Grid Expansion Research Articles

How flexible electrification can integrate fluctuating renewables

To phase out fossil fuels, energy systems must shift to renewable electricity as the main source of primary energy. In this paper, we analyze how electrification can support the integration of fluctuating renewables, like wind and PV, and mitigate the need for storage and thermal backup plants. Using a cost-minimizing model for system planning, we find substantial benefits of electricity demand in heating, transport, and industry adapting to supply. In Germany, flexible demand halves the residual peak load and the residual demand and reduces excess generation by 80%. Flexible operation of electrolyzers has the most significant impact accounting for 42% of the reduction in residual peak load and 59% in residual demand. District heating networks and BEVs also provide substantial flexibility, while the contribution of space and process heating is negligible. The results are robust to restrictions on the expansion of the transmission grid.

Model Predictive Control of Grid-Connected Battery Systems to avoid PV-induced Overvoltage

Photovoltaic (PV) power plants are currently built at a high rate, both small ones for single family houses and large-scale plants with a power output in the MW range. This development accelerated even more since the beginning of the energy crisis in 2021. Due to intermittent energy production, large voltage swings may result in the electrical grid, which are challenging for grid and operators. We are considering the problem of overvoltage in times of excessive PV production, which is well documented in the literature. To avoid overvoltage, without PV-curtailment or grid expansion, grid-connected battery systems are proposed. The research focus is on advanced control strategies for such systems which charge and discharge at appropriate times to reduce the overvoltage in the grid while simultaneously minimizing the required battery capacity. The work presented extends a previous contribution of the authors. The analysis was done in a simulation environment (MATLAB/Simulink).

Methodology for integrating flexibility into realistic large-scale distribution network planning using Tabu search

A successful energy transition will be firmly based on the effective integration of distributed energy resources and on the integration of new flexibility providers into the energy system. To make this possible, a deep transformation in the design, operation and planning of power distribution systems is required. Currently, a lack of comprehensive planning tools capable of supporting operators in their investment plan options exists. As a result, reinforcements of conventional grid assets are common solutions put in place. This paper proposes a methodology to obtain cost-optimal distribution network expansion plans, by modelling a single-stage distribution network planning tool, using conventional assets as well as flexibility contracting from demand response. A Tabu Search metaheuristic has been implemented in order to solve the optimization problem. A case study based on a realistic large-scale city network model is presented, for a planning horizon of ten years with significant load growth due to electromobility penetration. Results show that, in the case study analysed, the use of load flexibility in combination with conventional reinforcements can reduce the total expansion network cost by about 7.5 %. Furthermore, a sensitivity analysis on the cost of flexibility contracting is undertaken. Remarkably, the methodology presented generalises to further alternative solutions by providing a straightforward financial benchmark between the latter and conventional grid expansion.

Collaboration, decarbonization, and distributional effects

We use a CIB analysis and a CGE model to develop decarbonization scenarios for the European power market. Our CIB analysis reveals qualitative scenarios that differ in the level of political (stringency of climate policy) and physical collaboration (transmission grid expansion). The CGE model quantifies those scenarios for further usage in the power market model EUREGEN to analyze related distributional effects across heterogeneous countries as well as between consumers and producers. EUREGEN predicts that consumers experience considerably higher electricity prices in the future in all scenarios, whereas producers observe higher rents. Electricity prices are lowest in the least collaborative future. Producer rents in turn are highest in the most collaborative one. Patterns hugely differ by country, making 13 countries to profiteers of the least collaborative future and 12 countries to profiteers of the most collaborative one. Only 3 countries profit from medium collaboration. Countries that profit from the most collaborative future experience substantially higher producer rents. Countries that profit from the least collaborative one in turn experience lowest electricity prices.

A New Discretization Scheme for the Non-Isotropic Stockwell Transform

To avoid the undesired angular expansion of the sampling grid in the discrete non-isotropic Stockwell transform, in this communication we propose a scale-dependent discretization scheme that controls both the radial and angular expansions in unison. Based on the new discretization scheme, we derive a sufficient condition for the construction of Stockwell frames in L2(R2).

