A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems

Hybrid renewable energy systems (HRES) turned into an appealing choice for supplying loads in remote areas. The application of smart grid principals in HRES provides a communication between the load and generation from the HRES. Using smart grid in the HRES will optimally utilize the generating resources to reschedule the loads depending on its importance. This paper presents a new proposed design and optimization simulation program for techno-economic sizing of grid-independent hybrid PV/wind/diesel/battery energy system using Cuckoo search (CS) optimization algorithm. Using of CS will help to get the global minimum cost condition and prevent the simulation to be stuck around local minimum. A new proposed simulation program (NPSP) is acquainted using CS to determine the optimum size of each component of the HRES for the lowest cost of generated energy and the lowest value of dummy energy, at highest reliability. A detailed economic methodology to obtain the price of the generated energy has been introduced. Results showed that using CS reduced the time required to obtain the optimal size with higher accuracy than other techniques used iterative techniques, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Numerous significant outcomes can be extracted from the proposed program that could help scientists and decision makers.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Thermoeconomic installation limit of PV/WT hybrid energy systems for Off-grid islands

An ideal off-grid island can become 100% energy-sufficient if one installs renewable energy systems such as solar photovoltaic (PV) and wind turbine (WT) systems. However, the intermittent and uncertain nature of the power supply from renewable energy systems hinders a 100% autonomy level (AL) without an infinite energy storage capacity. The thermoeconomic installation limit (TEIL) of a PV/WT hybrid energy system was studied using hourly weather data and the energy demand profile for off-grid islands. An appropriate battery size for the TEIL was also determined. Given the current installation cost of the hybrid energy system and the battery unit, the AL for a PV/WT hybrid energy system at the TEIL is calculated to be approximately 70%. Above the limit, the size of the energy storage unit and, correspondingly, the total annual cost of the PV/WT hybrid energy system increase sharply.     

A review on optimization techniques for sizing of solar-wind hybrid energy systems

Solar and wind are inexhaustible, abundant, environmentally friendly and freely available renewable energy sources. Integration of these two sources has always been a complex optimization problem which requires efficient planning, designing and control strategies. Many researchers have designed cost effective and efficient hybrid solar-wind energy systems by using various available software tools and optimization algorithms. With the advancement in artificial intelligence methods, various new optimization techniques have been developed in the last few decades. This paper presents state of the art optimization methods applied to hybrid renewable based energy systems. A brief introduction of each technique is presented along with papers published in different reputed journals. This article also reviews different power management, control strategies and multi-objective optimization methods used for hybrid wind-solar systems. A case study is presented to demonstrate the efficacy of some of the algorithms.     

Multi-objective-based optimal transmission switching and demand response for managing congestion in hybrid power systems

ABSTRACT

This paper proposes a novel congestion management (CM) approach by using the optimal transmission switching (OTS) and demand response (DR) for a system with conventional thermal generators and renewable energy sources (RESs). In this paper, wind and solar PV units are considered as the RESs. The stochastic behavior of wind and solar PV powers are modeled by using the appropriate probability density functions (PDFs). The proposed CM methodology simultaneously optimizes the generation dispatch, demand response, and also the network topology of the power system. The OTS identifies the branches that should be taken out of service by significantly reducing the operating cost of the system while respecting the system security. Here, the total operating cost minimization/social welfare maximization and system losses minimization are considered as the objectives to be optimized. The proposed CM problem is solved using the multi-objective Jaya algorithm and it is used to determine a set of Pareto-optimal solutions. The Jaya algorithm is simple and it does not have any algorithmic-specific parameters to be tuned. This aspect reduces the designer’s effort in tuning the parameters to arrive at the optimum objective function value. A fuzzy logic-based approach is used to identify the best compromise solution. The effectiveness of the proposed CM approach is examined on modified IEEE 30 and practical Indian 75 bus test systems. The obtained simulation results are analyzed and they show the effectiveness of the proposed approach.     

