A Demand-Supply Matching-Based Approach for Mapping Renewable Resources towards 100% Renewable Grids in 2050

Recently, many renewable energy (RE) initiatives around the world are based on general frameworks that accommodate the regional assessment taking into account the mismatch of supply and demand with pre-set goals to reduce energy costs and harmful emissions. Hence, relying entirely on individual assessment and RE deployment scenarios may not be effective. Instead, developing a multi-faceted RE assessment framework is vital to achieving these goals. In this study, a regional RE assessment approach is presented taking into account the mismatch of supply and demand with an emphasis on Photovoltaic (PV) and wind turbine systems. The study incorporates mapping of renewable resources optimized capacities for different configurations of PV and wind systems for multiple sites via test case. This approach not only optimizes system size but also provides the appropriate size at which the maximum renewable energy fraction in the regional power generation mix is maximized while reducing energy costs using MATLAB’s ParetoSearch algorithm. The performance of the proposed approach is tested in a realistic test site, and the results demonstrate the potential for maximizing the RE share compared to the achievable previously reported fractions. The results indicate the importance of resource mapping based on energy-demand matching rather than a quantitative assessment of anchorage sites. In the examined case study, the new assessment approach led to the identification of the best location for installing a hybrid PV / wind system with a storage system capable of achieving a nearly 100% autonomous RE system with Levelized cost of electricity of 0.05 USD/kWh

Performance and economic analysis of hybrid microhydro systems

Microhydro (MHP) systems usually employ unregulated turbines and an electronic load controller, a demand-side control device. Existing analytical models for such systems are lacking details, especially supply-side flow control, for performance simulation at hourly or sub-hourly scales. This work developed stochastic models for downscaling of streamflow and an empirical model of MHP systems. We integrated these models within the framework of Hybrid2 tool to simulate the long-term performance of a tri-hybrid system consisting of hydropower, solar PV and wind turbine. Based on an additive model of time series decomposition, we develop a Multiple Input Single Output (MISO) model in order to synthesize an hourly time series of streamflow. The MISO model takes into account daily precipitation dataset as well as regional hydrological characteristics. The model employs a constrained Monte-Carlo Markov Chain (MCMC) algorithm which is validated against an hourly time series of flow data at Blue River at Blue, Oklahoma. A non-dimensional performance model of MHP systems is developed based on empirical data from Nepal. Three design configurations are presented for a case study. The results show that, along with a small pond that can store water for an hour at the rated capacity of MHP system, a hybrid system with half the size of the battery bank can supply the load year around at Thingan Project in Nepal. This system meets the availability requirements of the Multi-Tier Framework for measuring energy access for household supply. The new proposed system is marginal in the economic sense as well. This project can never recover the initial capital cost at a current rate of the tariff which is about 7 cents/kWh. Other O&M risks aside, the sensitivity analysis suggests that the system may barely recover the initial capital cost, excluding the subsidy, at twice the existing rate of tariff and half the interest rate. This study aspires to come up with better techniques to simulate hybrid microhydro systems and enhance their design and operation through more effective utilization of resources

Considering Life Cycle Greenhouse Gas Emissions in Power System Expansion Planning for Europe and North Africa Using Multi-Objective Optimization

We integrate life cycle indicators for various technologies of an energy system model with high spatiotemporal detail and a focus on Europe and North Africa. Using multi-objective optimization, we calculate a pareto front that allows us to assess the trade-offs between system costs and life cycle greenhouse gas (GHG) emissions of future power systems. Furthermore, we perform environmental ex-post assessments of selected solutions using a broad set of life cycle impact categories. In a system with the least life cycle GHG emissions, the costs would increase by ~63%, thereby reducing life cycle GHG emissions by ~82% compared to the cost-optimal solution. Power systems mitigating a substantial part of life cycle GHG emissions with small increases in system costs show a trend towards a deployment of wind onshore, electricity grid and a decline in photovoltaic plants and Li-ion storage. Further reductions are achieved by the deployment of concentrated solar power, wind offshore and nuclear power but lead to considerably higher costs compared to the cost-optimal solution. Power systems that mitigate life cycle GHG emissions also perform better for most impact categories but have higher ionizing radiation, water use and increased fossil fuel demand driven by nuclear power. This study shows that it is crucial to consider upstream GHG emissions in future assessments, as they represent an inheritable part of total emissions in ambitious energy scenarios that, so far, mainly aim to reduce direct CO$_{2}$ emissions

A Polygeneration System Based on Desiccant Air Conditioning Coupled with an Electrical Storage

This study presents an extension of a previous paper recently published by the authors. In particular, the current paper focuses on adding electrical storage to a polygeneration system developed for residential applications. Different from the previous work, it aims to design an off-grid facility. The polygeneration plant provides electricity, space heating and cooling, domestic hot water, and freshwater for a single-family dwelling in Almería, Spain. The main system technologies are photovoltaic/thermal collectors, reverse osmosis, and desiccant air conditioning. Lead-acid battery storage was added as a backup for the electrical system. The system was performed in the TRNSYS simulation environment for one year with a 5-min time step. A parametric study was carried out to investigate the grid dependence according to the number of batteries installed. Design optimization was also performed to provide the optimal system configuration for the off-grid case. A solar collector efficiency of 0.55 and a desiccant air-conditioning coefficient of performance of 0.42 were obtained. All demands were fully supplied, and the primary energy saving and CO2 saving achieved 100%. A minimum battery state of charge of 30% was reached for a few hours all year long

