Off-grid Power System Research Articles

Hydrogen storage integrated in off-grid power systems: a case study

This paper investigates the feasibility and benefits of integrating hydrogen storage systems into off-grid power systems. As a case study, a stand-alone microgrid located on a small island in southeastern Sardinia (Italy) and already equipped with a photovoltaic (PV) system coupled with batteries is chosen.To evaluate the integration benefits of the two storage systems (hydrogen and batteries) and the optimal sizing of the hydrogen storage section, a parametric analysis with a simulation model implemented in the MATLAB environment has been carried out. Results show that the optimal integration between the two storage systems is found by imposing a share of the batteries (18 kWh, 50% of the overall battery capacity) to exclusively supply the load demand (called battery energy buffer). In these conditions, an almost 100% self-sufficiency of the microgrid can be achieved by a hydrogen generator with the lowest size considered (2.4 kW), a hydrogen storage volume of 10 m3 and a fuel cell, mainly able to completely cover the night loads, of 1.5 kW. This sizing leads to a Levelized Cost of Electricity (LCOE) for the hydrogen section of about 10.5 €/kWh.

Design, modeling, and simulation of a PV/diesel/battery hybrid energy system for an off-grid hospital in Ethiopia

In the pursuit of sustainable energy solutions, off-grid hybrid systems have emerged as a promising avenue, catering to the electrification needs of rural areas. These systems encompass a multifaceted approach, addressing concerns of reliability, sustainability, and environmental preservation. Leveraging advanced tools such as HOMER modeling, the design and simulation of hybrid off-grid systems, alongside the evaluation of existing diesel generator (DG) power supply, have become imperative. This paper embarks on a comprehensive exploration with the overarching objective of designing, modeling, and simulating an off-grid power system tailored for the Shinshicho Primary Hospital. Nestled in the heart of Shinshicho Town within the Kembata Tembaro Zone of Ethiopia, this healthcare facility stands as a focal point for community well-being. The proposed hybrid system integrates solar PV, diesel generators, and battery storage, offering a robust and resilient energy solution. Throughout the optimization process, a primary load demand of 276 kgwatt-hours per day and a peak load of 40 kW were pivotal considerations. The financial cost of this hybrid system results in an initial capital requirement of $160,500, complemented by operational and maintenance costs amounting to $14,824. Over the projected 20-year lifespan, the total net present cost (NPC) is estimated at $216,155. With these economic parameters in mind, the cost-effectiveness of the selected hybrid system is underscored by a cost of energy (CEO) of 0.187 dollars per kilowatt-hour. This metric not only highlights the economic viability of the proposed solution but also positions it as a sustainable and financially prudent choice for meeting the energy needs of Shinshicho Primary Hospital.

Designing off-grid renewable energy systems for reliable and resilient operation under stochastic power supply outages

The power supply from solar and wind generators is not only inherently variable but also prone to failure due to rare-weather related events, i.e., hailstorms, icing. Current system sizing strategies often consider system reliability or resilience but rarely consider them simultaneously. Here, we proposed a sizing approach for an off-grid power system to supply a minimum power threshold (Lth) during power disruption events. The Lth concept ensures blackout avoidance and enough dispatchable stored energy during power outages. We developed several scenarios with 4- to 24-hour simulated outage events occurring multiple times per year. After sizing a system, designs are tested by simulating the systems’ operation based on data containing stochastic outage events. The resulting lost load is recorded to assess system reliability and resilience. Results showed that, regardless of outage frequency, total annual stochastic outage durations up to 32 h did not affect the optimal capacities of system components while ensuring the same reliability level. However, system capacities increased by up to 90% when the annual outage duration increased to 144 h. Meanwhile, introducing a minimum power threshold, Lth = 0.97, further increased the renewables generation and storage capacity up to 50% and 7%, respectively. Systems’ resilience tests showed an 80% chance of a system designed with the Lth approach to withstand the prolonged stochastic power disruptions, while this value is only 25% for the systems designed using the conventional approach.

