Abstract

A novel time–current-rate-based inverse characteristic curve for relays in a DC microgrid is proposed in this paper. Line current rise rate is used as actuating quantity, ensuring quick line fault clearing (relay operating time is in order of a few . The advantage of using line current rise rate as actuating quantity is that for a line short-circuit fault, it does not vary significantly for grid-connected and islanded modes of operation and varying network topologies of DC microgrid. Consequently, using the proposed characteristic, a single set of optimal relay settings is obtained using an optimization solver in MATLAB. The obtained settings ensure reliable and selective coordination between primary and backup relays for various pole-to-ground and pole-to-pole line faults under different operating conditions with multiple sources in two different 4-bus 400V low voltage DC microgrids. The maximum relay operating time for a high resistance fault with the proposed curve is for the first considered low voltage DC microgrid. Simulations in the Real Time Digital Simulator and comparisons with previous schemes (one comparison on the second considered DC microgrid), conventional standard inverse, and extremely inverse curves for DC microgrid protection indicate the effectiveness of the proposed scheme.

Introduction

The ease of integration of solar Photo-Voltaic (PV) and Battery Energy Storage Systems (BESSs) based renewable energy resources in a DC microgrid, compared to an AC microgrid, has led to the increased expansion and research interest of DC microgrids over AC microgrids [1], [2]. Also, DC microgrid can be a great way to power remote towns, shipboards, spaceships, and grids with sensitive loads, where the quality of power is crucial [3], [4]. However, the rate of rise of current is very high in a DC microgrid during a line fault due to the rapid discharge of the DC link capacitor and the associated low line impedance [5]. Hence, in general, the DC microgrid protection schemes follow a three-time frame based protection methodology in which the protection of the line, feeder, and the source should be done within a few milliseconds, and seconds, respectively [6]. Several DC Circuit Breakers (CBs) have been developed to support the quick isolation of lines during a fault in a DC microgrid, among which the solid-state CBs have a response time in the range of a few

Conclusion

This paper proposes a novel inverse time relay characteristic for the protection of DC microgrids against line faults using line current rise rate as an actuating quantity. It can coordinate relays in a DC microgrid with non-unit fault detection schemes or act as a backup scheme for relays with communication-based primary method. The relay coordination using the proposed characteristic is tested on a V LVDC microgrid. A single set of optimal relay settings ( and ) and a common set of values of and in (8) are obtained, considering all possible modes of operation, network configurations, and worst-case PG, PP LRFs and PG HRFs. Consequently, the proposed approach does not require an online update of and with a change in operating condition of DC microgrid. The efficacy of the proposed curve is validated with the obtained optimal unique relay settings for various PG, PP LRFs, PG HRFs for GC, islanded modes of operation, ring, radial network configurations, and intermittency of generation from renewable energy sources. Zero relay miscoordinations with a maximum primary relay operating time with the proposed curve are and for LRF and HRF faults, respectively, proving the effectiveness of the proposed technique in LVDC microgrid.

Further, the issues of using SI and EI curves to coordinate relays in a LVDC microgrid using line current and line current rise rate as actuating quantity and issues with using line current as actuating quantity in proposed scheme are discussed. It is observed that the conventional EI curve with line current rise rate may be used for relay coordination in DC microgrid. However, the high relay operating time (maximum primary relay operating time being ) may lead to prolonged line fault isolation. Additionally, the proposed scheme is fast and reliable, compared to EI curves, since the sum of primary relay operating times, considering all fault scenarios, is with the proposed curve, compared to the EI curve, which gives . The comparison with [16], [17] reveals the efficacy of the proposed scheme with the relay operating times in the proposed scheme being in the range of a few for line faults in LVDC microgrid.

