Complementarity between Combined Heat and Power Systems, Solar PV and Hydropower at a District Level: Sensitivity to Climate Characteristics along an Alpine Transect

Combined heat and power systems (CHP) produce heat and electricity simultaneously. Their resulting high efficiency makes them more attractive from the energy managers’ perspective than other conventional thermal systems. Although heat is a by-product of the electricity generation process, system operators usually operate CHP systems to satisfy heat demand. Electricity generation from CHP is thus driven by the heat demand, which follows the variability of seasonal temperature, and thus is not always correlated with the fluctuation of electricity demand. Consequently, from the perspective of the electricity grid operator, CHP systems can be seen as a non-controllable energy source similar to other renewable energy sources such as solar, wind or hydro. In this study, we investigate how ‘non-controllable’ electricity generation from CHP systems combines with ‘non-controllable’ electricity generation from solar photovoltaic panels (PV) and run-of-the river (RoR) hydropower at a district level. Only these three energy sources are considered within a 100% renewable mix scenario. Energy mixes with different shares of CHP, solar and RoR are evaluated regarding their contribution to total energy supply and their capacity to reduce generation variability. This analysis is carried out over an ensemble of seventeen catchments in North Eastern Italy located along a climate transect ranging from high elevation and snow dominated head-water catchments to rain-fed and wet basins at lower elevations. Results show that at a district scale, integration of CHP systems with solar photovoltaic and RoR hydropower leads to higher demand satisfaction and lower variability of the electricity balance. Results also show that including CHP in the energy mix modifies the optimal relative share between solar and RoR power generation. Results are consistent across the climate transect. For some districts, using the electricity from CHP might also be a better solution than building energy storage for solar PV.

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A Smart Adaptive Switching Module Architecture Using Fuzzy Logic for an Efficient Integration of Renewable Energy Sources. A Case Study of a RES System Located in Hulubești, Romania

Sustainability ◽

10.3390/su12156084 ◽

2020 ◽

Vol 12 (15) ◽

pp. 6084

Author(s):

Simona-Vasilica Oprea ◽

Adela Bâra ◽

Ștefan Preda ◽

Osman Bulent Tor

Keyword(s):

Fuzzy Logic ◽

Renewable Energy ◽

Power Systems ◽

Electricity Generation ◽

Renewable Energy Sources ◽

Storage System ◽

Weather Conditions ◽

Energy Sources ◽

Fuzzy Logic Systems

Electricity generation from renewable energy sources (RES) has a common feature, that is, it is fluctuating, available in certain amounts and only for some periods of time. Consuming this electricity when it is available should be a primary goal to enhance operation of the RES-powered generating units which are particularly operating in microgrids. Heavily influenced by weather parameters, RES-powered systems can benefit from implementation of sensors and fuzzy logic systems to dynamically adapt electric loads to the volatility of RES. This study attempts to answer the following question: How to efficiently integrate RES to power systems by means of sustainable energy solutions that involve sensors, fuzzy logic, and categorization of loads? A Smart Adaptive Switching Module (SASM) architecture, which efficiently uses electricity generation of local available RES by gradually switching electric appliances based on weather sensors, power forecast, storage system constraints and other parameters, is proposed. It is demonstrated that, without SASM, the RES generation is supposed to be curtailed in some cases, e.g., when batteries are fully charged, even though the weather conditions are favourable. In such cases, fuzzy rules of SASM securely mitigate curtailment of RES generation by supplying high power non-traditional storage appliances. A numerical case study is performed to demonstrate effectiveness of the proposed SASM architecture for a RES system located in Hulubești (Dâmbovița), Romania.

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Circumventing Unintended Impacts of Waste N95 Facemask Generated during the COVID-19 Pandemic: A Conceptual Design Approach

ChemEngineering ◽

10.3390/chemengineering4030054 ◽

2020 ◽

Vol 4 (3) ◽

pp. 54

Author(s):

Oseweuba Valentine Okoro ◽

Adjoa Nkrumah Banson ◽

Hongxia Zhang

Keyword(s):