Electricity systems with near-zero emissions of CO2 based on wind energy and coal gasification with CCS and hydrogen storage

Emissions from electricity generation will have to be reduced to near-zero to meet targets for reducing overall greenhouse gas emissions. Variable renewable energy sources such as wind will help to achieve this goal but they will have to be used in conjunction with other flexible power plants with low-CO₂ emissions. A process which would be well suited to this role would be coal gasification hydrogen production with CCS, underground buffer storage of hydrogen and independent gas turbine power generation. The gasification hydrogen production and CO₂ capture and storage equipment could operate at full load and only the power plants would need to operate flexibly and at low load, which would result in substantial practical and economic advantages. This paper analyses the performances and costs of such plants in scenarios with various amounts of wind generation, based on data for power demand and wind energy variability in the UK. In a scenario with 35% wind generation, overall emissions of CO₂ could be reduced by 98–99%. The cost of abating CO₂ emissions from the non-wind residual generation using the technique proposed in this paper would be less than 40% of the cost of using coal-fired power plants with integrated CCS.     

Optimization of grid tied hybrid power system in smart premises

Tapping of renewable energy sources like solar and wind is given great priority by power producers all over the world. Technical problems of linking them to the grid are solved. The cost constraints of utilizing renewable energy at specific locations are to be determined. In this work, a model is developed for grid tied hybrid power system (HPS) consisting of photovoltaic (PV) module and wind mill at the roof top of smart premises. The grid is capable of delivering and receiving energy. Objective function is formed with constraints taking into account the cost of PV module, wind mill, and grid tied inverter with controller. The constraints are rating of HPS and energy that can be delivered to the grid. Using this model, case studies were conducted in three locations in India, each location having two different demands. The results are presented. With the optimal rating of HPS, results shows that, conventional energy cost is higher.     

Game theory and hybrid genetic algorithm for energy management and real-time pricing in smart grid: the Tunisian case

ABSTRACT

Microgrids are the key for integrating renewable energy from different sources into smart grid, that is why power grid evolves into a combination of interconnected microgrids. In fact, future power grids are undergoing this groundbreaking change that will help meet the increasing demand of electric power and reduce carbon emission. In this sense we study in this paper, based on measured data, a real case of energy management in the area of Beja located in Tunisia. Indeed, we propose a model for the power exchange which proves the potential of applying game theory in the development of both real-time pricing and energy management mechanism for an open electricity market. We also introduce a hybrid genetic algorithm to compute the Nash Equilibrium. Results show that the proposed smart energy management can decrease the real cost of power up to 20%, to divide the energy transmission losses by a factor of two and to reduce the carbon emission in the area of Beja.     

Energy Supply Potentials and Needs, and the Environmental Impact of their Use in Sudan

Sudan is an agricultural country with fertile land, plenty of water resources, livestock, forestry resources, and agricultural residues. An overview of the energy situation in Sudan is introduced with reference to the end uses and regional distribution. Energy sources are divided into two main types; conventional energy (biomass, petroleum products, and electricity); and non-conventional energy (solar, wind, hydro-electricity, etc.). Sudan possesses a relatively high abundance of solar radiation, and moderate wind speeds, hydro, and biomass energy resources. The application of the new and renewable sources of energy available in Sudan is now a major issue in future energy strategic planning and for an alternative to fossil conventional energy. Sudan is an important case study in the context of renewable energy. It has a long history of meeting its energy needs through renewables. Sudan's renewables' portfolio is broad and diverse, due in part to the country's wide range of climates and landscapes. Like many of the African leaders in renewable energy utilization, Sudan has a well-defined commitment to continue research, development, and implementation of new technologies. Sustainable low-carbon energy scenarios for the new century emphasize the untapped potential of renewable resources. Rural areas of Sudan can benefit from this transition. The increased availability of reliable and efficient energy services stimulates new development alternatives. It is concluded that renewable, environmentally friendly, energy must be encouraged, promoted, invested, implemented, and demonstrated by full-scale plants, especially for use in the remote rural areas of Sudan.     