Abstract

In recent years, floating photovoltaic (FPV) systems have emerged as a promising technology for generating renewable energy using the surface of water bodies such as reservoirs, lakes, and oceans. FPV systems offer several advantages over traditional land-based solar arrays, including increased land-use efficiency, reduced water evaporation, and improved cooling and maintenance. However, like all solar power systems, FPVs are subject to variability and intermittency due to changes in weather, seasons, and time of day. The environmental impact is discussed along with the deployment consideration and the feasibility for a better understanding of the system. Challenges associated with this are addressed by progressed research suggesting the integration of FPVs with various energy storage and hybrid systems. The most promising areas researched in this paper look at hybrid FPV hydropower plants (HPP), in parts of the world experiencing droughts HPP is not working to its optimum capacity. A review of available literature has been conducted on the topic of offshore and onshore floating solar electricity generation using floating solar photovoltaics to identify the challenges and opportunities presented. This work looks at a variety of other hybrid FPV energy sources with varying technology readiness levels. This paper concludes with the possibility of integrating different renewable technologies with existing FPVs and highlights the boons of doing so with some examples. Ultimately, current as well as future perspectives have been provided which consolidate the current research being done and give recommendations for future research work.

Introduction

One of the biggest challenges that is faced by the world is global warming due to which both humans and the planet are suffering as a whole, this is directly linked to the burning of the fossil fuels that we rely on to facilitate our daily life. The Intergovernmental Panel on Climate Change (IPCC) set out the impacts of global warming 1.5 °C above preindustrial levels [1]. We are not currently on course to limit 21st-century global warming to under 1.5 °C or even 2 °C [2]. Another key issue is the lack of clean electrification for a vast population which is hampering the development of the planet in tackling the climate change issue as many rely on the burning of fossil fuel for various daily requirements from generating electricity to cooking. It has been estimated that about 675 million people are still forced to live in the dark most of them belong to sub-Saharan Africa according to 2021 data. Though there has been an increase in the rate of access to electricity from 87% in 2015 to 91% in 2019, this has provided electricity to nearly 800 million people [3]. This is where solar PV can play a substantial role, solar PV has the benefit of being a renewable energy source, producing electricity from solar irradiance without any greenhouse emission [4].

However, there are challenges that must be addressed in order to fully realize the potential of solar energy and traditional photovoltaics [5]. These challenges include land usage, intermittency, storage, and integration into existing energy grids. One promising and upcoming alternative to traditional land-based photovoltaics is Floating Photovoltaics (FPV) or flotavoltaics [6]. The majority of renewable energy sources, such as biomass, solar, and others, take considerable footprint areas to generate electricity on a larger scale, which restricts the use of land for agriculture [[7], [8], [9]]. This sparked the discussion over whether land should be used for food production or energy production [10,11], encouraging research into offshore renewable technologies [12], and led to the creation of the floating photovoltaic (PV) array concept for the production of commercial electricity [13]. FPV technology is a concept in which solar panels are placed on platforms that float on water bodies such as natural lakes, man-made reservoirs, and the seas and oceans [14]. Fig. 1 shows a typical standalone floating photovoltaic system with all the components including an inverter, pontoons, solar panels, and cables connected to the grid.

Conclusion

This review article has examined the current state of research on the integration of floating photovoltaics with different storage and hybrid systems, including batteries, pumped hydro storage, compressed air energy storage, hydrogen storage and mixed energy storage options as well as the hybrid systems of FPV wind, FPV aquaculture, and FPV hydrogen production. The findings suggest that such systems have the potential to significantly increase the efficiency and reliability of renewable energy generation, as well as provide additional flexibility in managing electricity supply and demand.

FPV has many benefits over ground-mounted such as reduced land costs, increased efficiency, reduced soiling, reduced shading, reduced evaporation, and lower visual impact. Hybrid FPV has all of these benefits while being able to reduce its lifetime costs when paired with another technology a reduction in O&M costs, grid infrastructure and cable pooling. Overall, hybrid FPV has all the benefits of FPV plus reduced costs, while enhancing another technology. While FPV is set to rise this will initially be in land first with offshore following, the priority should be covering HPP first due to its complementary nature and benefits for both technologies. Countries, which have HPP reservoirs, should be looking into all the benefits of combining FPV with it. As FPV becomes more common it will be seen moving offshore, as the offshore wind increases it creates the opportunity for FPV to become a hybrid system.

