Feed-in Research Articles

A refined method for optimising inverter loading ratio in utility-scale photovoltaic power plant

This paper proposes a novel approach for designing the inverter loading ratio (ILR) for utility-scale PV systems. As the first of its kind, a deterministic approach is proposed for dealing with such a design issue. The design objective is to maximise the economic reliability of the photovoltaic (PV) Plants. The problem is reformulated using a linear programming (LP) technique. The proposed solution allows dealing with each system individually and requires only the information of the DC/AC power conversion unit system. The results are tailored for utility-scale PV systems but can also be easily revamped for residential and private/industrial installations. The results were validated using a real-world case study of a utility-scale PV power plant in Ireland, operating under the Renewable Electricity Support Scheme (REFIT) feed-in tariff. These results were compared with the design method from the commercial PVsys software. In the proposed case study, reducing the ILR value from 1.4656 (as designed by PVsys) to 1.4528 led to an increase in annual profit annuities, demonstrating the effectiveness of the proposed approach.

Modeling of methane emissions from waste disposal sites at selected Egyptian governorates and potential energy production from waste-to-energy projects

Waste and energy sectors have significant contributions to the greenhouse gas (GHG) emissions caused primarily by the population expansion. Waste-to-Energy (WtE) is introduced to address the issue raised by both sectors simultaneously through utilization of the potential energy stored in municipal solid waste (MSW) as well as offsetting GHG emissions. Limited research have been conducted in Egypt to assess the current situation of MSW management and associated methane emissions. The current study focused on estimating the baseline methane emissions for six Egyptian governorates and determining the energy production potential from WtE projects. To achieve this aim, three scenarios have been assessed: Baseline, Landfill Gas to Energy (LFGE), and Incineration scenarios. Key results revealed that a total of 3.7 million tonnes of methane would be emitted from all studied governorates generated over 50 years. Incineration also found to be more favorable in all governorates in terms of energy production, quantity of avoided GHG emissions, and in terms of economic viability over LFGE. Implementing incineration in all governorates would generate about 5.6 TWh energy annually and could avoid about 5 Mt CO2 eq annually in comparison to LFGE that would generate about 0.6 TWh annually and could avoid about 2.5 Mt CO2 eq annually. In terms of economic viability of WtE projects, while they were generally not economically viable under the assumptions made in the current study, incineration technology deemed promising, but policy adjustments, such as competitive Feed-in Tariff (FiT) rates and the inclusion of gate fees, are necessary. Specific minimum gate fees and FiT were identified for each governorate, providing essential guidance for decision makers to ensure the viability of WtE implementation. This study would support the decision makers in assessing technically and financially feasible options for WtE technologies in the selected governorates.

Integration of Renewable Energy Solutions in Agricultural Operations

The integration of renewable energy solutions in agricultural operations presents a transformative approach to enhancing sustainability, reducing greenhouse gas emissions, and improving the economic viability of farming practices and explores the various renewable energy technologies applicable to agriculture, including solar, wind, biomass, and biogas energy solutions. Each technology is examined for its specific applications within the agricultural sector, highlighting its potential benefits and the challenges faced in implementation. Solar energy, through photovoltaic and thermal systems, offers significant potential for powering irrigation, greenhouse operations, and processing facilities, thereby reducing reliance on fossil fuels and grid electricity. Wind energy, with its ability to generate electricity through turbines, is particularly valuable in regions with consistent wind patterns, contributing to both onfarm energy needs and grid supply. Biomass energy, utilizing agricultural residues and dedicated bioenergy crops, provides a sustainable solution for heating and energy generation, while also addressing waste management challenges. Biogas production, through anaerobic digestion of organic waste, presents a dual benefit of generating renewable energy and improving nutrient recycling in farming systems. Government subsidies, feedin tariffs, research funding, and technical support play pivotal roles in encouraging farmers to transition to renewable energy sources. Case studies from various regions illustrate the practical implementation of these technologies, demonstrating their impact on enhancing agricultural productivity, reducing environmental footprints, and fostering energy independence, including policymakers, researchers, and farmers, about the opportunities and challenges in adopting sustainable energy practices. The findings underscore the importance of continued innovation, supportive policies, and collaborative efforts to achieve a resilient and sustainable agricultural sector.

