Surplus Generation Research Articles

Electricity scenarios for Hungary: Possible role of wind and solar resources in the energy transition

The paper examines the compatibility of wind and solar energy resources with projections of future electricity demand in Hungary. For such, we model the national electricity system and estimate surplus generation. The model makes use of hourly distributions of electricity demand and power generation. Simulations for the year 2033 (last scenario year) suggest that 46–47% of the projected electricity consumption can be supplied by wind turbines and solar PV technology with a surplus of less than 5% of yearly consumption. A suitable capacity ratio of wind to solar PV and the management of electric vehicle charging may reduce surplus electricity. It is shown by our EnergyPLAN model that the solar PV capacity should be 1.1 times the wind power capacity which is a huge contrast to the current situation where solar PV is almost 10 times the wind power capacity in Hungary.

STrade: Blockchain based secure energy trading using vehicle-to-grid mutual authentication in smart transportation

Electric vehicles are gaining popularity in the Vehicle-to-Grid network due to recharge batteries during off-peak electricity hours and discharge during peak hours. It allows for accomplishing electricity requirements in periods of high demand and additional storage in case of surplus generation from the grid. Electric vehicles also earn reward points for energy trading. The significant trading data volume processed by the underlying Vehicle-to-Grid infrastructure results in numerous security, privacy and scalability challenges. Researchers suggested various energy trading schemes but suffered from anonymity, large overheads, and dependency on a centralized system, which may cause single-point failure. As a solution, new design principles are desirable to enable the next generation of Vehicle-to-Grid networks. Decentralized energy information networks are a crucial aspect of future power grids, and blockchain technology offers promising potential to support local energy trading and decentralized power generation. Thus, a proposed framework uses the blockchain-based decentralized, secure, and privacy vehicle-to-grid network mutual authentication and energy trading system using elliptic curve cryptography with a scheduling feature. The Proposed scheme is divided into four steps (1) Registration, (2) Scheduling, (3) Mutual authentication and (4) Consensus and energy trading. Distributed ledger blockchain technology makes every transaction valid and authentic, possibly minimizing or eliminating mediators in energy trading, while lightweight elliptical curve cryptography is used for mutual authentication. Further, the performance of our scheme is justified by using the popular AVISPA simulation tool. Our analysis illustrates that the proposed model is secure, privacy-preserving, and supports minimal communicational and computational overhead of 1750 bits and 7.027 ms compared to state-of-the-art work.

Interpretable Transformer Model for Capturing Regime Switching Effects of Real-Time Electricity Prices

Real-time electricity prices are economic signals incentivizing market players to support real-time system balancing. These price signals typically switch between low- and high-price regimes depending on whether the power system is in surplus or shortage of generation, which is hard to capture. In this context, we propose a new Transformer-based model to assist the short-term trading strategies of market players. The proposed model offers high-performance probabilistic forecasts of real-time prices while providing insights into its inner decision-making process. Transformers rely on attention mechanisms solely computed via feed-forward networks to explicitly learn temporal patterns, which allows them to capture complex dependencies such as regime switching. Here, we augment Transformers with subnetworks dedicated to endogenously quantify the relative importance of each input feature. Hence, the resulting forecaster intrinsically provides the temporal attribution of each input feature, which foster trust and transparency for subsequent decision makers. Our case study on real-world market data of the Belgian power system demonstrates the ability of the proposed model to outperform state-of-the-art forecasting techniques, while shedding light on its most important drivers.

Development of an optimization model for the feasibility analysis of hydrogen application as energy storage system in microgrids

Hydrogen can be used as an Energy Storage System (ESS) in a microgrid allowing to store surplus generation of variable renewable sources for later use. Research in the area mainly refers to the sizing of the components, however few studies evaluate the optimal technology selection and operation of microgrids using hydrogen as ESS. In this work, a model to determines optimal selection and to dispatch of Distributed Energy Resources (DER) allowing to evaluate the viability of hydrogen application as ESS in a microgrid is developed. The model is implemented in GAMS, using mixed integer linear programming, and applied in a hypothetical microgrid using as input data load profiles and commercial data available in literature. The results indicate the economical and environmental benefits of DER adoption, but the currently high investment costs make it infeasible to adopt hydrogen into a microgrid. However, when considering environmental costs and market prospects, the adoption of this technology became a good alternative, improving the energy management and reducing the total annual cost of the microgrid by 14.1%.