Perspective on perovskite indoor photovoltaics

The concept of the Internet of Things (IoT) is a future development opportunity for mankind, which is a system that realize the interaction of various electronic devices through wireless communication. With the rise and development of this concept, the energy demand gap of self-powered equipment in IoT has emerged. The construction of an off-grid power system will make the wireless network of IoT easy to integrate and meet the higher requirements of power supply equipment in terms of size, weight, energy-consumption, and cost. Indoor photovoltaics (IPVs) can provide stable and long-term power guarantee by collecting indoor light, which are perfectly matched with IoT. Photovoltaic cells based on a-silicon, dye, organic compounds, and halide perovskite have been proved to be suitable for IPVs. Among them, perovskite indoor photovoltaics (PIPVs) have attracted much attention due to its advantages of tunable bandgap, high output voltage, flexible preparation, and low cost. In addition, the indoor stability and toxicity of PIPVs are also discussed in this Perspective.

A Simulation Study of the Resiliency of Mobile Energy Storage Networks

Resilience is regarded as an essential design objective of a wide range of systems in modern society. This work is based on a vision that networks of mobile energy storage systems could provide an alternative off-grid power system design for rural and underdeveloped regions. To evaluate the resiliency of networked energy storage systems under overload failure, a model of concurrent cascading failure and healing processes is developed and demonstrated. Two resilience metrics are used to evaluate the resilience of a real-world network, namely the recovery level at a specified time and the recovery time. The simulations generate system trajectories at each time step. We explore the dependence of the system behavior on different model parameters that capture key recovery strategies. The success probability of the recovery of a failed node needs to be high enough for the network to restore its original functionality. Similarly, the increase in recovery budget parameter also leads to faster and higher recovery levels. However, in most cases, there appears to be upper limits for both parameters, beyond which any further increase could not improve the recovery performance. There is an optimum portion of the loads of the active neighboring nodes that will be carried by the newly recovered node that results in the shortest recovery times or highest recovery levels. Our work sheds light on how to enhance networked systems resiliency by considering the optimization of various model parameters.

Intelligent Optimized Voltage Control for Hybrid Off-Grid Power Systems

Hybrid off-grid power systems with different renewable and non-renewable energy sources, such as wind, photovoltaics, and diesel generation, have a wide application scope in regions where grid extension is not possible. To supply quality power, hybrid off-grid power systems need proper reactive power management to deal with randomly changing load and supply. In particular, to realize dependable and quality power supply, hybrid off-grid power systems require suitable and efficient control techniques. A properly tuned controller of reactive power sources is crucial to maintain a prescribed voltage profile. Computational intelligence techniques such as particle swarm optimization can provide desired and acceptable solutions for optimization problems. In this study, we applied computational intelligent techniques for optimal control of reactive power sources, such as photovoltaic inverters and automatic voltage regulators for synchronous generators in diesel engines, to investigate dynamic voltage profile stability through reactive power management.

Reserve Provision in the Optimal Planning of Off-Grid Power Systems: Impact of Storage and Renewable Energy

Reserve Provision in the Optimal Planning of Off-Grid Power Systems: Impact of Storage and Renewable Energy

Decentralized DC solar power system for remote areas

The emission of CO2 by industries and automobiles creates a problem like global warming. Especially in areas nearby mega-cities, the concentration of CO2 is increasing by a considerable level. The existing setup of electricity generation is centralized which generates electricity centrally in one place and it is transmitted everywhere. Decentralized DC solar power is the newest innovation in the field of renewable energy especially in solar energy to give more efficiency for casual and residentially applications. By utilizing the series–parallel combination of solar panels we can make our off-grid power system. This off-grid power system is the best power system for those families whose power requirements are less and some villages which are apart from centralized power communities. One approach is to generate power at a place where we need it. As we know that solar panel generates DC Voltage and we can develop a 12 V or 24 V DC system, which does not require conversion from AC to DC. This paper is mainly for Off-grid power generation and awareness for future research in the field of renewable, pure, and Off-grid DC solar power.

