Portion Of Renewable Energy Research Articles

Volt-VAR Control in Active Distribution Networks Using Multi-Agent Reinforcement Learning

With the advancement of power systems, the integration of a substantial portion of renewable energy often leads to frequent voltage surges and increased fluctuations in distribution networks (DNs), significantly affecting the safety of DNs. Active distribution networks (ADNs) can address voltage issues arising from a high proportion of renewable energy by regulating distributed controllable resources. However, the conventional mathematical optimization-based approach to voltage reactive power control has certain limitations. It heavily depends on precise DN parameters, and its online implementation requires iterative solutions, resulting in prolonged computation time. In this study, we propose a Volt-VAR control (VVC) framework in ADNs based on multi-agent reinforcement learning (MARL). To simplify the control of photovoltaic (PV) inverters, the ADNs are initially divided into several distributed autonomous sub-networks based on the electrical distance of reactive voltage sensitivity. Subsequently, the Multi-Agent Soft Actor-Critic (MASAC) algorithm is employed to address the partitioned cooperative voltage control problem. During online deployment, the agents execute distributed cooperative control based on local observations. Comparative tests involving various methods are conducted on IEEE 33-bus and IEEE 141-bus medium-voltage DNs. The results demonstrate the effectiveness and versatility of this method in managing voltage fluctuations and mitigating reactive power loss.

Integrated Load–Source Side Management for Techno-Economic-Environmental Performance Improvement of the Hybrid Renewable Energy System for Rural Electrification

Electricity produced by a hybrid renewable energy system (HRES) is reliable, economical, and environmentally benign. However, effective management of the load-source side is essential to enhance the reliability, affordability, and eco-friendliness of HRES. Therefore, an integrated load–source side management for techno-economic-environmental (TEE) performance improvement of HRES is developed in this paper. The factors considered are namely technical (renewable energy portion, excess energy factor, and unmet load), environmental (particulate matter and carbon emission), and economical (annualized cost of system, total net present cost, and cost of energy). To solve the HRES size optimization problem, a marine predators algorithm (MPA) is used for the first time. HRES is investigated without Load side management (LSM), with LSM, and with LSM integrated with source-side management (SSM). LSM is carried out using the peak shifting technique, which shifts time-movable loads (TMLs) to off-peak hours depending on excess energy availability, taking into account consumer comfort violations and customer behavior uncertainty. For SSM, a comparatively better energy management strategy (EMS) than the load following, cycle charging, and generator order is proposed, which improves the TEE performance of HRES. The integrated load–source side management saves 5% in NPC and 0.008 $/kWh in COE, respectively. To come up with a configuration that is more feasible, a sensitivity analysis for the HRES's component costs and macroeconomic variables is carried out. Furthermore, the optimal configuration COE is slightly higher than that of the most recent study in the literature. By contrasting the MPA result with the HRES PSO result, the accuracy of the MPA result is also confirmed.

Socio‐techno‐economic‐environmental sizing of hybrid renewable energy system using metaheuristic optimization approaches

AbstractElectricity supply reliability in an electricity distribution network is majorly affected due to unexpected power failures and power cuts. A hybrid renewable energy system (HRES) with the optimal size of renewable energy sources can substantially improve power reliability. Therefore, this article develops an objective function incorporating socio‐techno‐economic‐environmental (STEE) factors for HRES optimal sizing to supply reliable power to a rural village. The factors considered in the objective function are namely social (employment generation factor, human progress index, and land cost), technical (excess energy factor, renewable energy portion, and loss of power supply probability), economical (total net present cost, cost of energy, and annualized cost of system), and environmental (emission cost). In this article, for the first time, marine predators algorithm (MPA) based metaheuristic optimizer is devised to address the sizing optimization problem of HRES. Three HRES configurations, having different arrangements of diesel generator (DG), biogas generator (BG), battery (BAT), wind turbine (WT), and photovoltaic (PV), are examined utilizing MPA, particle swarm optimization (PSO), salp swarm algorithm (SSA), and genetic algorithm (GA) for optimal configuration. Due to the lowest value of economical and environmental factors and the highest value of the social factor, the PV‐WT‐BAT‐BG‐DG configuration is optimal compared to other investigated configurations with MPA. Comparing the four optimizers, MPA has the best STEE factor values, as well as stronger convergence, greater ability to escape from local minima, and higher ability to approach the global optimum. Additionally, by contrasting it with the PSO result for the three HRES configurations, the MPA result quality is confirmed. Furthermore, the cost of energy (0.1799 $/kWh) of the optimal configuration is less than the latest addressed in the literature.