Abstract

Solar energy forecasting has seen tremendous growth by using weather and photovoltaic (PV) parameters. This study presents new approach that predicts solar energy production by using the scheduled, unscheduled maintenance activities and weather data. The dataset is obtained from the 1MW solar power plant of PDEU (our university), which has 12 structured columns and 1 unstructured column with manual text entries about different scheduled and unscheduled maintenance activities, and weather conditions on the daily basis. The unstructured column is used to create new features by using Hash-Map, flag words and stop words. The solar power generation forecasting is formulated as a vector auto regression (VAR) optimization problem and total power generation forecasting is presented with the results of four different cases. The results have shown that the root mean square percentage error (RMSPE) in total power generation forecasting is less than 10% for different lag (p) values. The vector auto regression can forecast the unscheduled maintenance activities like Grid failure, Inverter Failure, scheduled maintenance activity like module cleaning, weather activity like cloudy along with total power generation forecasting for effective and efficient management of solar power plants. The power generation decay is different for all the PV sets which show the variations in the impacts of weather, aging and maintenance on the solar power plant. This research work has proven that the peaks of total power generation forecasting and prediction can be tracked in a better way by using daily unscheduled, scheduled maintenance activities and weather conditions.

Introduction

Solar energy forecasting is an emerging area over the last decade by using historical time series data collected through a weather station (such as weather variables wind speed and direction, solar irradiance, and temperature). The scheduled and unscheduled maintenance activities are carried out frequently for efficient and effective management of solar power plant. Another important parameter that contributes slowly but effectively is the age of the Solar PV module. The degradation of PV modules is further impacted by the conditions such as High temperature, solar cell shedding, discoloration, and delamination, etc. India has been endowed with non-depleting renewable energy resources like solar, hydro, geothermal, and wind and it is currently ranked no. 3rd globally in the renewable energy market. According to MNRE sources, about 5,000 trillion kWh of energy is falling on India’s land mass annually, with the majority receiving between 4 and 7 kWh per square meter per day. This is going to be one of the fastest-developing industries to boost rural electrification as well as the economy. Currently, there are more than 35 solar power plants in India. These plants are managed and operated by various government organizations. The operational expenditure of MW to GW solar photovoltaic power plants imposes a huge cost. Artificial Intelligence based solutions such as forecasting and recommendation-based systems can provide fruitful insights to reduce such expenditure.

Conclusions and Future Work

The maintenance activities like “grid failure”, “inverter failure”, “module cleaning” and the weather parameter “cloudy” have huge impact on the solar power generation forecasting and prediction. The optimum value of lag p=12 results in lowest RMSPE, RMSE and MAE for different cases. The error is reduced due to inclusion of duration for maintenance activities in this model for case 2. The VAR model used in this work is capable of forecasting all the four features as well as power generation target variable simultaneously. The predicted power generation is able to follow the trends of original power generation when the thresholding is applied to the predicted values of maintenance features (activities). The results have shown that the root mean square percentage error (RMSPE) in total power generation forecasting is less than 10% for different lag (p) values for all cases. The vector auto regression can forecast the unscheduled maintenance activities like Grid failure, Inverter Failure, scheduled maintenance activity like module cleaning, weather activity like cloudy along with total power generation forecasting which result in effective and efficient management of solar power plant. The power generation decay is different for all the PV sets which show the variation in the impacts of weather, aging and maintenance on the solar power plant. The effects of aging, dust and other environmental factors can be considered in the model as a future scope to improve the solar power generation forecasting and prediction.

Abstract

     The modern active distribution systems necessitate integrating storage systems, thereby facilitating the large-scale proliferation of photovoltaic (PV) energy resources. This further calls for the optimal planning of energy storage systems, satisfying all the operational and economic constraints. This article describes an exhaustive storage integration method, deeming the life cycle of the battery energy storage, the uncertainty of load and PV output, and the islanded mode of operation of the system. A two-stage mixed-integer linear programming problem is formulated that determines the capacity and the number of discharge cycles of the batteries in the first stage. The lifetime of the battery based on the partial depth of discharge is analyzed in the second stage. Furthermore, the uncertainty and variability of PV and demand are taken into account through probabilistic analysis and time-period clustering. The method is validated on a standard 33-bus radial distribution network for the allocation of distributed lithium-ion batteries. Also, the method’s scalability is validated on a practical Indian distribution network and a 141-bus distribution network of metropolitan area of Caracas with distributed PV installations on various nodes.