Sector Coupling through Vehicle to Grid: A Case Study for Electric Vehicles and Households in Berlin, Germany

A key factor in limiting global warming is the conversion of conventional electricity generation to renewable energy sources. However, a major obstacle is that renewable energy generation and energy demand often do not coincide in time, and energy must therefore be stored temporarily. Vehicle to grid (V2G) can be used to store excess renewable energy in battery electric vehicles (BEVs) and feed it back into the electric grid when needed. For effective V2G operation, the grid may have to be expanded, as the energy needs to be transported to BEVs. However, the grid should only be strengthened where renewable energy demand exceeds current grid capacity due to high grid expansion costs. This requires a method that determines the spatial distribution of V2G potential at a high resolution. Since such a method has not yet been reported in the existing literature, and so is developed in this paper. The method is demonstrated for the city of Berlin and its 448 sub-districts. For each sub-district, the method allows determining the percentage of residential and BEV energy demand that can be met by renewables if V2G is deployed, and answers the question of whether a full renewable supply is possible. The results show that BEVs can be effectively used as intermediate storage for renewable energy. If 30% of the BEVs participate in V2G, more than 99% of the energy demand of households and BEVs in Berlin can be covered by renewables on certain days. On the other hand, V2G deployment increases the average peak load in the districts by up to 100% and results in a nearly double load on vehicle batteries. High shares of renewable energy can be observed in districts with a high degree of motorization, which are predominantly found in the outskirts of the city.

Multicriteria Decision-Making Approach for Optimum Site Selection for Off-Grid Solar Photovoltaic Microgrids in Mozambique

Given the constraints associated with grid expansion costs, limited access to reliable electricity, and priorities in addressing the climate agenda and Sustainable Development Goals in low-income countries, microgrids and off-grid solar projects represent a viable solution for rural electrification. This type of solution has the advantage of being less expensive than conventional technologies, is rapidly scalable, affordable, environmentally sustainable, and can play a critical role in empowering rural communities. In this context, this study proposed a spatial framework for off-grid solar energy planning based on a Geographical Information System and Boolean logic, Fuzzy logic, and Analytic Hierarchy Process Multicriteria Decision-Making methods. The results of the applied methodology show that the selection of optimal locations for off-grid solar photovoltaic microgrid projects in Mozambique is significantly influenced by the following order of criteria: climatology, orography, technical and location, social, and institutional criteria. Geographically, about 49% or 344,664.36 km2 of the total study area is initially suitable for an off-grid solar photovoltaic microgrid project; 4% is low suitable, 14% is moderately suitable, 18% is suitable, and 13% is highly suitable. However, 51% of the ranked areas fall into the not feasible and restricted areas, mainly in conservation areas, protected areas, and areas at high risk of flooding and cyclones, covering a total of 387,005.5 km2 within the study area. In general, the approach helps to reduce uncertainty and increase flexibility to identify appropriate sites and strengthen indicators of sustainable development impacts of decentralized rural electrification.

Death spiral of the legacy grid: A game-theoretic analysis of modern grid defection processes

Decreasing costs of distributed generation and storage, alongside increasing network charges, provide consumers with a growing incentive to defect from the main grid. On a large scale, this may lead to price inflation, hindrance of the energy transition, and even a "death spiral"- a domino effect of disconnections. Here, we develop a game-theoretic framework that demonstrates how conflicting interests among consumers - an aspect that previous studies overlooked - may lead to complex dynamics of grid defection. Our results reveal that although individual consumers benefit from staying connected at the distribution level, the defection of small energy communities from the grid may lead to the defection of larger communities. We also demonstrate that centralized design approaches may lead to inefficient outcomes, e.g., redundant grid expansions, because of the inherent inability to predict potential defections. However, we indicate how, by properly incorporating defection considerations into the grid's design, social welfare can be improved.

Replacing gas boilers with heat pumps is the fastest way to cut German gas consumption

The supply security of fossil gas has been disrupted by the Russo-Ukrainian War. Decisions to relocate the production and transport of gas have become so urgent that new long-term contracts are imminent that undermine the Paris Climate Agreement. Here, we simulate how quickly the addition of renewable electricity and the installation of heat pumps can substitute enough gas to reduce supply risk, while taking a decisive step towards meeting the Paris Agreement. Our bottom-up modelling, using Germany as an example, shows technical pathways on how installing heat pumps is one of the fastest ways to reduce gas consumption, in addition to reducing the load hours of gas-fired power plants. With targeted efforts, maximally 60% of gas from the Russian Federation can be substituted by 2025 with heat pumps and grid expansions, and enough electricity will remain available that the phase-out of coal and the entry into e-mobility will still be practicable.