Possibility of exporting hydrogen in Nepal

The leap of Nepal's hydropower energy generation due to increased capacity of hydropower plants leads to a significant energy surplus. For proper utilization of power, surplus generation can be bridged with electrification of major sectors such as transportation, house hold heat supply, industries and export. It can be used to replace fossil fuels and achieve energy independence. Utilization of surplus hydropower and renewable energy gives an opportunity to produce green hydrogen at marginal costs. Hydrogen is a carbon neutral solution with multi-faceted applications in the field of heat, power and energy storage. Energy models to determine the installation capacities of hydrogen plants is very important to plan projects and visualize results. This paper is an observational study where different scenarios of surplus energy and the potential to produce hydrogen are explored. Estimation of size, cost and hydrogen generation for different scenarios of surplus are analysed using excel model. The data simulated and projected are taken from NEA, IRENA, and ADB etc. The simulated data of electricity generation profile is used. From the results of this paper, a size of hydrogen system and its economic constraints can be speculated for different case of Nepal's surplus energy.

The ‘Petrocurrency’ Determinants in Growing Sino-US Confrontation: Implication for South Asia

The purpose of this article is to identify the areas where China’s internationally rising monetary and petrocurrency influence is likely to conflict with the US’s monetary as well as strategic interests. It is assumed that China’s creation of mutually financially supportive networks of economic, monetary, petrocurrency as well as highly innovative and expanding defence industrial structures are sources of generation and reinvestment of revenues and surpluses which are directly coming in conflict with the US’s international interests and especially in the South Asian region. In this perspective, this article poses the questions: what are the innovative developments in China’s refinement of its petrocurrency and its internationally extended arms industry? How are these leading to confrontation with the US? And lastly what are the impacts of this monetary and petrocurrency policies on the South Asian region? In the theoretical domain, this article addresses the role of the combination of monetary and strategic factors in growing confrontation between the two great powers and the possibilities of conflicts leading to changes in international polarity and order. It is argued that China appears to suggest that its new version of international order encourages economic competition among great powers; however, this newly emerging Chinese global monetary and geostrategic network has equal risks of leading to strategic confrontations and armed conflict between China and the US as well as South Asian states.

Evaluation of the Spanish regulation on self-consumption photovoltaic installations. A case study based on a rural municipality in Spain

In European countries, an energy transition towards renewable energies is taking place, promoting self-consumption photovoltaic systems. Some studies point out that the existing regulations and support for photovoltaic systems is still scarce in Spain. This work analyses the penetration of photovoltaic systems and their amortisation in rural areas within the Spanish regulatory framework. For this purpose, an economic decision-making method for the implementation of photovoltaic systems is proposed. This method is based on comparing the possible self-consumption scenarios included in the Spanish regulation and their payback periods. Subsequently, a rural municipality in Spain has been analysed in detail as a case study. Results show that the Spanish regulation on self-consumption does not provide an adequate profitability in rural areas, as the amortisation period with surplus sale is between 16 and 22 years. If the surplus generation is not sold, the payback rises up to 28 years. Therefore, from the economical point of view, photovoltaic generation power plants with surplus sale are more attractive than self-consumption installations, as the payback period is around 12 years. Consequently, a change in the current Spanish regulations is necessary to support individual self-consumption photovoltaic installations, to make them as profitable as photovoltaic generation power plants.