Introduction

     S MART grid is a gratuity to the consumers and the stakeholders involved in the electric grid’s generation, transmission, and distribution sections. It includes the complete modernization of the power system with smart meters, automation devices, intelligent monitoring, demand-side management, and self-healing capability schemes. Along with these activities, generation units are set up in the distribution section, i.e., nearer to the consumer premises, to reduce the transmission losses. This shift of the electric grid from a passive network to a bidirectional active network is due to the small generators being set up in the distribution grid known as distributed/decentralized generation. These distributed generators (DGs) mainly generate energy using renewable energy resources, such as photovoltaic (PV), wind, biomass, tidal, etc., as they are clean sources of energy and promote sustainable development. However, the intermittent nature and excess penetration of these resources pose problems, such as reverse power flow, voltage fluctuations, increase in losses, harmonic distortion, and instantaneous matching of demand and supply [1], [2]. Although integrating storage systems in the distribution network can help alleviate the aforementioned problems if allocated optimally. Also, India’s target of 40-GW PV rooftop installations by the year 2022 and the declining cost of batteries will provide a fillip to the installation of energy storage systems (ESSs) [3]. Therefore, an ESS can be seen as a game changer in the ever-changing power system paradigm and can serve multiple ranges of benefits. To achieve these benefits, methods for optimal sizing, allocation, and operation of ESSs are required

Conclusion

     The integration of renewable energy resources necessitates the allocation of distributed energy storage to mitigate voltage deviation and defer distribution upgrades. This article illustrated a two-stage procedure for integrating lithium-ion batteries in a PVpenetrated active distribution network. The planning methodology considered an ac-OPF model with the uncertainty of PV and demand to determine the batteries’ accurate size. Moreover, the reverse power flow due to excess PV penetration was utilized and the voltage was within limits after the integration of batteries in the system. The battery’s life cycle was examined in the second stage with the partial cycle of discharge and complete discharge cycles. For lithium-ion batteries, partial cycle discharging was fine as there was no memory effect, and the battery does not need full discharges periodically. From the results, it was illustrated that with the partial cycle of discharge, the battery will last longer. Moreover, the method used here was the mathematical programming, which provides a robust solution, but may require significant computation time for large and complex problems. Also, the maximum discharging capacity of the battery gradually declined with its cycles, which can be kept as a future research direction. Furthermore, to enhance the stability and cost-effectiveness, a smart charging and discharging operation can be added to the problem. In addition, different types of DGs, such as wind, micro-turbines, and fuel cells, can be considered an extension to the OPF formulation.

Abstract

Introduction

Review of literature on the current understanding and ongoing debate of smart cities

Method and data

Results and discussion

Conclusion

Declarations

References

Abstract

     Smart city is one of the fastest growing socio-economic and scientific initiative in the world. Still, it is only in principle and a mere blueprint for many developing countries. This study reviews literature on smart city in Nigeria and developing countries. Our aim is to explore ways to improve the quality of Nigeria’s urban areas, based on recent research on the concept of smart city and its implementation. We summarise key research findings, and gather evidence that shows what composition of urban governance, social, economic, and environmental factors, that would influence actualising a smart city in Nigeria. Although knowledge has grown tremendously in the current literature on the definition, significance, governance, policy, and implementation of a smart city, its significance in Nigeria and other developing countries is supplemental. As an environmentally friendly initiative, a smart city will support urban sustainability and livelihood in Nigeria in a myriad of ways—environmental protection, and mainstream urban services, including public security and safety, access to quality health care, efficient power supply, clean water distribution, assets management, smart transportation, etc. However, despite her unique traditional urban agglomeration trends, Nigeria is unambitious and constrained towards actualising a smart city. Actualising a smart city in Nigeria and other developing countries would require radical and ambitious policies on development of human and infrastructural capacity, as well as institutional reinforcement. This highlights the need for more research, of which we are optimistic that the findings of this research will support with its new insight and clear guidelines.

Introduction

     A smart city is modern architectural philosophy, focusing on the use of information and communication technology (ICT) to solve problems endogenous to the city, and to power vital activities. It represents a major transformation from the traditional urban agglomeration to a twenty-frst-century metropolis, which advances city functions, promotes economic growth, and improves the quality of life for citizens (Bakıcı et al., 2013). One obvious beneft of a smart city is the level of government response to the needs and well-being of citizens through positive interaction between the government and citizens, aided by technology-driven policies and services. When we look at some of the smart cities in the world today for example Singapore, San-Diego, Barcelona, and Hong Kong, we could fnd that smartness of cities creates applications and urban services that combine technology and promotes the development of policies and practices to address the social, economic, and environmental challenges facing today’s urban areas (Su et al., 2011).

