar radiation in summer, however, more than 50% of annual loss was accounted for in summer. We suggest that at the broad scale of whole cities the influence of vegetation on rooftop solar potential estimates is negligible (especially in densely populated areas). Analyses which do not consider vegetation because of data availability nevertheless provide valuable insight into localities' solar potential.

A commentary on the US policies for efficient large scale renewable energy storage systems: Focus on carbon storage cycles

The inevitable depletion of fossil resources and increasing atmospheric greenhouse gas concentrations demonstrate the need for renewable energy conversion technologies for a sustainable economy. Intermittencies and variability in availability of renewable energy sources are the challenges for uninterrupted energy supply, which can be overcome by large scale energy storage facilities. Pumped hydroelectric energy storage is an efficient but a very low energy density energy storage method that dominates the current energy storage market with ~96% share. We first present a recently developed potential solution for large scale efficient and dense energy storage: closed loop carbon storage cycles and a specific example dimethyl ether storage cycle. We then discuss the relevant US energy storage regulations, policy initiatives, their status, and potential modifications that will contribute to the invention and implementation of novel energy storage systems.

Study of Hybrid PV-Wind Energy System to Isolated Micro-grid

The optimal sizing of the isolated hybrid microgrid using an optimization technique was proposed. The hybrid system features WT, PV and conversion systems were used to feed the electrical load demand. A HOMER software was used to model system performance during a time of one year, considering Sensitivity variations in both the availability of renewable energy sources and variations in the load demand. The optimal solution was obtained with respect to decrease the cost of energy (COE) and the loss of power supply probability (LPSP) over a project lifetime of 25 years to improve the isolated operation of the microgrid. The aim of this study is to investigate an optimum combination of different energy systems which can supply electricity to a rural area in Egypt. The results show the COE for the optimal model was found 0.139 $/kWh which is less than half of the PV or WT system.

Efficient cogeneration and district heating systems in bioenergy villages: an optimization approach

The availability of renewable energy sources and highly efficient technologies are two major considerations when evaluating a sustainable energy supply with low carbon emission. Bioenergy villages combine the use of biomass as a renewable energy source with the efficient cogeneration of heat and power. The planning of these bioenergy villages using biomass as a source of electricity and heat calls for the simultaneous identification of facility location, capacity planning, and network design for the heating grid. A linear mathematical model is presented, that optimizes the local bioenergy production and distribution system and considers various parameters such as biomass availability, the number of heat customers, or heat loss in the system. The model is applied and validated using a case study in a small village in Lower Saxony (Germany).

Finding an optimal strategy of incorporating renewable sources of energy and electricity storing systems in a regional electrical grid

A game with a finite (more than three) number of players on a polyhedron of connected player strategies is studied. This game describes the interaction among (a) the base load power plant (the generator), (b) all the large customers of a regional electrical grid that receive electric energy from the generator, as well as from the available renewable sources of energy, both directly and via electricity storing facilities, and (c) the transmission company. An auxiliary three-person game on polyhedra of disjoint player strategies that is associated with the initial game is also considered. It is shown that an equilibrium point in the auxiliary game is an equilibrium point in the above game with connected player strategies. Verifiable necessary and sufficient conditions of an equilibrium in the auxiliary three-person game are proposed, and these conditions allow one to find equilibria in (the auxiliary) solvable game by solving three linear programming problems two of which form a dual pair.

A game-theoretic approach to optimizing the scale of incorporating renewable sources of energy and electricity storing systems in a regional electrical grid

The problem of developing a decision support system for estimating a) the scale of incorporating available renewable sources of energy (such as solar and wind energy) in a part of a country’s electrical grid (called a regional electrical grid further in this paper), and b) the scale of storing electricity in this (regional) electrical grid to make these renewable sources of electric power competitive with traditional power generators (such as fossil-fuel and nuclear ones) and to reduce the cost of acquiring electricity from all the electric power generating facilities in the grid is considered. In the framework of this system, renewable sources of energy are viewed as electricity generating facilities under both existing and expected electricity prices, and the uncertainty of energy supply from them and the uncertainty of the grid customer demand for electricity during every 24 h are taken into account. A mathematical model underlying the system allows one to study the interaction of all the grid elements as a game with a finite (more than three) number of players on a polyhedron of connected player strategies (i.e., strategies that cannot be chosen by the players independently of each other) in a finite-dimensional space. It is shown that solving both parts of the problem under consideration is reducible to finding Nash equilibrium points in this game.

Costs assessments of European environmental policies

The evolution of energy production in the European Union (EU) is going through a big change in recent years: the incidence of traditional fuels is diminishing gradually for increasing renewable energy sources (RES), due to international concerns over climate change and for energy security reasons. The aim of this paper is to construct a simulation model that identifies and estimates costs that may arise for a community of negotiating countries from opportunistic behavior of some country when defining environmental policies. In this paper, the model is applied specifically to the new 2030 Framework for Climate and Energy Policies (COM(2014) 0015) (EC, 2014 [11]) on the promotion of RES that commits EU governments to a common goal to increase the share of RES in final consumption to 27% by 2030. Costs faced by EU countries to achieve the RES target are different due to their endowment heterogeneity, the availability of RES, the diffusion process of cost improvements and the different instruments to support the development of the RES technologies. Given the still undefined participation agreement to reach the new overall RES target by 2030, we want to assess the potential cost penalty induced by free riding behavior. This could stem from some EU country, which avoids complying with the RES Directive. Our policy simulation exercise shows that costs increase more than proportionally with the non-participating country size, measured with GDP and CO2 emissions. Furthermore, we provide a model to analytically assess the likelihood each EU country may have to behave opportunistically within the negotiation process of the new proposal on EU RES targets (COM(2014) 0015).

Enabling practical electrocatalyst-assisted photoelectron-chemical water splitting with earth abundant materials

Sustainable development and continued prosperity of humanity hinge on the availability of renewable energy sources on a terawatts scale. In the long run, solar energy is the only source that can meet this daunting demand. Widespread utilization of solar energy faces challenges as a result of its diffusive (hence low energy density) and intermittent nature. How to effectively harvest, concentrate, store and redistribute solar energy constitutes a fundamental challenge that the scientific community needs to address. Photoelectrochemical (PEC) water splitting is a process that can directly convert solar energy into chemical energy and store it in chemical bonds, by producing hydrogen as a clean fuel source. It has received significant research attention lately. Here we provide a concise review of the key issues encountered in carrying out PEC water splitting. Our focus is on the balance of considerations such as stability, earth abundance, and efficiency. Particular attention is paid to the combination of photoelectrodes with electrocatalysts, especially on the interfaces between different components.