On-Grid Hybrid Wind–Solar Power Plants in Ukraine’s Residential Sector: Economic Justification of Installation Under Different Support Schemes

On-grid hybrid wind–solar systems are one of the best sustainable solutions for developing distributed generation, as they can provide a stable and reliable electricity supply, effectively using the potential of the two most common renewable energy resources. In Ukraine, promoting the development of on-grid hybrid wind–solar power plants takes on particular importance under conditions of electricity shortages caused by the large-scale destruction of the energy infrastructure due to the ongoing hostilities. This article examines the economic efficiency of installing such power plants in the residential sector of Ukraine under different state support schemes. This study was conducted for on-grid hybrid wind–solar systems of various configurations and installed capacities with different equity and debt capital proportions involved in implementing investment projects. This study’s results highlight the economic efficiency of the feed-in tariff compared to the net billing for households investing in such facilities and emphasize the need to improve policy measures to increase their investment attractiveness.

Research on multi-energy coupled preheating system of city gate station based on Modelica simulation

Natural gas depressurization at city gate stations can cause hydrate formation, necessitating preheating before pressure regulation. To reduce the high energy consumption of traditional city gate station preheating processes, this study introduces four novel multi-energy coupled systems: photovoltaic-air source heat pump (PV-ASHP), solar thermal-combined heat and power-ASHP (ST-CHP-ASHP), CHP-ASHP, and ASHP system, with a typical city gate station in Shanghai taken as the research case. Dynamic energy simulation systems were developed in Dymola software to evaluate the proposed systems from energy, environmental, and economic perspectives, conducting a comparison with conventional boiler preheating systems, including sensitivity analysis of energy prices on system economics. Results indicate PV-ASHP has the lowest annual total cost (ATC) and shortest discounted payback period, while ATC values for ST-CHP-ASHP, CHP-ASHP, and ASHP increase by 6.4 %, 9.6 %, and 12.6 %, respectively. ST-CHP-ASHP and PV-ASHP demonstrate advantages in primary energy rate and carbon emissions, with ST-CHP-ASHP performing slightly better than PV-ASHP. Currently, PV-ASHP demonstrates the highest development potential. If photovoltaic feed-in tariffs remain constant, and natural gas prices decrease by over 12.5 % or CHP feed-in tariffs increase by over 38.4 %, ST-CHP-ASHP becomes more economically viable. This research provides valuable insights for retrofitting China's existing city gate station preheating systems.

Economic viability of decentralised battery storage systems for single-family buildings up to cross-building utilisation

Due to the great cost decrease of photovoltaics as well as battery storage, especially in the segment of decentralised home storage, the number of grid-connected battery-supported photovoltaic systems being installed in recent years is steadily increasing. However, the scientific community has intensively discussed that lithium-based battery storage systems cannot yet be operated economically in most cases. This paper addresses the level to which the cost of lithium battery storage needs to decrease in order to be economically viable. For this purpose, the economic viability of battery storage systems in single-family buildings, multi-apartment buildings and across-buildings is analysed on the basis of a linear optimisation model and the method of the internal rate of return. The utilisation of the storage system is optimised for different battery and photovoltaic capacities on the basis of generation and consumption. The internal rate of return method is used to compare the savings resulting from the reduced consumption from the electricity grid with the investment costs and the operation and maintenance costs. In order to be able to estimate the influence of the most important parameters a sensitivity analysis is also carried out. The analysis concludes that, depending on the combination of capacities of photovoltaics, battery storage and in relation to the load profile, the battery storage costs would have to drop by at least 85% in order to generate a certain predefined return over a depreciation period of 25 years. Furthermore, the more different load profiles can be covered directly with photovoltaic electricity, e.g. in a multi-apartment building or across buildings, the less electricity needs to be stored and this reduces the benefit and the utilisation of the battery storage and therefore the specific investment costs must further decrease. Another conclusion that emerges from the sensitivity analysis is that the electricity price and the spread between the electricity price and the feed-in tariff have the greatest influence on the investment costs and profitability. Due to limited space for photovoltaics and simultaneously high consumption, self-consumption is already quite high with cross-building utilisation and can no longer be increased to the necessary extent by the battery storage system, which is why the investment costs must also be lower. The novelty of this paper lies in particular in the fact that it deals with the target costs of battery storage systems in various scenarios for certain rates of return. The analyses in this paper are intended to provide a deeper understanding of the framework conditions for the economic operation of a battery storage system in the aforementioned scenarios. However, this paper does not take into account alternative sources of income other than savings on grid consumption. The possibility of time-variable (grid) tariffs, for example, is also not considered in detail in this paper and should be analysed further in future work.