CNN-LSTM vs. LSTM-CNN to Predict Power Flow Direction: A Case Study of the High-Voltage Subnet of Northeast Germany

The massive installation of renewable energy sources together with energy storage in the power grid can lead to fluctuating energy consumption when there is a bi-directional power flow due to the surplus of electricity generation. To ensure the security and reliability of the power grid, high-quality bi-directional power flow prediction is required. However, predicting bi-directional power flow remains a challenge due to the ever-changing characteristics of power flow and the influence of weather on renewable power generation. To overcome these challenges, we present two of the most popular hybrid deep learning (HDL) models based on a combination of a convolutional neural network (CNN) and long-term memory (LSTM) to predict the power flow in the investigated network cluster. In our approach, the models CNN-LSTM and LSTM-CNN were trained with two different datasets in terms of size and included parameters. The aim was to see whether the size of the dataset and the additional weather data can affect the performance of the proposed model to predict power flow. The result shows that both proposed models can achieve a small error under certain conditions. While the size and parameters of the dataset can affect the training time and accuracy of the HDL model.

Implementation of seed collection programs for the recovery of Argopecten purpuratus populations in the La Rinconada marine reserve (Antofagasta, Chile)

Abstract ‘La Rinconada Marine’ Reserve (MR), Chile was created in 1997 to preserve the genetic stock of the scallop Argopecten purpuratus and eventually to supply seed to areas outside of the reserve and support aquaculture activities. Data from biological and fisheries monitoring of A. purpuratus as well as environmental conditions in the MR are available for the period from 1993 to 2009. The continuous extraction of A. purpuratus from La Rinconada MR in Chile, without a science‐based exploitation plan, has not only decreased the abundance and population structure of the species but has also significantly affected seed settlement in artificial collectors and population recruitment. Therefore, the goals of the MR have not been achieved. This review of biological and fishing studies of A. purpuratus in La Rinconada MR provides a basis for the implementation of a sustainable programme for the natural collection of A. purpuratus seed for population recovery. A. purpuratus recruitment varies substantially between years and is not strongly related to the size of the parental population. Larval collection and recruitment depend on environmental events (El Niño‐Southern Oscillation) and biological substrate availability (Rhodymenia red algae). These factors produce a bentho‐pelagic decoupling between parental abundance, larval production and subsequent recruitment of A. purpuratus that limits stock recovery in the MR. To address the poor population status of A. purpuratus in the MR, recovery of the adult population is needed. Therefore, an assisted collection and recruitment strategy is proposed to increase the population and enable the generation of surplus seed, fulfilling the initial aims of La Rinconada MR.

Tecno-economic evaluation of residential PV systems under a tiered rate and net metering program in the Dominican Republic

This article presents a study of the profitability of Residential Photovoltaic Systems (RPVS), through a techno-economic model based on the Net Metering Program (NMP) and tiered rate in the Dominican Republic (DR). This work seeks to identify profitable investment options in RPVS according to the level of monthly consumption of customers and the effect of the Tax Credit (TC). The methodology consists of maximizing the Net Present Value (NPV) to obtain the Payback Time (PBT) and the Internal Rate of Return (IRR). Without TC, the IRR was from 9.0 % to 23.0 % and the PBT was from 9.91 to 4.46 years for Average Monthly Electricity Consumed (AMEC) of 242 kWh and 1594 kWh respectively. At all levels of electricity consumption chosen, surplus generation at the end of the year was required to maximize the NPV; the numerical simulation showed oversized RPVS in relation to the energy demanded, between 25 % and 84 %. To maximize NPV, the lowest installed capacity was 3.28 kWp due to the increase of LCOE on RPVS for low consumption customers.

Realise flexibility potential of EV fleets through grid-serving charging strategies

Making flexibility of electric vehicles usable for distribution system operators is crucial to further integrate large portions of renewable energy sources into the energy system as well as high power loads. This paper provides a better understanding of a fleet's flexibility potential with a nightly dwell time and its deployment using indirect control schemes related to grid charges. Three grid-serving charging strategies were modelled (time-variable grid charges (TV), flexible time window (FL), and schedule (SC)) and compared for local setup configurations using a photovoltaic (PV) system, stationary battery, and vehicle-to-grid (V2G) in varying grid situations. In comparison to simple balanced charging, all grid-serving strategies can achieve a higher utilisation of energy from periods with generation surplus and reduce residual load peaks. TV has substantially higher precision in increasing energy withdrawal during curtailment, while FL performs comparable in utilising generation surplus. Both can be extended by additional flexibility through battery and V2G; an additional PV system, however, decreases the volume of shiftable load. In most variations, gridserving charging results in savings for the DSO which are not fully reflected by the consumer grid charges. The results indicate how feed-in from flexible components has to be remunerated to render it more attractive for both DSO and customer.