Exploring long-term electrification pathway dynamics: a case study of Ethiopia

The Open Source Spatial Electrification Tool (OnSSET) is extended to provide a long-term geospatial electrification analysis of Ethiopia, focusing on the role of grid- and off-grid technologies to increase residential electricity access under different scenarios. Furthermore, the model explores issues of compatibility between the electricity supply technologies over time. Six potential scenarios towards universal access to electricity in the country are examined based on three pathways; the Ambition pathway sees high demand growth and universal access achieved by 2025, the Slow Down pathway follows a lower demand growth with a slower electrification rate and with a higher share of off-grid technologies, and the Big Business pathway prioritizes grid electricity first for the industrial sector, leading to slower residential electrification. The results show a large focus on grid extension and stand-alone PV deployment for least-cost electrification in case of low grid-generation costs and uninhibited grid expansion. However, in case of a slower grid rollout rate and high demand growth, a more dynamic evolution of the supply system is seen, where mini-grids play an important role in transitional electrification. Similarly, in the case where grid electricity generation comes at a higher cost, mini-grids prove to be cost-competitive with the centralized grid in many areas. Finally, we also show that transitional mini-grids, which are later incorporated into the centralized grid, risk increasing the investments significantly during the periods when these are integrated and mini-grid standards are not successfully implemented. In all cases, existing barriers to decentralized technologies must be removed to ensure off-grid technologies are deployed and potentially integrated with the centralized grid as needed.

Optimal grid expansion under future electricity demand for groundwater irrigation in Ethiopia

Ethiopia is a lower-income country with an agrarian based, fast-growing economy that is susceptible to climate change impacts. As the nation continues to develop, domestic electricity consumption and electricity export opportunities will increase alongside a growing electricity demand for groundwater irrigation to mitigate the effects of drought. There are upcoming mega-dams– the Grand Ethiopian Renaissance Dam, Genale Dawa III, and Koysha – that will triple the electricity generation capacity. However, the central electricity grid is not sufficient to efficiently utilize this new capacity. We model future grid expansion scenarios by building a regional-scale linear optimal power flow model based on a transshipment representation of power flow that guides cost-optimal generation operations and transmission expansion, while satisfying competing electricity demand for domestic electricity consumption, groundwater irrigation, and international electricity export.We first evaluate cost-optimal generation and transmission expansion for a baseline case, with an estimate of current Ethiopian electricity demand. We then consider five potential future demand scenarios. These demand scenarios include estimates of both present and future domestic electricity demand, multiple levels of productive electricity demand for groundwater irrigation, and demand for international exports. Compared to the baseline, seasonal capacity factors for generators in the five model scenarios increased when collocated with an increase in electricity demand except for the generators that already operated at maximum capacity. All scenarios with higher domestic regional demand than the baseline surpass the transmission expansion planned by the Ethiopian Electric Power Corporation, independent of changes in irrigation and export demand. Our analysis suggests that the current expansion plan is not sufficient to meet future demand. Our research contributes to the literature by creating an optimal power flow model that can be applied in data-poor environments to model endogenous electricity infrastructure decisions under different scenarios of internal and external demand.

Review on Smart Charging of Electric Vehicles via Market-Based Incentives, Grid-Friendly and Grid-Compatible Measures

Smart charging of electric vehicles is a promising concept for solving the current challenges faced by connecting mobility and electricity within the context of the ongoing sustainable energy transition. It allows cost savings for the expansion and operation of the power grid and a more efficient use of renewable energies. However, wide implementation of smart charging requires further work on technical and regulatory issues and further development of standards, especially an end-to-end consistency of the control signals. A fully automated process, as well as customisable services and flexible tariffs, would also facilitate wider market penetration. The novelty of this paper is the consensus of German pilot projects funded within the German programme “Elektro-Mobil” on the communication channel between all stakeholders for the use cases of smart charging based on market price incentives. Within this consensus, the projects have illustrated how specific standards can facilitate the communication between smart charging stakeholders, become a reality in the pilot projects and should be applied to further use cases in the low-voltage network. This consensus results in a white paper. On this basis, the adjustment of the standards can be made to ensure the consistency of the control signals from the beginning of the control process up to the end. In an advanced Edition, solutions for the prioritisation and orchestration of the different control signals could be designed.

Research on Construction Technology of Deep Foundation Pit of High Voltage Transmission Line in Plateau Area

With the further expansion of China power grid, it is the current and future trend of power system development to set up high-voltage or even ultra-high-voltage transmission lines. Because the construction environment of high-voltage transmission lines is very complex and changeable, how to ensure the construction quality and progress of transmission lines according to the construction drawings provided by the design unit is the key to the construction of transmission lines. The quality level of deep foundation pit excavation is a representative factor that profoundly affects the construction quality level of high-voltage transmission line projects in plateau areas. Only by managing the construction quality of all sub-projects in the power system can the stability of power operation be effectively guaranteed. This paper expounds the key points of deep foundation pit excavation construction technology, in order to analyze the deep foundation construction technology of high-voltage transmission lines in plateau area, and provide theoretical support for the deep foundation pit construction of high-voltage transmission lines in plateau area.