Renewable energy technology diffusion model: Evaluation of financial incentives in the electricity market of ecuador

This paper develops a simulation model using the System Dynamics paradigm to evaluate the effect of applying financial incentives on the diffusion of non-conventional renewable energy technologies in the Ecuadorian electricity market. The barriers to the diffusion of renewable energies are studied, the diffusion models are characterised, and the model is built with market variables and financial indicators integrated into its base structure. The Ecuadorian electricity market is described as a case study focusing on the incentive scheme. Based on investment, generation, and indirect incentives, this scheme plays a crucial role in promoting renewable energy technologies. Different long-term diffusion scenarios are simulated and compared with each other and with the baseline scenario to obtain diffusion rates and financial information for five renewable generation technologies: non-conventional hydro, wind, solar photovoltaic, biomass, and geothermal. The results of the simulations show that the combination of incentives leads to high diffusion rates, reassuring the audience about the potential impact of the proposed model. However, the feed-in tariff and tradable green certificate incentives are the most effective in promoting the use of renewable energy. For the Ecuadorian electricity market, the results show that wind and biomass technologies would be the most profitable, as opposed to geothermal energy, whose diffusion will not be feasible within the simulated period.

System friendliness of distributed resources in sustainable energy systems

The increasing share of volatile renewable energy generation in current and future energy systems which does not follow the demand, makes it necessary to shift the synchronization tasks to the system and demand level. The intended demand side consumption management is usually incentivized via financial mechanisms. However, the optimum design of related incentives is still unclear. It is usually discussed under the term “system friendliness” which in turn still lacks a broadly accepted definition. In this article we introduce a new technical definition of “system friendliness” and develop comprehensive and holistic related indicators. For that, we introduce the burden concept for energy systems which represents the amount of technical infrastructure required for stable operation. We use the concept of a hypothetical system energy storage to derive indicators that are capable of quantifying the system friendliness of a given point-of-interest. The developed indicators are independent of regulations or market environments which enables comparability of results between studies and different systems. In a case study we demonstrate our newly developed methodology and exemplary examine decentral district energy storages. Our findings demonstrate that today’s regulatory environments that usually support residential self-consumption maximization are counterproductive. Instead, we show that dynamic end-user prices coupled with dynamic feed in tariffs are able to incentivize an almost 100% system friendly behavior of distributed prosumers.

Technical and economic analysis of digitally controlled substations in local district heating networks

Since the 1990s, there has been a noticeable increase in the establishment of local district heating networks in Germany, coinciding with the use of thermal energy from biogas and biomass facilities. Historically, the prioritization of economically efficient heat utilization was subdued due to favorable electricity feed-in tariffs. However, with the expiration of Renewable Energy Sources Act subsidies, operators shifted focus to the operational costs of district heating networks. This study aims to examine the effects of optimizing controllers and valves at district heating substations in single-family homes, utilizing two local district heating networks. The emphasis is on evaluating impacts on operating costs and determining whether the economic and energetic benefits justify implementation. Simulation studies in MATLAB/Simulink Simscape depict both consumers and district heating networks individually, without aggregation. In the most favorable scenario, investing in enhancing substation controllers in single-family homes is projected to yield returns after 13 years. Comprehensive optimization of all substation controls in single-family homes can potentially result in up to 9% savings in thermal energy demand due to reduced heat losses and a corresponding 9% reduction in electrical power consumption for the main pump.