Multi-vector energy management system including scheduling electrolyser, electric vehicle charging station and other assets in a real scenario

Today, in the field of energy, the main goal is to reduce emissions with the aim of maintaining a clean environment. To reduce energy consumption from fossil fuels, new tools for micro-grids have been proposed. In the context of multi-vector energy management systems, the present work proposes an optimal scheduler based on genetic algorithms to manage flexible assets in the energy system, such as energy storage and manageable demand. This tool is applied to a case study for a Spanish technology park (360 kW consumption peak) with photovoltaic and wind generation (735 kW generation peak), hydrogen production (15 kW), and electric and fuel cell charging stations. It provides an hourly day-ahead scheduling for the existing flexible assets: the electrolyser, the electric vehicle charging station, the hydrogen refuelling station, and the heating, ventilation, and air conditioning system in one building of the park.A set of experiments is carried out over a period of 14 days, using real data and performing computations in real time, in order to test and validate the tool. The analysis of results show that the solution maximises the use of local renewable energy production (demand is shifted to those hours when there is a surplus of generation), which means a reduction in energy costs, whereas the computational cost allows the implementation of the tool in real time.

Modeling and evaluating bidirectionally chargeable electric vehicles in the future European energy system

In addition to a massive expansion of renewable energies, a successful change towards a decarbonized energy system requires the flexibilization of consumers and the integration of storage and sector coupling technologies. Bidirectionally chargeable electric vehicles (EVs) represent such a consumer flexibility. They are able to charge when there is an electricity generation surplus and to discharge when there is a shortage in electricity generation. Therefore, they can act as a storage from the perspective of the energy system. This paper analyzes different modeling approaches of bidirectionally chargeable EVs in large-scale energy systems and evaluates the impact of bidirectionally chargeable EVs on the future European energy system design. We compare the modeling of discrete EV profiles, clustered EV profiles as well as an aggregated EV profile with simplified constraints. Aggregation of EV profiles per country leads to significantly lower computation times, while still achieving results close to the reference case. The number of bidirectionally chargeable EVs in a cost optimal future European energy system increases from 6 million EVs in 2025 to over 60 million EVs in 2050. We show that bidirectionally chargeable EVs lead to a better integration of PV generation, to lower installed capacities of gas- and hydrogen-fired power plants as well as stationary battery storages. They also lead to decreasing electricity prices and total European energy system costs.

Decarbonizing the electricity sector in Qatar using PV combined with ice thermal and battery storage

High daytime electricity demand from space cooling synergetic with predictable and reliable solar insolation creates a unique opportunity to exploit solar PV-enabled decarbonization solutions in Qatar. This paper examines the economic viability of combining utility-scale PV with ice thermal and battery storage to decarbonize the electricity sector in Qatar, which exclusively runs on gas generation. The problem is formulated in a two-stage stochastic linear programming that minimizes annual system costs at a given gas price. Under the current gas price of $3.3/MMBtu (gas-generated electricity at $37/MWh), PV and ice storage deployed in Qatar could reduce gas generation use and peak demand by 43% and 18%, respectively, and cut the annual system costs by 20%. At a gas price of $6.5/MMBtu (equivalent to carbon pricing at $60/ton of CO2), gas generation can be reduced by 60% using PV and ice storage. Reducing gas generation further is challenging since both cooling and non-cooling demands peak in August, whereas PV generation peaks in June, producing less surplus generation at a time of need, and ice thermal storage cannot cost-effectively outcompete already existing gas generations for highly seasonal cooling needs. Battery storage becomes cost-effective above a gas price of $9.2/MMBtu (equivalent to carbon pricing at $110/ton of CO2); it is primarily used to manage the diurnal behavior of non-cooling loads and could decarbonize the electricity sector by around 90%.