Forecasting of Power Quality Parameters Based on Meteorological Data in Small-Scale Household Off-Grid Systems

Off-grid power systems are often used to supply electricity to remote households, cottages, or small industries, comprising small renewable energy systems, typically a photovoltaic plant whose energy supply is stochastic in nature, without electricity distributions. This approach is economically viable and conforms to the requirements of the European Green Deal and the Fit for 55 package. Furthermore, these systems are associated with a lower short circuit power as compared with distribution grid traditional power plants. The power quality parameters (PQPs) of such small-scale off-grid systems are largely determined by the inverter’s ability to handle the impact of a device; however, this makes it difficult to accurately forecast the PQPs. To address this issue, this work compared prediction models for the PQPs as a function of the meteorological conditions regarding the off-grid systems for small-scale households in Central Europe. To this end, seven models—the artificial neural network (ANN), linear regression (LR), interaction linear regression (ILR), quadratic linear regression (QLR), pure quadratic linear regression (PQLR), the bagging decision tree (DT), and the boosting DT—were considered for forecasting four PQPs: frequency, the amplitude of the voltage, total harmonic distortion of the voltage (THDu), and current (THDi). The computation times of these forecasting models and their accuracies were also compared. Each forecasting model was used to forecast the PQPs for three sunny days in August. As a result of the study, the most accurate methods for forecasting are DTs. The ANN requires the longest computational time, and conversely, the LR takes the shortest computational time. Notably, this work aimed to predict poor PQPs that could cause all the equipment in off-grid systems to respond in advance to disturbances. This study is expected to be beneficial for the off-grid systems of small households and the substations included in existing smart grids.

Application of electromagnetic continuous variable transmission in hydraulic turbines to increase stability of an off-grid power system

In the context of climate change, today's adoption of renewable energy sources in isolated power systems is becoming an increasingly more significant issue. Micro-hydro power plants are emerging as a mature balancing technology and a great alternative to large hydropower plants as they do not encounter population displacement and many environmental problems. It is worth noting that hydroelectric power plants combined with various sources require improvement in control laws and algorithms. Strong disturbing impacts, namely transient processes, in an isolated electric power system cause an appreciable decrease in dynamic stability. This paper presents research conducted to ensure synchronous parallel operation of permanent-magnet generators used in micro-hydroelectric power plants in an isolated power system with a controllable flexible coupling between turbine and generator. The importance of this study lies in the issue of electromechanical compatibility to be achieved in parallel operation of generators that have different parameters of time constant of mechanical inertia of rotors of electrical machines. This paper provides an overview of possible solutions to the identified problem. A concept based on a controllable flexible coupling between generator and turbine is proposed as a promising avenue to solve this problem. The mathematical models are presented along with the laws and algorithms developed for automatic control of the generator speed. Oscillograms of simulation and physical modeling presented in the final part of the paper show parallel operation of permanent-magnet synchronous generators in an isolated electric power system for various electrical distances of three-phase short circuit points.

Analysis of the frequency deviation in off-grid power system of oil field

The paper represents the results of field measurements in the off-grid power system of oil field including diesel power plant, which supplies drilling rig system BU-4500/270 EK-BM. The data has been processed using the instantaneous power theory by Hirofumi Akagi. The active power load diagram of diesel power plant and power system frequency schedule have been obtained for hole drilling technological process of drilling rig. Abrupt load changes during drilling lead to large frequency deviations, which do not allow using gas piston generators in power system of oil field without revision of number and rated power of generators or using electrical energy storage system.

Impact of Capacity Shortage on The Feasibility of PV-Wind Hybrid Systems in Africa

Reliable optimization of renewable energy system is the one that balances between electrical sizing of the system components in order to satisfy the load and the cost of that system. This techno-economic optimization can be assured by HOMER software through some sensitivity parameters such as capacity shortage. For Saharan villages in Africa, it is required to install off-grid power systems with low cost. To fulfill this requirement, is it necessary to avoid the over-sizing of system due to high and short peaks of load, so the optimization of PV-wind hybrid system on this article is done with sensitivity analysis of the system for different capacity shortage rates. The only rates that do not exceed the mean values of electrical outage of Algeria are 0 % and 0.5 %, and HOMER had favorited the optimal system with 0.5 % of capacity shortage due to the 18 % gain in total cost of system and the energy cost. The results achieved on this article encourage on techno-economical optimizing PV-wind hybrid systems with acceptable capacity shortage and electrical outage rates for a better economic feasibility in Saharan villages.