Conclusion

     A smart city represents a shift both in mindset and architectural framework from the traditional agglomeration of roads, public utilities, and amenities to a modern system that uses big data and ICT to enhance the livelihood of the citizens and government policy and program of service delivery within the city. This is a major incentive for research and policy towards the sustainable development of cities. There is also an opportunity to tackle urban scenic distortion and to provide a more dynamic and diversifed science to address common issues – such as climate change, increasing frequency, and severity of crimes, social disorders, and disasters – arising from urban agglomerations and the burgeoning human population in cities.

For the developing countries (DCs) such as Nigeria – the focus of this study – a smart city’s conceptualization is slightly skewed because of the vagaries of challenges to its actualization. Thus, the idea of a smart city is still more utopian than realistic. However, the future of the DCs is arguably a smart city because of the complex urbanizations and predictions that places within the DCs will contribute signifcantly to the global urban populations, which is estimated at 90% of the global population by 2050. Therefore, to address the attendant problems that prevail presently in the DCs’ urban areas – which include environmental, economic, and human development issues – a smart city is a potent option.

Highlights

Abstract

Keywords

Abbreviations

1. Introduction

2. Microgrid model

3. Description of the proposed multi-functional algorithm

4. Simulation results

5. Comparison with other existing techniques

6. Conclusion

CRediT authorship contribution statement

Declaration of Competing Interest

References

Abstract

A large part of the current microgrids (MGs) operate in grid-connected mode and act as slaves following the voltage and frequency dictated by the main grid. Therefore, these MGs are not expected to be operated in parallel as islands. Hence, according to the IEEE 1457-2018 standard, the power generation units in these grid-connected MGs (GCMGs) have to be disconnected in less than 2 s if islanding occurs. On the contrary, if the islanding operation (IO) does not occur, these MGs exchange power with the electrical grid. This paper explores the feasibility of a multi-functional algorithm (MA) for these GCMGs in an attempt to address three tasks simultaneously; (i) power sharing, (ii) voltage support and, (iii) islanding detection (ID). The MG object of study comprises an electronically interfaced photovoltaic (PV) unit supplemented by a battery energy storage system (BESS) equipped in combination with a bidirectional charger. The model of the GCMG has been implemented in MATLAB, where an extensive set of simulations has been performed. The results demonstrate the effectiveness and benefits of the proposed MA, which fulfils several functions all at once.

1. Introduction

Conceptually, MGs are self-sufficient entities formed by an aggregation of generation units, energy storage systems and a set of controllable loads [1]. These MGs can be either connected to the grid (i.e., the abovementioned GCMGs) or operating in stand-alone mode [2]. Even though these GCMGs can be powered by different technologies (Wind, PV, mini-hydro, etc.), rooftop PV units are becoming very popular in residential and industrial applications due to their multiple benefits. Even though these GCMGs require the main grid, if both generation and storage devices are properly coordinated and sized, the amount of energy exchanged with the grid can be significantly reduced. Therefore, these GCMGs are becoming less grid-dependents in terms of exchanged energy.

In this regard, multi-functional algorithms are gaining momentum in MGs. For example, a fully distributed MA control has been proposed in [3], while references [4], [5], [6] used MAs for optimal MG management. If the peak power is shaved and the energy supplied by the grid is curtailed, this will imply a reduction in the electricity cost [7], [8]. Undoubtedly, this aspect is crucial for these MGs; for instance, see the techno-economic analysis carried out in [9].

Albeit these MGs offer several advantages for the users and the DNs (e.g., losses reduction and voltage support) [10], [11], some issues may occur due to their inherent intermittency. In particular, voltage regulation is among the most concerning issues for the distributor operators (DSOs). Although these PV-based distributed generations (DGs) are commonly operated at unity power factor, some grid codes require reactive power support by the voltage source converters (VSCs). Therefore, optimal Volt/VAR strategies have been investigated for such purposes, see [12]. Presently, the electronically-interfaced grid-connected generation units which provide grid support are also known as grid-following VSCs, see [13].