Study on overvoltage suppression method of phase modulation of hydroelectric generating units and its cooperative optimization in new energy grid

When a significant portion of renewable energy is transmitted to the power grid through high voltage direct current, when the monopolar blocking occurs, as a result of the converter station’s filter and reactive power compensation equipment’s influence, overvoltage will be generated, which will cause harm to the new energy station, and even lead to large-scale new energy grid disconnection. This paper initially examines the mechanism behind overvoltage in a new energy power grid and then puts forward a method to restrain overvoltage by using phase modulation operation of hydroelectric generating units. To improve the phase modulation capability of hydroelectric generating units and optimize the utilization of new energy sources, this paper proposes a particle swarm optimization to determine the optimal phase modulation capacity. Finally, this paper builds an example of the PSASP platform to verify the correctness and effectiveness of collaborative optimization.

A new look at China’s environmental quality: how does environmental sustainability respond to the asymmetrical behavior of the competitive industrial sector?

ABSTRACT This research aims to expand the existing literature by bringing a new perspective to China’s environmental quality. Existing literature concerning China’s environmental sustainability disregards competitive industrial performance, which allows the analysis of Sustainable Development Goal-9. The study investigates the impact of competitive industrial performance, economic growth, and renewable energy consumption on the environmental quality (represented by load capacity factor) within the load capacity curve framework. Considering the positive and negative shocks in industrial competitiveness, the study runs the novel asymmetric ARDL with Fourier terms method to examine the non-linear connection between competitiveness and the environment. Empirical analysis shows that industrial competitiveness asymmetrically affects environmental quality and that the load capacity curve hypothesis is invalid in China. It is also evident that renewable energy contributes to environmental quality. Based on these findings, the study presents sustainable development policies for China within the framework of SDG targets. In this context, country’s rapid growth and higher-order industrial competitiveness strategies need to be redesigned in order to increase the share of high-tech activities in total manufacturing and the portion of renewable energy in total energy use. Accordingly, the Chinese policymakers’ primary objectives should be regulations that guide fundamental principles for enhancing environmental quality while preserving the country’s rapid growth and competitive advantage in the industrial process.

Modelling Biodiesel Production of Banking Scheme With Spline Regression

The portion of renewable energy, one of which is biodiesel production in Indonesia, still relatively low due several obstacles, such as the banking financing scheme. Therefore, this research was carried out by involving banking variables, including the banks, third parties fund and Gross Domestic Regional Product of each province to find the best model that affected the rate of biodiesel production in Indonesia. The Spline Regression method was employed here. Modelling the rate of biodiesel production was done by using the knots point method with the smallest GCV Value. Based on the findings, all variables had an influence with a coefficient of determination of 50%, meaning that the model formed was feasible to use in the modelling data patterns. Among these 3 variables, the variable banks had the best influence in determinang tha rate of biodoesel production in each province in Indonesia. In conclusion, the financing scheme from the banking side is an important thing to do considering that the more the number banks in a province, the greater the development potenstial of biodiesel production from each of these provinces.

Desain Simulasi dan Analisa Closed Loop Boost Converter Terintegrasi Solar PV Berbasis PID

The tendency for the price of using solar PV (photovoltaic) to become cheaper means that the portion of the use of this solar energy source is encouraged to be larger along with the addition of the portion of renewable energy (EBT) generators based on PLN's 2021-2030 Electricity Supply Business Plan (RUPTL). As a step to mitigate this problem, a power electronics circuit application is needed in the form of a boost converter or what can be called a step-up DC-DC converter. In this study, the boost converter design modeling is made a closed loop. There is feedback by adding a PID controller to adjust the duty cycle as a function of switching on or off MOSFET so that the output voltage is as desired (setpoint) and adjusts to needs of load. Open-loop design modeling is also included as a comparison. The design stage begins with determining the circuit design, calculating component specifications, and simulating using MATLAB R2013a software and hardware implementation. From the test results, it was found that the boost converter can increase the solar PV voltage varies (17.34-19.13 Volts). In the closed loop boost converter circuit with a constant load of 129.96 Ω with varying duty-cycle value set by PID controller with value of Kp=0.005 Ki=9.75 Kd=0.00000029, the average output voltage is 36. 0067 Volts and stable at the desired setpoint of 36 Volts.

