The population, technology, and per capita energy consumption are all growing at an exponential rate, which is driving up energy demand. The load demand cannot be met by conventional power generation alone. Utilizing Renewable Energy Resources (RERs) to generate power is essential. In addition, the RERs are limitless and non-polluting. As a result, power systems based on renewable energy are garnering increased attention as a reliable and affordable power source. RER power generation can be used for both off-grid and grid-connected applications. However, the RERs are intermittent and not reliable, a single resource may not supply the required load demand of the remote rural area. For a reliable and cost-effective power supply, it is imperative to combine two or more RESs.
Today, the off-grid Integrated Hybrid Renewable Energy System (HRE) is considered to be an ambitious source of electrical power due to its technological, economic, and environmental benefits. Optimal integration of renewable energy resources has been found the most viable option for powering stand-alone remote rural areas. One can observe that the majority of research works conducted in the literature focuses on the techno-economic optimization of standalone HREs for isolated communities or regions. The majority of the HREs have been assessed under each dispatch strategy, as can be seen. Furthermore, a single type of battery is used in the majority of the studies. The literature did not take into consideration or report a performance comparison between two different batteries. Thus far, no comprehensive research on performance analysis based on dispatch strategy has been published. To obtain feasible and efficient RES, Demand Side Management (DSM) can be implemented.
The performance has not been evaluated under LF, CC, and CD strategies. The Demand Side Management (DSM)-based techno-economic analysis under Load Following (LF), Cycle Charging (CC), and Combined Dispatch (CD) strategies with Lead Acid (LA) and Lithium-Ion (Li-Ion) batteries is in consideration. In this work, peak shifting DSM methods and strategic conservation are taken into consideration. Sensitivity analysis was performed to assess how input parameters, including load demand, fuel cost, PV cost, and battery cost, affected NPC, COE, and Renewable Fraction (RF).
Motivation
The exponentially growing demand for electricity, environmental concerns, dwindling fossil fuel reserves, and their unpredictable price along with the provision of electricity to the off-grid rural areas have increased interest in RERs significantly. For off-grid rural areas, a stand-alone HRES is an alternative option – where the grid extension is not feasible. To supply power to these isolated, stand-alone areas, optimization of the HRES presents an efficient and economically viable option (Ramesh and Saini 2020). Nevertheless, by adding the DSM to the suggested HRES, the system’s dependability and running costs can be further increased (Rajanna and Saini 2016; Chauhan and Saini 2016). The authors’ motivation to present a study on DSM-based optimization to improve the suggested HRES’ performance stems from this.
Methodology
Demand Side Management or DSM, is the process of modifying load usage patterns and/or energy conservation. As seen in Figure 2, DSM can be carried out using a variety of techniques, including peak clipping, valley filling, peak shifting, strategic conservation, and strategic load growth. DSM planning offers the following advantages: lower energy and HRE system costs, better social and environmental outcomes, and increased system dependability.
The peak clipping, valley filling, and strategic load growth are not suitable for the off-grid locations due to most of the loads are priority loads. Peak clipping is the removal of loads during the peak periods of the HRES, which is practically difficult due to most of the loads during peak periods are priority loads. Valley filling is adding loads during off-peak periods, which is not considered in these off-grid locations where the loads are limited and are priority loads. Building the load throughout the day is known as ‘strategic load growth’, but this approach falls short of the study’s primary goal. As a result, it is determined that these techniques are inappropriate for the off-grid HRES utilized in remote area applications. The goal of strategic conservation is to use energy-efficient electrical appliances to lower the load throughout the day. The process of shifting shiftable peak period loads to off-peak periods is known as peak shifting. The off-grid HRES can readily use these two techniques. The methods of peak shifting and strategic conservation are applied in this viewpoint to evaluate the system.
Strategic conservation method
By substituting energy-efficient appliances for inefficient ones, the strategic conservation method essentially reduces load by lowering the ratings of various electrical appliances. According to the cost of the devices, this method takes into account three different ratings: Low Rating High Cost (LRHC), Medium Rating Medium Cost (MRMC), and High Rating Low Cost (HRLC).
Shiftable loads are the loads that are flexible to shift their operation from the pre-defined time slots to allowable time slots.
Objective function and constraints
Modelling of two important objective functions such as NPC and COE has been considered. Capacity shortage and battery storage limits have been considered as constraints.
Objective function
The NPC of the HRES is the present value of all the capital costs, O&M costs over the project lifetime minus the present value of all the income of the system obtain over the lifetime of the project.
Further, the COE also considered evaluating the economic feasibility of the system. It is defined as the average cost/kWh of electrical energy produced by the HRES.
Constraints
Optimization constraints for net present cost and cost of energy are as follows:
- Reliability criteria
- Storage battery limits
Technical and economic benefits
It is evident that by using energy-efficient devices in place of ordinary devices a huge number of components have been minimized. It is also found that the sizing of the system has been optimized with DSM as compared to that without DSM.
Environmental benefits
From the results, it is evident that under the DSM approach, all the pollutant emissions are reduced than the emissions produced by without DSM. The renewable fraction has been increased.
Conclusion
Using the DSM approach, a nearly 40% reduction is seen under all strategies taken into consideration, despite the nominal COE reduction. DSM implementation also results in a significant reduction in the number of PV arrays and batteries, which frees up a significant amount of space. In both NPC and COE, the discrepancy between the ideal and maximum values has been determined to be roughly 30%. Additionally, it is observed that DSM reduces pollutant emissions by 63%. The study’s conclusion indicates that investing in a hybrid renewable energy system over the long term makes sense for the area under consideration and could be applied to other off-grid locations.
Shibna Hussain is pursuing PhD in the Department of Renewable Energy, RTU Kota. She obtained the B.Tech. (Electronics and communication) & M.Tech. (Renewable Energy) degrees from Rajasthan Technical University, India. Her research area is Smart Grid Management systems, Solar-wind hybrid energy systems, and Demand-Side management systems.