供給と需要側を考慮した電源システムのモデリングと評価

Modelling and optimization of sustainable power system and energy network are becoming complex engineering. Demand side resources also need to be planned considering characteristics of district energy supply scenario. This research first analyzes the feasibility of VPP based on scenario of Chongming Island. VPP focuses on expansion of renewable energy and upgrade of efficient appliances, results verify the effectiveness of the VPP concept. Then investigates the techno-economic viability of high variable renewable integration. PV-PHS dispatch scenarious are carried out with constraints, PHS effectively recovers the suppression and decreases the PV power levelized cost. Introduction PV-PHS shifts merit order curve to right, decreasing power generating cost. Thirdly, cost and environmental benefits of optimal designed decentralized energy systems were investigated. Scheduled distributed energy resources could be optimized to benefit the public grid. Performance of dynamic price is investigated based on the social demonstration project experiment. Finally, the conclusions are provided.北九州市立大

Supervisory model predictive control of building integrated renewable and low carbon energy systems

To reduce fossil fuel consumption and carbon emission in the building sector, renewable and low carbon energy technologies are integrated in building energy systems to supply all or part of the building energy demand. In this research, an optimal supervisory controller is designed to optimize the operational cost and the CO2 emission of the integrated energy systems. For this purpose, the building energy system is defined and its boundary, components (subsystems), inputs and outputs are identified. Then a mathematical model of the components is obtained. For mathematical modelling of the energy system, a unified modelling method is used. With this method, many different building energy systems can be modelled uniformly. Two approaches are used; multi-period optimization and hybrid model predictive control. In both approaches the optimization problem is deterministic, so that at each time step the energy consumption of the building, and the available renewable energy are perfectly predicted for the prediction horizon. The controller is simulated in three different applications. In the first application the controller is used for a system consisting of a micro-combined heat and power system with an auxiliary boiler and a hot water storage tank. In this application the controller reduces the operational cost and CO2 emission by 7.31 percent and 5.19 percent respectively, with respect to the heat led operation. In the second application the controller is used to control a farm electrification system consisting of PV panels, a diesel generator and a battery bank. In this application the operational cost with respect to the common load following strategy is reduced by 3.8 percent. In the third application the controller is used to control a hybrid off-grid power system consisting of PV panels, a battery bank, an electrolyzer, a hydrogen storage tank and a fuel cell. In this application the controller maximizes the total stored energies in the battery bank and the hydrogen storage tank

OFF-GRID OPTIMIZATION ANALYSIS OF HYBRID SOLAR-WIND POWER SYSTEM IN UTP USING HOMER SOFTWARE

Through this Paper a project on studying the off-grid optimization of hybrid renewable energy system using Homer software in Universiti Teknologi PETRONAS will be introduced on an average of 20 modern homes located in Village 6. The government of Malaysia has expressed its interests and commitment towards developing the renewable energy sector as stated in the 9th Malaysian Plan. Solar and wind energy sources are intermittent sources of energy. They are not available on demand and necessary implementation of backup systems is to be arranged to obtain a reliable supply. The reliability and overall performance of solar and wind power plants can be improved by implementing a hybrid system where both the solar and wind plants supplement each other to further enhance their energy harvesting capability

An Overview on Functional Integration of Hybrid Renewable Energy Systems in Multi-Energy Buildings

Buildings are responsible for over 30% of global final energy consumption and nearly 40% of total CO2 emissions. Thus, rapid penetration of renewable energy technologies (RETs) in this sector is required. Integration of renewable energy sources (RESs) into residential buildings should not only guarantee an overall neutral energy balance over long term horizon (nZEB concept), but also provide a higher flexibility, a real-time monitoring and a real time interaction with end-users (smart-building concept). Thus, increasing interest is being given to the concepts of Hybrid Renewable Energy Systems (HRES) and Multi-Energy Buildings, in which several renewable and nonrenewable energy systems, the energy networks and the energy demand optimally interact with each other at various levels, exploring all possible interactions between systems and vectors (electricity, heat, cooling, fuels, transport) without them being treated separately. In this context, the present paper gives an overview of functional integration of HRES in Multi-Energy Buildings evidencing the numerous problems and potentialities related to the application of HRESs in the residential building sector. Buildingintegrated HRESs with at least two RESs (i.e., wind–solar, solar–geothermal and solar–biomass) are considered. The most applied HRES solutions in the residential sector are presented, and integration of HRES with thermal and electrical loads in residential buildings connected to external multiple energy grids is investigated. Attention is focused on the potentialities that functional integration can offer in terms of flexibility services to the energy grids. New holistic approaches to the management problems and more complex architectures for the optimal control are described