Ground source heat pump driven by reciprocating engine firing biomethane from wastewater treatment plant sludge in a cogeneration for district heating and cooling. A case study in Spain

Wastewater treatment plants are a key facility in municipalities to reach the required water quality before returning to the environment. Their energy consumption constitutes the most critical cost in their operation, although sludge produced in the treatment can be fed into an anaerobic digester to produce biogas. Such biogas is usually burnt into a cogeneration reciprocating engine that produces power injected into the grid and heat to maintain the required temperature in the digester. This energy recovery technique also avoids direct methane emissions from the biogas to the atmosphere. An alternative energy recovery of the sludge is proposed in this paper, seeking to cover both the winter and summer thermal demands of the municipality whose wastewater is treated by the plant.A district heating and cooling network is assumed to be available in the municipality, whose demand will be met (total or partially) by the proposed system. The biogas production has been assessed from a large number of wastewater treatment plants in Spain. This fuel will be upgraded to biomethane to inject eventual surplus generation into the natural gas grid. The hourly thermal demand is estimated from a self-elaboration expansion of annual expressions given in Spanish regulations. A high insulation level in the dwellings of the municipality is assumed to reach the maximum thermal demand coverage level. Underfloor heating and cooling is used as final air conditioning system. The conversion is carried out by supplying the biomethane to a cogeneration reciprocating engine, whose power output drives a ground source heat pump and its recovered heat is used for the thermal conditioning of the biogas digester as well as for heating in winter.The results show that for a 50,000 inhabitants treatment plant, the thermal demand coverage percentage ranges from 28 % to 51 % and the levelized cost of heating and cooling from 38 to 65 €/MWhth. Generally, the lowest cost is reached in zones with an intermediate coverage percentage. Even with high insulation dwellings and high-efficiency systems, the thermal demand coverage percentage is low. This suggests that biomethane production from all the entire municipality can be devoted to meet a selected district's complete demand, built with high standards. This district might be focused on social dwellings.

Improvement of Operating Efficiency of Energy Cooperatives with the Use of “Crypto-Coin Mining”

Poland remains the most coal-dependent economy in the EU. To minimize that problem, which is particularly clear and dangerous in the period of a shortage of fossil fuels, the Polish authorities have decided to establish various institutions, organizational and regulatory solutions. Their role is to support the development of renewable energy sources and local energy communities. The latter are to focus on optimizing the production and consumption of energy in pursuit of energy self-sufficiency on a local scale. One such institution, set up in Poland over the last several years, is the energy cooperative, which is intended to increase the efficient use of the potential of renewable energy sources in rural and urban–rural areas. The authors of this article verify the assumptions, for instance, the number, composition or production and members’ consumption profiles, under which such a relatively new institution has the chance to develop. A novelty in this research paper is that the interests of the entities composing a given energy cooperative may additionally be secured by the use of surplus generation for crypto-coin mining, and thus the storage of energy in virtual currency. A dedicated mathematical model in mixed-integer programming technology was used, enriched with respect to previous research, making it possible for members of the cooperative to achieve energy independence while maximizing self-consumption and using their excess energy for processing cryptocurrency. This is in line with the global trend of “greening”; the processes of acquiring electronic money.

DESIGN OF A BIDIRECTIONAL DC MICROGRID CONTROLLED WITH ENERGY MANAGEMENT SYSTEM

Energy management integrating renewables and conventional grids might be viable for meeting current and future energy demands. The amount of energy generated from renewable sources varies from time to time. When a hybrid renewable-based unidirectional dc microgrid is linked to the utility grid, energy might be underutilized during periods of surplus generation. Bidirectional dc microgrid systems can help with energy management and address various environmental challenges. The architecture of a bidirectional dc microgrid, including solar photovoltaics (PV), wind turbines, battery storage and conventional utility grid has been designed in this work. An energy management system (EMS) is designed to supply the required energy to particular loads under various conditions. Maximum available power is extracted from PV using Maximum Power Point Tracking (MPPT), using the P&O algorithm. When the combined power of the PV panels and wind turbine exceeds the demand of the loads, the extra energy is used to charge the batteries. The remaining energy is supplied to the power grid through an inverter when the battery's state of charge (SOC) reaches 90%. When there is a dearth of generated electricity from renewable sources, and the battery's SOC is less than 30%, power is drawn from the utility grid and provided to loads. The system design is implemented in MATLAB/Simulink and the effects of altering the circumstances on the electrical parameters are observed. Variable load and generation circumstances are used to generate the simulation results.