Environmental Performance ◽

Electricity Generation ◽

Fermentation Process ◽

Combined Heat And Power ◽

Hydrothermal Liquefaction ◽

Process Models ◽

Protective Equipment ◽

Generation Process ◽

Liquefaction Process ◽

Waste Conversion

The global crisis arising from the current COVID-19 pandemic has resulted in a surge in the magnitude of global waste from used Personal Protective Equipment with special emphasis on waste N95 facemask. Creative approaches are therefore required to resolve the surging facemask waste disposal issue in an economical and environmentally friendly manner. In an attempt to resolve the evolving global waste challenge, the present study has assessed the economic and environmental performances of converting N95 facemasks to steam and electricity via a combined heat and power plant, to ethanol via a syngas fermentation process, and to an energy-dense gasoline-like oil product via a hydrothermal liquefaction process. These processes were assessed using “conceptual” process models developed using ASPEN plus as the process simulation tool. Economic and environment assessments were undertaken using net present values (NPVs) and the rate of potential environmental impacts (PEIs) respectively, as sufficient performance measures. Therefore, the present study was able to establish that the conversion of waste N95 facemask to syngas prior to a fermentation process for ethanol production constituted the least economical and least environmental friendly process with a negative NPV and the highest rate of PEI (1.59 PEI/h) value calculated. The NPV values calculated for N95 facemask waste conversion to steam and electricity and energy-dense oil processes were US$ 36.6 × 106 and US$ 53 × 106 respectively, suggesting the preference for the production of a valuable energy-dense oil product. Furthermore, it was observed that when the environmental performance of both processes was considered, rates of PEIs of 1.20 and 0.28 PEI/h were estimated for the energy-dense oil production process and the steam and electricity generation process, respectively. Therefore, the study was able to establish that the utilisation of waste N95 facemask for steam and electricity generation and for generating an energy-dense oil product are both promising approaches that could aid in the resolution of the waste issue if both environmental and economic performances constitute crucial considerations.

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Barriers and Solutions for Increasing the Integration of Solar Photovoltaic in Kenya’s Electricity Mix

Energies ◽

10.3390/en13205502 ◽

2020 ◽

Vol 13 (20) ◽

pp. 5502

Author(s):

Dominic Samoita ◽

Charles Nzila ◽

Poul Alberg Østergaard ◽

Arne Remmen

Keyword(s):

Geothermal Energy ◽

Trade Balance ◽

Electricity Generation ◽

Renewable Energy Sources ◽

Electricity Production ◽

Solar Photovoltaic ◽

Solar Pv ◽

Storage Solutions ◽

Electricity Mix ◽

National Trade

Currently, Kenya depends mainly on oil, geothermal energy and hydro resources for electricity production, however all three have associated issues. Oil-based electricity generation is environmentally harmful, expensive and a burden to the national trade balance. The rivers for hydropower and their tributaries are found in arid and semi-arid areas with erratic rainfall leading to problems of supply security, and geothermal exploitation has cost and risk issues amongst others. Given these problems and the fact that Kenya has a significant yet underexploited potential for photo voltaic (PV)-based power generation, the limited—although growing—exploitation of solar PV in Kenya is explored in this paper as a means of diversifying and stabilising electricity supply. The potential for integration of PV into the Kenyan electricity generation mix is analysed together with the sociotechnical, economic, political, and institutional and policy barriers, which limit PV integration. We argue that these barriers can be overcome with improved and more robust policy regulations, additional investments in research and development, and improved coordination of the use of different renewable energy sources. Most noticeably, storage solutions and other elements of flexibility need to be incorporated to balance the intermittent character of electricity generation based on solar PV.

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A Probabilistic Approach for Transient Stability Analysis of Power Systems with Solar Photovoltaic Energy Sources

2016 IEEE Green Technologies Conference (GreenTech) ◽

10.1109/greentech.2016.36 ◽

2016 ◽

Author(s):

Muthanna Al-Sarray ◽

Haider Mhiesan ◽

Mahmood Saadeh ◽

Roy McCann

Keyword(s):

Stability Analysis ◽

Power Systems ◽

Transient Stability ◽

Probabilistic Approach ◽

Energy Sources ◽

Solar Photovoltaic ◽

Photovoltaic Energy ◽

Transient Stability Analysis

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Analyzing the impact of dust accumulation and different cleaning mechanism on efficiency of solar photovoltaic panel

Thermal Science and Engineering ◽

10.24294/tse.v1i3.730 ◽

2018 ◽

Vol 1 (3) ◽

Author(s):

Atul Kumar1 ◽

Srivastava Manish2

Keyword(s):

Renewable Energy Sources ◽

Dust Particles ◽

Energy Sources ◽

Pollution Level ◽

Solar Photovoltaic ◽

Solar Pv ◽

Photovoltaic Panel ◽

Pv Systems ◽

The Impact ◽

Rooftop Solar

Electricity generation around the world is mainly produced by using non-renewable energy sources especially in the commercial buildings. However, Rooftop solar Photovoltaic (PV) system produced a significant impact on environmental and economical benefits in comparison to the conventional energy sources, thus contributing to sustainable development. Such PV’s system encourages the production of electricity without greenhouse gas emissions that leads to a clean alternative to fossil fuels and economic prosperity even in less developed areas. However, efficiency of rooftop solar PV systems depends on many factors, the dominant being geographical (latitude, longitude, and solar intensity), environmental (temperature, wind, humidity, pollution, dust, rain, etc.) and the type of PV (from raw material extraction and procurement, to manufacturing, disposal, and/or recycling) used. During the feasibility analysis of the environment, geographical conditions are keep in well consideration, but the pollution level of the city is always overlooked, which significantly influences the performance of the PV installations. Therefore, this research work focused on the performance of rooftop solar PV installed in one of the most polluted city in India. Here, the loss in power generation of rooftop solar PV has been studied for the effect of deposited dust particles, wind velocity before and after the cleaning of the panels. The actual data has been utilized for the calculation of the energy efficiency and power output of the PV systems. According to the results, it has been concluded that dust deposition, wind speed and pollution level in city significantly reduces the efficiency of solar photovoltaic panel. Hence, an overview of social and environmental impacts of PV technologies is presented in this paper along with potential benefits and pitfalls.