Conditions for a 100% renewable energy supply system in Japan and South Korea

In the wake of the Fukushima nuclear accident, alternative energy paths have been discussed for Japan, but except for a few studies the assumption is usually made that Japan is too densely populated to be suited for a near-100% sustainable, indigenous energy provision. The studies emphasizing renewable energy have proposed the use of photovoltaic power as the main source of electricity supply, in combination with diurnal battery storage and supplemented by other renewable sources such as wind, hydro, and geothermal power. Here, an alternative approach is explored, with wind and derived hydrogen production as the main energy source, but still using solar energy, biofuels, and hydropower in a resilient combination allowing full satisfaction of demands in all sectors of the economy, i.e., for dedicated electricity, transportation energy as well as heat for processes and comfort. Furthermore, the possible advantage of establishing a regional energy system with energy interchange and coordinated management of the mix of renewable energy resources across a wider region is discussed. As the closest neighbor, the energy system of South Korea is considered, first regarding the possibility of a similar full renewable energy reliance, and then for possible synergetic effects of connecting the Korean and the Japanese energy systems, in order to be able to better cope with the intermittency of renewable energy source flows.     

Sizing and performance analysis of standalone hybrid photovoltaic/battery/hydrogen storage technology power generation systems based on the energy hub concept

In this study, the optimal sizing and performance analysis of a standalone integrated solar power system equipped with different storage scenarios to supply the power demand of a household is presented. One of the main purposes when applying solar energy resource is to face the increasing environmental pollutions resulting from fossil fuel based electricity sector. To this end, and to compare and examine two energy storage technologies (battery and hydrogen storage technology), three storage scenarios including battery only, hydrogen storage technology only and hybrid storage options are evaluated. An optimization framework based on Energy Hub concept is used to determine the optimum sizes of equipment for the lowest net present cost (NPC) while maintaining the system reliability. It was determined that the most cost effective and reliable case is the system with hybrid storage technology. Also, the effects of solar radiation intensity, the abatement potential of CO₂ emissions and converting excess power to hydrogen on the system’s performance and economics, were investigated and a few noticeable findings were obtained.     

A novel wind speed forecasting model for wind farms of Northwest China

Wind resources are becoming increasingly significant due to their clean and renewable characteristics, and the integration of wind power into existing electricity systems is imminent. To maintain a stable power supply system that takes into account the stochastic nature of wind speed, accurate wind speed forecasting is pivotal. However, no single model can be applied to all cases. Recent studies show that wind speed forecasting errors are approximately 25% to 40% in Chinese wind farms. Presently, hybrid wind speed forecasting models are widely used and have been verified to perform better than conventional single forecasting models, not only in short-term wind speed forecasting but also in long-term forecasting. In this paper, a hybrid forecasting model is developed, the Similar Coefficient Sum (SCS) and Hermite Interpolation are exploited to process the original wind speed data, and the SVM model whose parameters are tuned by an artificial intelligence model is built to make forecast. The results of case studies show that the MAPE value of the hybrid model varies from 22.96% to 28.87 %, and the MAE value varies from 0.47 m/s to 1.30 m/s. Generally, Sign test, Wilcoxon’s Signed-Rank test, and Morgan--Granger--Newbold test tell us that the proposed model is different from the compared models.     

A multi-period optimization model for energy planning with CO2 emission consideration

A novel deterministic multi-period mixed-integer linear programming (MILP) model for the power generation planning of electric systems is described and evaluated in this paper. The model is developed with the objective of determining the optimal mix of energy supply sources and pollutant mitigation options that meet a specified electricity demand and CO₂ emission targets at minimum cost. Several time-dependent parameters are included in the model formulation; they include forecasted energy demand, fuel price variability, construction lead time, conservation initiatives, and increase in fixed operational and maintenance costs over time. The developed model is applied to two case studies. The objective of the case studies is to examine the economical, structural, and environmental effects that would result if the electricity sector was required to reduce its CO₂ emissions to a specified limit.     