The Practical Impact of Price-Based Demand-Side Management for Occupants of an Office Building Connected to a Renewable Energy Microgrid

This paper examined the practical impact of price-based demand-side management (DSM) for occupants of an office building connected to a renewable energy microgrid. There has been an absence of studies that have analyzed occupant reactions, in terms of perceived practicality, regarding the implementation of DSM in conjunction with factors including renewable energy generation, load shifting and energy costs. An increased understanding of the practicality of DSM will support future improvements in building energy efficiency and sustainability. Ten occupants of the National Build Energy Retrofit Test-bed (NBERT) were selected as a case study. The electricity consumption pattern of the NBERT occupants was derived over a period of two years. Five unique DSM schedules were developed for each of the NBERT occupants, and a survey was carried out to investigate the practicality of these DSM schedules. A real-time electricity pricing tariff, electricity CO2 intensity, three feed-in tariffs and two microgrid control methods were evaluated to assess the practicality of each DSM schedule on the ten NBERT occupants. The results showed that the incorporation of onsite renewable energy generation with price-based DSM had a positive impact (r = 0.69–0.75) on occupant practicality. Onsite renewable energy generation was able to offset the demand for expensive electricity from the grid during peak hours, which aligned with the occupants’ typical work schedules. However, the introduction of a feed-in tariff with a renewable energy microgrid made price-based DSM less practical (r = 0.15–0.64).

Techno-Economic Analysis of Combined Production of Wind Energy and Green Hydrogen on the Northern Coast of Mauritania

Green hydrogen is becoming increasingly popular, with academics, institutions, and governments concentrating on its development, efficiency improvement, and cost reduction. The objective of the Ministry of Petroleum, Mines, and Energy is to achieve a 35% proportion of renewable energy in the overall energy composition by the year 2030, followed by a 50% commitment by 2050. This goal will be achieved through the implementation of feed-in tariffs and the integration of independent power generators. The present study focused on the economic feasibility of green hydrogen and its production process utilizing renewable energy resources on the northern coast of Mauritania. The current investigation also explored the wind potential along the northern coast of Mauritania, spanning over 600 km between Nouakchott and Nouadhibou. Wind data from masts, Lidar stations, and satellites at 10 and 80 m heights from 2022 to 2023 were used to assess wind characteristics and evaluate five turbine types for local conditions. A comprehensive techno-economic analysis was carried out at five specific sites, encompassing the measures of levelized cost of electricity (LCOE) and levelized cost of green hydrogen (LCOGH), as well as sensitivity analysis and economic performance indicators. The results showed an annual average wind speed of 7.6 m/s in Nouakchott to 9.8 m/s in Nouadhibou at 80 m. The GOLDWIND 3.0 MW model showed the highest capacity factor of 50.81% due to its low cut-in speed of 2.5 m/s and its rated wind speed of 10.5 to 11 m/s. The NORDEX 4 MW model forecasted an annual production of 21.97 GWh in Nouadhibou and 19.23 GWh in Boulanoir, with the LCOE ranging from USD 5.69 to 6.51 cents/kWh, below the local electricity tariff, and an LCOGH of USD 1.85 to 2.11 US/kg H2. Multiple economic indicators confirmed the feasibility of wind energy and green hydrogen projects in assessed sites. These results boosted the confidence of the techno-economic model, highlighting the resilience of future investments in these sustainable energy infrastructures. Mauritania’s north coast has potential for wind energy, aiding green hydrogen production for energy goals.