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Review on Optimised Configuration of Hybrid Solar-PV Diesel System for Off-Grid Rural Electrification.

International Journal of Power Electronics and Drive Systems (IJPEDS) ◽

10.11591/ijpeds.v9.i3.pp1374-1380 ◽

2018 ◽

Vol 9 (3) ◽

pp. 1374

Author(s):

Amanda Halim ◽

Ahmad Fudholi ◽

Stephen Phillips ◽

Kamaruzzaman Sopian

Keyword(s):

Solar Energy ◽

Electricity Generation ◽

Efficient Solution ◽

Energy Sources ◽

Rural Electrification ◽

Solar Pv ◽

Pv System ◽

Solar Pv System ◽

System Configurations ◽

Electric Loads

<p>At present, solar energy is perceived to be one of the world’s contributive energy sources. Holding characteristics such as inexhaustible and non-polluting, making it as the most prominent among renewable energy (RE) sources. The application of the solar energy has been well-developed and used for electricity generation through Photovoltaic (PV) as the harvesting medium. PV cells convert heat from the sun directly into the electricity to power up the electric loads. Solar PV system is commonly built in a rural area where it cannot be powered up by the utility grid due to location constrains. In order to avoid the electricity fluctuation because of unsteady amount of solar radiation, PV solar hybrid is the efficient solution for rural electrifications. This paper presents a review on optimised Hybrid Solar-PV Diesel system configurations installed and used to power up off grid settlements at various locations worldwide.</p>

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Solar Photovoltaic Power Forecasting in Jordan using Artificial Neural Networks

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v8i1.pp497-504 ◽

2018 ◽

Vol 8 (1) ◽

pp. 497 ◽

Cited By ~ 3

Author(s):

Mohammad H. Alomari ◽

Jehad Adeeb ◽

Ola Younis

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Power Systems ◽

Output Power ◽

Solar Irradiance ◽

Machine Learning Algorithms ◽

Solar Photovoltaic ◽

Solar Pv ◽

Intensive Training ◽

Artificial Neural

In this paper, Artificial Neural Networks (ANNs) are used to study the correlations between solar irradiance and solar photovoltaic (PV) output power which can be used for the development of a real-time prediction model to predict the next day produced power. Solar irradiance records were measured by ASU weather station located on the campus of Applied Science Private University (ASU), Amman, Jordan and the solar PV power outputs were extracted from the installed 264KWp power plant at the university. Intensive training experiments were carried out on 19249 records of data to find the optimum NN configurations and the testing results show excellent overall performance in the prediction of next 24 hours output power in KW reaching a Root Mean Square Error (RMSE) value of 0.0721. This research shows that machine learning algorithms hold some promise for the prediction of power production based on various weather conditions and measures which help in the management of energy flows and the optimisation of integrating PV plants into power systems.

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Rural Electrification Using Diesel Power Systems in Fiji: A Review

ASME 1997 Turbo Asia Conference ◽

10.1115/97-aa-041 ◽

1997 ◽

Author(s):

Surendra Prasad

Keyword(s):

Developing Countries ◽

Natural Gas ◽

Power Systems ◽

Electricity Generation ◽

South Pacific ◽

Petroleum Products ◽

Energy Resources ◽

Energy Sources ◽

Rural Electrification ◽

Pacific Island

For small developing countries such as Fiji being devoid of conventional energy resources such as petroleum products, coal or natural gas, there is always heavy, and in many cases total, reliance on conventional energy sources for transportation, industries and for electricity generation. Fiji, like most of its South Pacific island neighbours, has relied very heavily on petroleum products for all of these, except for electricity generation since 1983, when hydro-electricity became the major source of electricity for the country.

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Modeling On-Site Combined Heat and Power Systems Coupled to Main Process Operation

Processes ◽

10.3390/pr7040218 ◽

2019 ◽

Vol 7 (4) ◽

pp. 218 ◽

Cited By ~ 2

Author(s):

Cristian Pablos ◽

Alejandro Merino ◽

Luis Felipe Acebes

Keyword(s):

Power Systems ◽

Electricity Generation ◽

Optimization Problem ◽

Combined Heat And Power ◽

Main Process ◽

Operational Cost ◽

System Behavior ◽

Dynamic Optimization Problem ◽

Process Operation ◽

Plant Configuration

Many production processes work with on-site Combined Heat and Power (CHP) systems to reduce their operational cost and improve their incomes by selling electricity to the external grid. Optimal management of these plants is key in order to take full advantage of the possibilities offered by the different electricity purchase or selling options. Traditionally, this problem is not considered for small cogeneration systems whose electricity generation cannot be decided independently from the main process production rate. In this work, a non-linear gray-box model is proposed in order to deal with this dynamic optimization problem in a simulated sugar factory. The validation shows that with only 52 equations, the whole system behavior is represented correctly and, due to its structure and small size, it can be adapted to any other production process working along a CHP with the same plant configuration.

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