Optimal Sizing of a Hybrid Renewable Energy System: A Socio-Techno-Economic-Environmental Perspective

Abstract Unprecedented power outages and load shedding significantly impact power supply reliability in a power distribution network. Furthermore, extending grid availability to far-flung regions with higher distribution losses is not economically viable. Therefore, a hybrid renewable energy system (HRES) is developed, and its socio-techno-economic-environmental (STEE) viability in supplying reliable electricity to the village is being examined in this paper. STEE factor-based multi-target optimization and sizing technique are designed using the homer pro software. The factors considered are namely social (land cost, human progress index, and employment generation factor), technical (unmet load, renewable energy portion, duty factor, and excess energy factor), economical (annualized cost of system, cost of energy, and total net present cost), and environmental (carbon emission and particulate matter). Three HRES setups are investigated, with various combinations of photovoltaic (PV), wind turbine (WT), battery (BAT), biogas generator (BG), and diesel generator (DG) and the optimal configuration is selected by STEE performance analysis. Compared to other evaluated setups, the HRES design with PV–WT–BAT–BG–DG is optimal for a consistent power supply. A sensitivity analysis for the optimal setup’s macro-economic variables and component costs is performed to achieve a more feasible optimal setup. Furthermore, the optimal setup’s cost of energy (0.1813 $/kW h) is lower than that of the most recent study in the literature. The closeness of the hybrid optimization of multiple electric renewables (HOMER) results (cost of energy (0.1813 $/kW h), unmet load (2.86 kW h/year)) and particle swarm optimization results (cost of energy (0.1799 $/kW h), unmet load (2.60 kW h/year)) for the optimal HRES setup supports the validity of the HOMER method used in this investigation.

Financial development and renewable energy consumption in Nigeria

Financial sector performance is increasingly linked with the transition to renewable energy in the sustainability discourse of developing economies. This paper examines the nexus and implication(s) of financial development on renewable energy consumption in Nigeria (the largest and most populous economy in Africa). Specifically, this study utilized the broad-based financial development index data to effectively address the multidimensional nature of financial development and the portion of renewable energy in total energy consumption as key variables, while other relevant pieces of information (growth rate of per capita GDP, foreign direct investment and consumer price index) were incorporated. The study employed a blend of the ADF test and Zivot-Andrew test to ascertain stationarity properties as well as the likelihood of structural breaks, while the ARDL was utilized to determine the long-run relationship(s) using data from 1981 to 2019. The study estimation finds, among other things, that financial development is critical for renewable energy consumption in Nigeria and recommends policies to promote better outcomes for the financial and energy sectors, respectively.

Renewable Energy Transition Strategy for PT.CI to Reduce 50% Emission by 2030

The global and Indonesia energy trend is heading to process of transitioning from fossil fuel to renewable energy (decarbonization) in the purpose of reducing Green House Gas (GHG) effects. Industries as one of the biggest contributors of emission generator expected to participate in this effort, where fuel and electricity play significant roles in running the operation. Many businesses try to participate and state their commitment on this energy transition initiative by increasing the portion of renewable energy within their operation. Meanwhile, business have several uncertainties’ on how the renewable energy will be acquired and will this renewable energy options be available at the time they need it. Campur Plc. (CP) through its subsidiary in Indonesia, PT. Campur Ilmiah (PT. CI) has targeted the entity to reduce 50% of the emission by 2030 with the baseline of 2018, which align with corporate target of 46.2% of emission reduction globally. Uncertainties on achieving this target generated from external and internal factors, and not to forget how to sustainably maintain the achievement. The location of PT.CI in industrial estate need to be considered as limitation because the power and energy supply are regulated. The accessibility, availability and affordability of renewable energy are expected to be handled by the government, industrial estate or other third party in energy business, but the phasing and the achievement up to now has not shown a promising progress. As a business, PT.CI need to have a strategic planning on this energy transition to support the global target as well as shown a positive investment climate in Indonesia. There are four (4) scenarios has been developed and each of the scenarios are explored to identify alternative and possible strategies to still be able achieving the target and how the organization manage these changes. As the conclusion of this research, four (4) strategic imperatives are defined. This research also might be use as the reference of future planning for the similar industries that have the similar target and type of energy mix.