A new solar energy-based system integrated with hydrogen storage and heat recovery for sustainable community

This study presents a unique solar energy-based system using green hydrogen as energy storage option developed to meet the electricity, heat and cooling demands for a potentially sustainable community. The energy and exergy analyses are implemented to analyse and assess the proposed system and its performance. In this regard, a community is identified in the Southern Ontario in Canada with 1500 residential units. The hydrogen produced in the system is stored in the underwater balloons, called “the underwater hydrogen balloon”. The heat recovery from the sewage is included in the system in order to enhance the performance of the air conditioners and heat pumps. The results of the present study indicate that in order to dedicate the off-grid power system, 288,000 m2 of PV panels is required in the month of December when the lowest solar radiation is obtained. On the hand, it is possible to provide 65,474 kWh of energy can be provide the grid with that much of PV panel in the month of June. Both energy and exergy efficiency values tend to decrease with the increasing both PV panel area and solar radiation due to increasing solar energy input against to constant demand items. The heat recovery from the sewage helps increase the performance of the air contioning system with heat pump by about 33%.

Analysis and techno-economic assessment of renewable hydrogen production and blending into natural gas for better sustainability

In this study, comprehensive thermodynamic analysis and techno-economic assessment studies of the renewable hydrogen production and its blending with natural gas in the existing pipelines are performed. Solar and wind energy-based on-grid and off-grid power systems are designed and compared in energy, exergy, and cost. Solar PV panels and wind turbines are particularly considered for electricity and hydrogen production for residential applications in an environmentally benign way. Fuel cell units are included to supply continuous electricity in the off-grid system. Here, the heat required for a community consisting of 100 houses is provided by hydrogen and natural gas mixture as a more environmentally benign fuel. The costs of capital, fuel, operation, and maintenance are calculated and evaluated in detail. The total net present costs are calculated as $6.95 million and $2.47 million for the off-grid and on-grid power systems, respectively. For the off-grid system, energy and exergy efficiencies are calculated as 32.64% and 40.73%, respectively. Finally, the energy and exergy efficiencies of the on-grid system are determined as 26.58% and 35.25%, respectively.

Improving dynamic response of PEMFC using SMES and bidirectional DC/DC converter

Nowadays, the use of renewable energy systems, especially fuel cells, has become very widespread in various applications. Some of their most important applications include using electric vehicles and local off-grid power systems. One of the challenges with the fuel cells is the slow dynamic response to load power changes. In fact, when the load power changes suddenly, the fuel cell supplies it with a time delay, and this can cause disturbances in the performance of the loads. In this research, a new control method for a bidirectional DC/DC converter equipped with a superconducting magnetic energy storage system (SMES) is presented to exchange the stored energy with the proton-exchange membrane fuel cell (PEMFC) in a high response dynamic to overcome the slow dynamic of the fuel cell feeding load. The appropriate validation of the proposed system is verified by simulation in the MATLAB SIMULINK environment. The results illustrate that the slow-response of PEMFC is improved appropriately.

Technical and Economical Investigation of a Centralized and Decentralized Hybrid Renewable Energy System in Cadaado, Somalia

The purpose of this paper is to investigate the feasibility of a wind–solar hybrid system on and off-grid power system for electricity generation at a selected location in Somalia using the renewable energy optimization software HOMER. The simulation model was successfully applied to find the best simulation results based on the energy-efficient system for the specific load. The technical and economic performance of an on-grid and stand-alone combination of 25 kW wind power and 60 kW solar photovoltaic was investigated. Since the city of Cadaado has not yet installed its own standard modern electricity grid and due to the great need to reduce energy costs in Somalia, a feasibility study was conducted on how to supply electricity to a sampled residential consumption. Based on the basic characteristics of renewable energy sources in central Somalia, the on-grid wind and solar photovoltaic systems could be economically feasible.