CO2 capture and storage from a bioethanol plant: Carbon and energy footprint and economic assessment

Biomass energy and carbon capture and storage (BECCS) can lead to a net removal of atmospheric CO₂. This paper investigates environmental and economic performances of CCS retrofit applied to two mid-sized refineries producing ethanol from sugar beets. Located in the Region Centre France, each refinery has two major CO₂ sources: fermentation and cogeneration units. “carbon and energy footprint” (CEF) and “discounted cash flow” (DCF) analyses show that such a project could be a good opportunity for CCS early deployment. CCS retrofit on fermentation only with natural gas fired cogeneration improves CEF of ethanol production and consumption by 60% without increasing much the non renewable energy consumption. CCS retrofit on fermentation and natural gas fired cogeneration is even more appealing by decreasing of 115% CO₂ emissions, while increasing non renewable energy consumption by 40%. DCF shows that significant project rates of return can be achieved for such small sources if both a stringent carbon policy and direct subsidies corresponding to 25% of necessary investment are assumed. We also underlined that transport and storage cost dilution can be realistically achieved by clustering emissions from various plants located in the same area. On a single plant basis, increasing ethanol production can also produce strong economies of scale.     

Co-production of hydrogen and electricity with CO2 capture

Electricity and hydrogen can be used as energy carriers to reduce emissions of CO₂ from small and mobile energy users. One of the most promising technologies for the production of electricity and hydrogen with low CO₂ emissions is coal gasification with CO₂ capture and storage. Performance and cost data are presented for plants which produce electricity and hydrogen alone and plants which co-produce both of these energy carriers. The co-production plants include plants which produce a fixed ratio of hydrogen to electricity and plants which are able to vary the ratio while continuing to operate the gasification and CO₂ capture parts of the plant at full load. The paper also assesses the ability of these types of plants to satisfy the varying demands for hydrogen and electricity in future energy supply systems. The lowest cost option for the scenarios assessed in the paper is the use of flexible co-production plants with underground buffer storage of hydrogen.     

An investigation of renewable resources and renewable technology applications in Bulgaria

A preliminary assessment of renewable energy resources in Bulgaria shows that these resources are significant on a national level. Terminology for total, accessible, and reserve resources is provided, and preliminary estimates for solar, wind, biomass, hydroelectric, and geothermal resources are given. The process used to make a first-level selection of renewable energy technologies for further evaluation is described and an initial ranking of technologies for electricity generation, industry, and buildings is provided.

     

Triple-objective optimal sizing based on dynamic strategy for an islanded hybrid energy microgrid

A triple-objective optimal sizing method based on a dynamic strategy is presented for an islanded hybrid energy microgrid, consisting of wind turbine, solar photovoltaic, battery energy storage system and diesel generator. The dynamic strategy is given based on a dynamic complementary coordination between two different master-slave control modes for maximum renewable energy utilization. Combined with the proposed strategy, NSGA-II-based optimization program is applied to the sizing optimization problem with triple different objectives including the minimization of annualized system cost, the minimization of loss of power supply probability and the maximization of utilization ratio of renewable energy generation. The sizing results and the proposed strategy are both compared and analyzed to validate the proposed method in a real case of an islanded hybrid energy microgrid on Dong’ao Island, China.     

Alternative energy balances for Bulgaria to mitigate climate change

Alternative energy balances aimed to mitigate greenhouse gas (GHG) emissions are developed as alternatives to the baseline energy balance. The section of mitigation options is based on the results of the GHG emission inventory for the 1987–1992 period. The energy sector is the main contributor to the total CO₂ emissions of Bulgaria. Stationary combustion for heat and electricity production as well as direct end-use combustion amounts to 80% of the total emissions. The parts of the energy network that could have the biggest influence on GHG emission reduction are identified. The potential effects of the following mitigation measures are discussed: rehabilitation of the combustion facilities currently in operation; repowering to natural gas; reduction of losses in thermal and electrical transmission and distribution networks; penetration of new combustion technologies; tariff structure improvement; renewable sources for electricity and heat production; wasteheat utilization; and supply of households with natural gas to substitute for electricity in space heating and cooking. The total available and the achievable potentials are estimated and the implementation barriers are discussed.

     

可再生能源技术在我国旅游循环经济发展中的应用

可再生资源代替常规能源使用，是旅游可持续发展的客观要求，是旅游循环经济应用的重要方面。太阳能、风能、水能、生物质能、地热能和海洋能利用技术可广泛应用于旅游循环经济系统中的旅游区（点）、旅行社、住宿、餐饮、交通、购物、娱乐等旅游企业。应采取观念更新、政府支持、技术支持等措施推进可再生资源技术在发展旅游循环经济中的研发、推广与运用。