Configuration optimization and performance analysis of hybrid PV/wind systems in building groups

Distributed hybrid renewable energy is a promising technology for addressing environmental and energy issues, and its performance and system configuration play an essential role in the application. However, the contribution of energy sharing among buildings in building groups to the matching performance has yet to be fully explored. This study established a joint MATLAB-TRNSYS optimization model for the hybrid PV/wind building system to investigate the matching performance of energy consumption in building groups and energy production in PV/wind systems. The optimal system configuration for three objectives, technical, economic, and environmental, was also studied using the multi-objective particle swarm algorithm. Several factors influencing system performance and configuration were considered: renewable energy hybrid, a hybrid of different buildings, intensity of energy use and energy resource, and economic parameters. The results reveal that a hybrid system outperforms a single system, particularly a PV system with a smaller roof area and less installed capacity. Additionally, wind turbines contribute more to system performance than PV panels. Mixing buildings with different heights and functions could also improve system performance by renewable energy sharing in most instances, except multi-story office buildings. Increasing wind resources improves system performance more than solar resources, and increasing energy use intensity negatively impacts system performance for residential buildings but is beneficial for office buildings. Higher grid prices and feed-in tariffs can bring more economic benefits. This study revealed the contribution of energy sharing among different buildings, which could support better application of distributed hybrid renewable energy systems in complex urban environments.

Dynamic grid emission factors and export limits reduce emission abatement and cost benefits of building PV systems

Photovoltaic (PV) installations in the building sector are expected to play a crucial role in Switzerland's efforts to achieve decarbonization targets. Nevertheless, most analyses on PV system design prioritize economic factors, and overlook the impact of angle-dependent PV generation, dynamic grid greenhouse gas (GHG) emissions, and export limitations on their emission abatement potential during operation. Our study sheds light on the cost- and emission-optimal orientation and sizing of PV systems in buildings, factoring in hourly grid GHG emission intensity and curtailment measures. We employ mixed-integer linear programming (MILP) and illustrate the methodology for a case study building under different scenarios, aiming to minimize costs and emissions by considering a combination of rooftop and façade PV systems, and a battery. We show that assuming a constant annual grid GHG emission intensity may overestimate annual emission abatement potential of PV generation by a factor of two, emphasizing the need for dynamic grid GHG emission intensity. When considered, cost-optimal solutions favour larger systems that maximize total production. In contrast, emission-optimal solutions increase self-consumption via inclusion of battery systems. Curtailment due to export limitations reduces the cost and emission benefits of excess generation (from feed-in tariff payments and carbon credits), prompting a trend towards smaller PV installations with steeper panel tilts. Thus, the emission abatement potential of PV generation heavily depends on the option to export excess electricity production.

The Impact of Participation Ratio and Bidding Strategies on New Energy’s Involvement in Electricity Spot Market Trading under Marketization Trends—An Empirical Analysis Based on Henan Province, China

As new-energy electricity increasingly enters the post-subsidy era, traditional fixed feed-in tariffs and guaranteed purchase policies are not conducive to the optimal allocation of large-scale, high-proportion new-energy power due to the high pressure of subsidy funds and the fairness issues of power-generation grid connection. Encouraging new energy to participate in electricity market transactions is considered an effective solution. However, existing studies have presupposed the adverse effects of new energy in proposing market mechanism optimization designs for new-energy participation without quantitative results to support this, which is not conducive to a true assessment of the comprehensive impact of individual instances of new-energy participation in the market. To this end, this study, based on the actual experience and data cases of China’s electricity spot market pilot provinces, considers both unit commitment and economic dispatch in the electricity distribution process, and constructs a two-stage optimization model for electricity spot market clearing. According to the differences in grid connection time and the construction costs of new-energy power, differentiated proportions of new-energy participation in the market and bidding strategies are set. By analyzing the quantitative results of new energy participating in spot market transactions under multiple scenarios, using both typical daily data for normal loads and peak loads, the study provides theoretical support and a data basis for the optimized design of market mechanisms. The research results show that there is a non-linear relationship between the scale of new energy entering the market and its bidding strategies and market-clearing electricity prices. In the transition phase of the low-carbon transformation of the power sector, the impacts of thermal power technology with a certain generation capacity and changes in the relationship between power supply and demand on electricity prices are significant. From the perspective of the individual interests of new-energy providers, the analysis of their bidding strategies in the market is important.