A Mini-Review on Power-to-Methane Catalysts

The ever increasing CO₂ atmospheric concentration causes the climate change threatening the present and future generations on earth. In order to resolve this global issue, the portion of renewable energy is expected to be increased in near future to replace the conventional fossil fuel-based energy. Because of the variability of renewable energy, various energy storage systems were proposed. One of them is the power-to-fuel concept in which the captured CO₂ is hydrogenated into fuels with hydrogen generated through water electrolysis by using renewable electricity. CO₂ methanation is one of key steps in this process. Since this is an exothermic reaction and thermodynamically limited one, the development of active catalyst at low temperatures is highly plausible. In this mini-review, we aim to overview the CO₂ methanation catalysts which are mainly composed of active metals, supports, and promoters. Furthermore, since CO₂ methanation is a highly exothermic reaction and the thermal heat release should be efficiently accomplished, some new concepts for the catalyst and reactor design are also addressed.

State-of-the-Art Review of Positive Energy Building and Community Systems

A positive energy system that produces more renewable energy than its demand while ensuring appropriate comfort levels is an excellent path towards increasing the portion of renewable energy, reducing carbon emission, and increasing the energy system’s overall performance. In particular, it has been believed as step forward towards zero energy systems. Recent progress in positive energy building and community levels is gaining interest among different stakeholders. However, an inadequate understanding of the positive energy system is widely noticed in many projects, and a shortage of standard details on the positive energy system still prevails in the research community. Therefore, a state-of-the-art review of positive energy building and community is conducted in this paper. Firstly, this paper begins with the definitions and concepts of positive energy buildings and communities. Secondly, it comprehensively describes the energy supplies, demands, indicators, storage, energy management, roles of stakeholders, and bottlenecks of positive energy systems. Thirdly, the main differences between positive energy buildings and communities are summarized. Fourthly, the impact of smart energy grids and new energy vehicles on the positive energy buildings and communities is derived. As a conclusion, this paper shows that even though all the energy-efficient buildings such as passive buildings, nearly zero energy buildings, zero energy buildings, positive energy buildings look like an up-trending scale of renewable penetration, considerable differences are visible among all, and the same thing applies to the community level. Furthermore, considerable differences exist when comparing between positive buildings and communities regarding both the technical and economic perspectives.

Macroeconomic Determinants of Renewable Electricity Technology Adoption in Thailand

Renewable energy plays a significant role in mitigating C02 emission and boosts sustainable development. Initially, this study examines those factors which create hurdles in adopting renewable energy technology in Thailand. Later, this study examined the impact of renewable energy with other supporting variables on Thailand's total energy consumption. For this purpose, this study used 38 years of data from 1990 to 2018. Initially, the Augmented Dickey fuller test applied to verify the order of integration on indicators, and it confirms that there exists a unit order of integration. Then applied Johansen Cointegration, and it confirms that there are long-run relationships among trade openness, GDP, energy consumption (fossil fuels), financial development, and renewable energy consumption. Further applied Vector error correction model (VECM) to estimates the coefficients on indicators. Results confirm that openness to trade endorses the consumption of renewable energy in Thailand. However, the development of the economy and traditional energy resources creates hurdles to adapting renewable energy in Thailand. Renewable energy technology in Thailand did not significantly impact financial growth and development. After the research, the researcher advised the government of Thailand to adopt and implement the regulations and policies that maximize the magnitude of renewable energy and maximize the portion of renewable energy in total consumption of the overall energy consumption for the country Thailand.