A Short Assessment of Renewable Energy for Optimal Sizing of 100% Renewable Energy Based Microgrids in Remote Islands of Developing Countries: A Case Study in Bangladesh

This study explores Bangladesh’s present energy condition, renewable energy (RE) possibilities and designs an optimal 100% RE-based off-grid power system for St. Martin’s Island, Bangladesh. The optimal size of a hybrid renewable microgrid based on photovoltaic (PV) cells, a battery energy storage system (BESS), fuel cells (FC), and an electrolysis plant (EP) is proposed. Advanced direct load control (ADLC) and rooftop PV meet the energy demand at the lowest cost, and profits are maximized by selling chemical products produced by seawater electrolysis. Four cases are explored with the mixed-integer linear programming (MILP) optimization technique using MATLAB® software to demonstrate the efficacy of the suggested power system. The system cost in case 1 is lower than in the other cases, but there is no chance of profiting. Cases 2, 3, and 4 have greater installation costs, which may be repaid in 8.17, 7.72, and 8.01 years, respectively, by the profits. Though the revenue in case 3 is 6.23% higher than in case 2 and and 3.85% higher than in case 4, case 4 is considered the most reliable power system, as it can meet the energy demand at the lowest cost while increasing profits and not putting a burden on customers.

Jointly Learning Environments and Control Policies with Projected Stochastic Gradient Ascent

We consider the joint design and control of discrete-time stochastic dynamical systems over a finite time horizon. We formulate the problem as a multi-step optimization problem under uncertainty seeking to identify a system design and a control policy that jointly maximize the expected sum of rewards collected over the time horizon considered. The transition function, the reward function and the policy are all parametrized, assumed known and differentiable with respect to their parameters. We then introduce a deep reinforcement learning algorithm combining policy gradient methods with model-based optimization techniques to solve this problem. In essence, our algorithm iteratively approximates the gradient of the expected return via Monte-Carlo sampling and automatic differentiation and takes projected gradient ascent steps in the space of environment and policy parameters. This algorithm is referred to as Direct Environment and Policy Search (DEPS). We assess the performance of our algorithm in three environments concerned with the design and control of a mass-spring-damper system, a small-scale off-grid power system and a drone, respectively. In addition, our algorithm is benchmarked against a state-of-the-art deep reinforcement learning algorithm used to tackle joint design and control problems. We show that DEPS performs at least as well or better in all three environments, consistently yielding solutions with higher returns in fewer iterations. Finally, solutions produced by our algorithm are also compared with solutions produced by an algorithm that does not jointly optimize environment and policy parameters, highlighting the fact that higher returns can be achieved when joint optimization is performed.

Designing an energy management system for household consumptions with an off-grid hybrid power system

<abstract> <p>This paper analyzes the effect of meteorological variables such as solar irradiance and ambient temperature in addition to cultural factors such as consumer behavior levels on energy consumption in buildings. Reducing demand peaks to achieve a stable daily load and hence lowering electricity bills is the goal of this work. Renewable generation sources, including wind and Photovoltaics systems (PV) as well as battery storage are integrated to supply the managed home load. The simulation model was conducted using Matlab R2019b on a personal laptop with an Intel Core i7 with 16 GB memory. The model considered two seasonal scenarios (summer and winter) to account for the variable available energy sources and end-user electric demand which is classified into three demand periods, peak-demand, mid-demand, and low-demand, to evaluate the modeled supply-demand management strategy. The obtained results showed that the surrounding temperature and the number of family members significantly impact the rate of electricity consumption. The study was designed to optimize and manage electricity consumption in a building fed by a standalone hybrid energy system.</p> </abstract>

Two-stage framework for optimizing the operation of remote off-grid power systems under uncertainties

With the precipitated integration of intermittent renewable sources, operation optimization employed with uncertainty management strategies is imperative to ensure a reliable, cost-effective, and secure energy supply for the remote off-grid power systems. This paper presents a two-stage operation optimization process embedded in a model predictive control framework. The first stage decision variables are derived in a deterministic optimization framework to achieve minimum operational costs and emissions. The second stage uses a stochastic optimization framework to refine the first stage decision variables to achieve a feasible operation considering several candidate scenarios in a computationally inexpensive manner. Several measures are integrated to the proposed framework in order to address the operational requirements pertaining to remote off-grid power systems. The effectiveness of the proposed framework is demonstrated through numerical experiments for an isolated remote power system in Northern Canada for both summer and winter seasons. Quality of the obtained results as well as the computation efficiency of the overall framework has been verified compared to the existing energy management techniques. The overall result confirms the applicability of the proposed method in achieving a cost-effective and environmentally friendly operational trajectory while effectively accounting for the underlying uncertainties with a reduced computational burden.