Rule-based energy management strategies for PEMFC-based micro-CHP systems: A comparative analysis

Commercial PEMFC-based micro-CHP systems are operated by rule-based energy management strategies. Each of these strategies constitutes a different way to meet the household energy demand (following the heat demand, following the electricity demand, the maximum of the two, etc.). Previous studies demonstrate that which of them is the best —i.e. the one that manages to meet the demand at the lowest operating cost— depends on the particular scenario in which the micro-CHP system works (gas and electricity prices, annual energy demands, ability to export electricity to the grid, etc.). This paper aims to explore this dependence relationship and to deepen our understanding of it. To this end, a parametric analysis is conducted and the performances achieved by four rule-based operating strategies are compared. The parameters whose influence is studied, and through which the scenario is jointly characterized, are: (1) energy prices (electricity and natural gas), (2) feed-in tariff, (3) stack degradation, (4) climate and (5) heat to power ratio of the demand. The results show this dependence relationship in a clear and more comprehensive way, and offer a better understanding of its nature. From this improved understanding it can be inferred, among other things, that adapting the strategy to the scenario can generate annual savings of up to 14.5 percentage points. Moreover, this enhanced characterization of that dependence relationship can be useful for the design of a new operating strategy, a strategy that, without falling into the complexity that an optimal energy management approach (based on linear programming) involves, manages to exploit the savings potential of micro-CHP systems, thus facilitating their future mass commercialization.

Nun of the river: The material and spiritual economies of small hydropower in rural Tanzania

This article examines the significance of hydroelectric mini-grids owned and operated by Catholic sisterhoods in rural Tanzania, situating them within a broader context of energy transition and environmental justice. The Tanzanian state is betting that mini-grids can effectively supplement the national grid’s limited reach; since 2010 it has invested considerable effort in developing a regulatory framework that streamlines licensing procedures and specifies feed-in tariffs. Today, the field is wide open and a range of ownership models – community, private, state-owned – are unfolding on the ground with variable results regarding their financial sustainability, environmental impact, and developmental outcomes. Though often overlooked in this discourse, missions, churches, abbeys, and convents have a history of operating run-of-the-river power stations and other off-grid systems that stretches back into the colonial era. Such infrastructures anchor material and spiritual economies of rain, care, and cash that straddle both community and commercially oriented modes of provisioning. Their continued presence suggests that in some ways this new paradigm of decentralized energy provision builds upon long-standing historical logics of patronage and political authority in marginal areas.

Economy and energy flexibility optimization of the photovoltaic heat pump system with thermal energy storage

Photovoltaic systems have been widely applied in building energy systems. However, with the sharp increase in demand of electricity in buildings during heating and cooling seasons, the uncertainty of photovoltaic generation further exacerbates the peak-valley difference in electricity use. To improve the economy and energy flexibility of buildings in hot summer and cold winter zones of China, a rule-based operation strategy was proposed for the photovoltaic heat pump with thermal energy storage system to optimize the size of the thermal energy storage system and system operation, with aims of minimizing the total annual cost of the system and maximizing the self-consumption rate of the photovoltaic generation. The effects of grid export power limits, grid import power limits, feed-in tariffs, and PV generation on the system operation optimization results were also investigated. The results indicated that by integrating the thermal energy storage system into the photovoltaic heat pump system, the self-consumption rate of the photovoltaic generation was reduced by 2.39 %, the total annual cost of the system was decreased by 6.61 %, and the payback period of the thermal energy storage system was 1.31 years. The optimum size of the thermal energy storage system and the self-consumption rate of the photovoltaic generation decreased with the increasing grid export power limits and grid import power limits. In contrast, higher grid export power limits, grid import power limits, feed-in tariffs, and PV generation all resulted in a lower total annual cost. This study provided a systematic design and operation optimization method for building energy systems.