Design optimization of a hybrid system subject to reliability level and renewable energy penetration

In recent years, design optimization of hybrid power generation systems which utilize renewable energy resources has received a significant attention. One of the most challenging problems in design of such systems is optimal sizing. To tackle this drawback, this paper presents an efficient and robust optimization approach for size optimization of a hybrid system composed of photovoltaic (PV) panel, diesel generator and fuel cell (FC). The proposed method is a modified version of crow search algorithm (CSA) in which awareness probability is adjusted by an adaptive manner. In the sizing framework, total net present cost (TNPC) is minimized subject to two main constraints: loss of power supply probability (LPSP) and renewable energy portion (REP). Simulation results show that (1) REP has a considerable impact on TNPC of the designed system, (2) optimal combination of PV, diesel generator, FC, electrolyzer and hydrogen tank leads to establishing a reliable and cost-effective hybrid power generation system and (3) the proposed method (CSAadaptive-AP) finds more promising and robust results than original CSA, genetic algorithm (GA) and particle swarm optimization (PSO).

Implementing triple helix through Listrik Kerakyatan initiative: community-based energy from waste

As depicted by its three components, A (academic), B (business), and G (government), the Triple Helix principle aims at narrowing the gap between the competencies of university graduates and those required by businesses or industries in the real world, under the corridor of government rules and regulations. The main issues that will be addressed by the triple helix concept is the national policy to attain 23% of renewable energy portion by the year 2025. However, the conventional electricity construction, which usually prefer a large-scale interconnected system, is currently facing serious delay due to difficulties in acquiring land and permit. Moreover, such large-scale power plants are not sufficient to serve consumers that are scattered in more than three thousand islands in Indonesia archipelago. In addition, such big projects are mostly owned by giant investors that depend on foreign fund and technology, leaving no opportunity for local people to contribute and have ownership over their energy needs. STT PLN proposes a simple small-scale distributed generation that can be owned and managed by local people by using renewable energy sources that are available around the communities. Waste is the most attractive resources because by converting waste to energy, the problem of waste can be solved at the same time. Based on the research and pilot project that had been conducted in three locations, Listrik Kerakyatan (Community-based Electricity) is technically simple so it can be applied and managed by local people. It is also economically viable as the required capital is relatively small and affordable by small enterprises. The commutative law of math also says that 1x1000 = 1000 x1. Therefore, going by that law, the total capacity generated by 1000 units of small LKs can be similar to one large unit of conventional model.

Modelling of Indonesian road transport energy sector in order to fulfill the national energy and oil reduction targets

Due to increasing concern of the Indonesian government towards the ever increasing national level of carbon emissions and the increasing demand of oil, in 2014 the Indonesian National Energy Council released the National Energy Policy which set the target of an increased renewable energy portion to become 23% of the total national energy consumption while setting a limit to oil consumption to be at most 25%. As the road transportation sector consumes more than 60% of the national oil consumption, measures targeting this sector will be important in fulfilling the target. A model has been set up to evaluate the impact of the measures on oil consumption via two main avenues: the substitution of oil based fuels with alternative fuels (e.g. biofuel, compressed natural gas/CNG), the reduction of oil consumption via vehicle retirement and the acceleration of fuel economy improvement for vehicles. Results have shown that it is important that policies consider the presence of older vehicles in the population since there is presently no vehicle retirement policy or penalty for older vehicles resulting in a large number of old vehicles still being operational. Thus, introduction of new vehicles will have a limited effect on the average fuel efficiency. Implementation of a vehicle retirement policy to reduce the amount of older vehicles is shown to be very effective in stemming the increase of oil consumption. In regards to fuel substitution, oil substitution with ethanol is most impactful, as most motor vehicles in Indonesia rely on gasoline including the rapidly increasing motorcycle population. While oil consumption is also reduced by biodiesel substitution, impact is more limited due to a smaller diesel vehicle population with a lower annual increase of vehicle population. In addition, financial, social and regulatory barriers exist that impend implementation of alternative fuels and vehicle limitation schemes. We also evaluated possible barriers and avenues that can further promote these measures to meet the national energy policy target.