Black Start Capability from Large Industrial Consumers

The way of control and operation of an electrical power system has been changing rapidly with the integration of renewable energy sources (RES). One of the emerging issues that require addressing is the capability of RES to participate in the restoration process upon a total or partial system failure. However, with the continuous shutdown of large-centralised generators, which traditionally provided the black start support together with the variability of RES, the restoration process becomes much more complex. Primarily, the RES should have enough capacity to energise the load at the time of the restoration. Nonetheless, due to significant advantages, there is an increasing trend to use RES to meet the local energy demand by large industrial customers. The flexibility of shifting loads together with the surplus of RE generation could support the system operator during the system energisation process after a blackout. This paper mainly focuses on identifying the capabilities and factors that should be accounted for to participate in the system restoration process by large industrial consumers. The case study conducted on a large-scale steel factory in the UK reveals the possibility of supporting the restoration process under the bottom-up approach.

교육비특별회계 순세계잉여금 실태와 영향 요인 분석: 불용액을 중심으로

The purpose of this study was conducted with the purpose of responding to external pressure to reduce local education finance, which was raised by inefficiency in the process of budgeting and executing the external local education finance, which is represented by a decrease in the school-age population and excessive net budget surplus. Accordingly, the current status of net budget surplus generation by year and factors influencing the occurrence of the special account for education expenses were analyzed, and policy improvement plans based on this were explored. As a result of the study, the total amount of net budget surplus in the special account for education expenses increased sharply in 2015 and then has been on a downward trend since 2019. Considering that the amount of tax revenue has continuously increased, this seems to be due to the offices of education’s efforts to reduce disuse of appropriation. It was found that the unused budget was mainly generated from reserve contingency fund, facility cost, and labor cost. In general, most of the unused budget came from the budget execution balance, which was due to the difference between successful bids, the reduction in contract review, and the inability to adjust the budget of the amount carried forward due to non-execution of construction during the semester. Based on these analysis results, increase efforts to organize the main budget of net budget surplus, stipulate regulations on the treatment and use of net budget surplus, make it mandatory to deposit a portion of net budget surplus into the rainy day fund, establish a plan for facility-related project expenses from a mid- to long-term perspective, and efforts to improve financial management efficiency through operation and early budget execution were. suggested.

A change in the air? The role of offshore wind in Australia’s transition to a 100 % renewable grid

Rapid decarbonisation of electricity production is required if Australia is to meet its obligations under the Paris Agreement. Critical to achieving this at low cost while maintaining system reliability is the selection of an appropriate mix of generation technologies to service electrical demand. Australia has seen extensive deployment of renewable energy technologies such as onshore wind and solar but has not yet seen the adoption of offshore wind technology. However, there is currently significant interest in developing this resource, with ongoing debate occurring about future technology costs and the potential of onshore renewables to meet electrical demand.This article presents the results of an investigation into the techno-economic impact of exogenously fixing offshore wind capacity on a future least-cost Australian National Electricity Market with 100 % renewable generation. An existing open-source cost optimisation model, National Electricity Market Optimiser, was used for the study.It was found that increasing the capacity of offshore wind in the generation mix leads to displacement of both onshore wind and solar generators. This is due to the greater magnitude and consistency of the offshore wind resource relative to onshore. Increasing offshore wind capacity therefore tends to reduce the total system generation capacity, as well as the amount of unused surplus generation. Using lowest published projections for future capital costs, inclusion of offshore wind was found to reduce total system costs. Using an average of future cost projections, total system costs were found to increase. However, adding up to 15 GW of offshore wind capacity to a 100 % renewable system would only impact total system costs by 5 %. Given the other potential advantages of offshore wind, namely closer siting to load centres, reduced need for onshore land resources, and the potential to transition existing fossil fuel workers, our results suggest that offshore wind may be a suitable candidate for inclusion in Australia’s transition to a low carbon electricity system, under a range of future cost scenarios.