Comparison between Blockchain P2P Energy Trading and Conventional Incentive Mechanisms for Distributed Energy Resources—A Rural Microgrid Use Case Study

Peer-to-Peer (P2P) energy trading is a new financial mechanism that can be adopted to incentivize the development of distributed energy resources (DERs), by promoting the selling of excess energy to other peers on the network at a negotiated rate. Current incentive programs, such as net metering (NEM) and Feed-in-Tariff (FiT), operate according to a centralized policy framework, where energy is only traded with the utility, the state-owned grid authority, the service provider, or the power generation/distribution company, who also have the upper hand in deciding on the rates for buying the excess energy. This study presents a comparative analysis of three energy trading mechanisms, P2P energy trading, NEM, and FiT, within a rural microgrid consisting of two prosumers and four consumers. The microgrid serves as a practical testbed for evaluating the economic impacts of these mechanisms, through simulations considering various factors such as energy demand, production variability, and energy rates, and using key metrics such as economic savings, annual energy bill, and wasted excess energy. Results indicate that while net metering and FiT offer stable financial returns for prosumers, P2P trading demonstrates superior flexibility and potentially higher economic benefits for both prosumers and consumers by aligning energy trading with real-time market conditions. The findings offer valuable insights for policymakers and stakeholders seeking to optimize rural energy systems through innovative trading mechanisms.

Comparative Analysis of Reinforcement Learning Approaches for Multi-Objective Optimization in Residential Hybrid Energy Systems

The rapid expansion of renewable energy in buildings has been expedited by technological advancements and government policies. However, including highly permeable intermittent renewables and energy storage presents significant challenges for traditional home energy management systems (HEMSs). Deep reinforcement learning (DRL) is regarded as the most efficient approach for tackling these problems because of its robust nonlinear fitting capacity and capability to operate without a predefined model. This paper presents a DRL control method intended to lower energy expenses and elevate renewable energy usage by optimizing the actions of the battery and heat pump in HEMS. We propose four DRL algorithms and thoroughly assess their performance. In pursuit of this objective, we also devise a new reward function for multi-objective optimization and an interactive environment grounded in expert experience. The results demonstrate that the TD3 algorithm excels in cost savings and PV self-consumption. Compared to the baseline model, the TD3 model achieved a 13.79% reduction in operating costs and a 5.07% increase in PV self-consumption. Additionally, we explored the impact of the feed-in tariff (FiT) on TD3’s performance, revealing its resilience even when the FiT decreases. This comparison provides insights into algorithm selection for specific applications, promoting the development of DRL-driven energy management solutions.

A comprehensive study on energy management, sensitivity analysis, and inertia compliance of feed-in tariff in IEEE bus systems with grid-connected renewable energy sources

The need to incorporate renewable energy generators (REGs) into the electrical grid has become increasingly crucial due to the push for a more sustainable environment. This study advocates an innovative strategy for optimizing inertia-integrated generation and transmission expansion planning (GTEP) to implement feed-in tariffs (FiT). The application of the GAMS CPLEX solver to the model, which tested on an IEEE 6/IEEE 16 system, reveals that using FiT results in a 12.1 % drop in system cost ($599 million to $526 million) and a 7.91 % rise in total system inertia. Sensitivity analysis highlights the correlation between increased REG integration and FiT payment reduction at 50 % penetration. The model outperforms soft computing optimization techniques, showcasing rapid convergence and computational efficiency. The proposed model's validated superiority in rapid convergence and computational efficiency is demonstrated by comparing its results with those obtained from other soft computing optimization techniques.