Influence of Policy, Air Quality, and Local Attitudes toward Renewable Energy on the Adoption of Woody Biomass Heating Systems

Heat produced from woody biomass accounts for a significant portion of renewable energy in the United States. Economic and federal policy factors driving institutional adoption of woody biomass heating systems have been identified and examined in previous studies, as have the effects of state policies in support of biomass heating. However, plans for a number of mid- to large-scale biomass facilities have been abandoned after being proposed in communities with many of the factors and policies considered favorable to the adoption of such systems. In many of these cases, opponents cited potential negative impacts on local air quality, despite being generally in favor of renewable energy. This study employed a zero inflated negative binomial (ZINB) statistical model to determine if state policies, air quality, and local attitudes toward renewable energy have a significant effect on the adoption and retention of distributed-scale biomass combustion systems used for institutional heating. State policy appears to have a negligible effect, while the influences of historic and current air pollution and local emissions appear insignificant. However, local attitudes in favor of renewable energy are associated with the adoption and retention of distributed-scale woody biomass heating systems. This is an indication of the importance of local support in determining the fate of future biomass energy projects.

Energy and exergy analysis of dry-steam geothermal power plant: Case study in kamojang geothermal power plant unit 2

The Government of Indonesia is committed to realize a policy of 35,000 Megawatt (MW) of an additional supply of electricity within 5 years (2014-2019). The projection of this capacity is largely supported by fossil fuel power plants and a small portion of renewable energy. One of the renewable energy which currently has great potential in Indonesia is the geothermal. Therefore, improving the capacity of geothermal is needed to support the policy. The Kamojang is one of the largest geothermal power plant in Indonesia with an installed capacity of 235 MW from 5 generating units. The purposes of this research is to calculate the energy and exergy analysis at Kamojang geothermal power plant. To improve the capacity, exergy analysis can be used by employing the thermodynamic method. In this research, unit 2 of Kamojang's plant is employed. The analysis was examined by using the Engineering Equation Solver (EES) code. The results show the first law of efficiency was calculated at 19.03% and the second law of efficiency at 40.31%.

ELCC Approach for Calculating Capacity Credit of Wind Power in Korea

The share of wind power generation in domestic renewable energy is expected to increase significantly due to nationwide effort to reduce greenhouse gas emission and to enlarge the portion of renewable energy in electricity generation mix. In this study, the capacity credit, which is the most important factor for evaluating the effective capacity of domestic wind power, is calculated by using the ELCC (Effective Load Carrying Capability) methodology. The ELCC method is known to have the most sophisticated rationale among the various capacity credit estimation methods. We used the single-year data (2014) for the reference system, power demand and wind utilization. CC has been calculated to be about 0.3091 when the wind power penetration rate is less than 1%, and CC has a tendency of decreasing steadily with increasing penetration rate. According to the survey, there is no previous research on national level CC for domestic wind power generation.

Risk-averse stochastic unit commitment with incomplete information

ABSTRACTDue to the sustainable nature and stimulus plans from government, renewable energy (such as wind and solar) has been increasingly used in power systems. However, the intermittency of renewable energy creates challenges for power system operators to keep the systems reliable and cost-effective. In addition, information about renewable energy is usually incomplete. Instead of knowing the true probability distribution of the renewable energy course, only a set of historical data samples can be collected from the true (while ambiguous) distribution. In this article, we study two risk-averse stochastic unit commitment models with incomplete information: the first model being a chance-constrained unit commitment model and the second one a two-stage stochastic unit commitment model with recourse. Based on historical data on renewable energy, we construct a confidence set for the probability distribution of the renewable energy and propose data-driven stochastic unit commitment models to hedge against the incomplete nature of the information. Our models also ensure that, with a high probability, a large portion of renewable energy is utilized. Furthermore, we develop solution approaches to solve the models based on deriving strong valid inequalities and Benders’ decomposition algorithms. We show that the risk-averse behavior of both models decreases as more data samples are collected and eventually vanishes as the sample size goes to infinity. Finally, our case studies verify the effectiveness of our proposed models and solution approaches.