Techno-economic analysis of battery storage systems and hydrogen-based storage systems as an alternative to grid expansion in the medium voltage grid in Germany

<abstract> <p>The decentralization of the energy system in Germany is leading to enormous investments in grid expansion, as the current regulation creates an obligation to expand the power grid to eliminate bottlenecks. Meanwhile, opportunities to leverage grid-friendly control of storage systems are neglected to alleviate the need for investment. For this reason, it is necessary to investigate intelligent alternatives to grid expansion, such as storage systems, to efficiently integrate distributed technologies into the power system and reduce the need for grid expansion. In this work, two representative configurations of a medium voltage grid in Germany are developed for the years 2022 and 2050, and different storage systems are compared economically with the grid expansion in a model-based simulation. Hydrogen storage and battery storage were chosen as storage systems. The results show that grid expansion is the least expensive option if only the grid expansion costs are included in the analysis. However, if additional uses for the storage systems are considered, the battery storage systems are more economical. While in the scenario for 2050 the grid expansion causes costs of approx. 56,000 EUR per year, revenues of at least 58,000 EUR per year can be achieved via the revenue opportunities of the battery storage, representing a 3.5% margin. Heat extraction, arbitrage trading, and avoidance of grid expansion in superimposed grid levels were integrated as additional revenue streams/sources. A robust data basis and cost degressions were assumed for the simulations to generate meaningful results. Overall, hydrogen storage systems are economically inferior to battery storage systems and grid expansion for this use case. The results demonstrate the complexity of analyzing the trade-offs in terms of storage as an alternative to grid expansion as well as the opportunities presented using battery storage instead.</p> </abstract>

Security-constrained robust dynamic power system planning with discrete recourse

In this study, we present a two-stage robust optimization model for dynamic generation and transmission expansion planning considering discrete recourse decisions and n − K security constraints. Unlike the mainstream literature, our approach exactly considers cost non-convexities, binary commitment decisions, and security constraints. By customizing a nested column-and-constraint generation procedure, we compute this complex problem accurately. On two test systems, we illustrate the efficacy of the method and the impacts of security constraints, and the discreteness of recourse decisions on grid expansions. • A robust dynamic expansion planning model for co-optimizing generation capacity and transmission network. • Modeling uncertainty of demand, renewable generation, and outage status of power system components. • A decomposition method based on a nested column-and-constraint generation procedure.

A Review of Microgrid Energy Management and Control Strategies

Several issues have been reported with the expansion of the electric power grid and the increasing use of intermittent power sources, such as the need for expensive transmission lines and the issue of cascading blackouts, which can adversely affect critical infrastructures. Microgrids (MG) has been widely accepted as a viable solution to improve grid reliability and resiliency, ensuring continuous power supply to loads. However, to ensure the effective operation of the Distributed Energy Resources (DER), Microgrids need to have Energy Management and Control Systems (EMCS). Therefore, considerable research has been conducted to achieve smooth profiles in grid parameters during operation at optimum running cost. This paper aims to provide a review of EMCS techniques that have evolved in recent years. Firstly, the fundamentals of microgrids are discussed for a general overview of the field. Then, a critical literature review is undertaken for the various methods applied for EM optimization in microgrid applications. Multiple factors have been explored in the objective functions throughout this review, including MG daily operational costs, energy storage degradation, revenue through trading with the grid or other parties, and Greenhouse Gas (GHG) emissions. A review of control systems has been conducted next by categorizing them based on the different applications in MGs for stable operation. This paper also focuses on IEEE standards related to MG operation and control to facilitate other researchers to build upon a standardized set of rules and to enhance the interoperability of the diverse EMCS techniques.

Geomagnetically induced current uncertainty quantification based on the earth conductivity models constructed by the Kriging method

• Proposed and verified the superiority of Kriging method in constructing earth conductivity model. • Illustrate the necessity of uncertainty analysis for GIC. • Obtained the sensitivity of GIC input parameters(transformer parameters, transmission line parameters and ground resistance parameters) in 1000kV UHV Northern China power grid. With the expansion of power grid, the hazard of geomagnetically induced current (GIC) has attracted more attention. Due to the small number of Magnetotelluric detection points, the earth conductivity model based on limited data cannot be adapted to the GIC calculation of large-scale power grids. In addition, it is necessary to consider the effect of simultaneous changes in multiple input variables on GIC calculation results. Therefore, this paper presents a method for modeling the conductivity of the earth which is used in the case of less data, and uses the model to quantify the uncertainty. Based on the existing Magnetotelluric data in Northern China, the conductivity model within the power grid region is established using the Kriging method. The uncertainty quantification model of the GIC is constructed based on the Polynomial Chaos Expansions(PCE) method. The uncertainty quantification analysis is carried out for the 1000 kV ultra-high voltage Northern China Power Grid. The statistical information of the GIC and its sensitivity to each input parameter are obtained.

Target-Value-Competition-Based Multi-Agent Deep Reinforcement Learning Algorithm for Distributed Nonconvex Economic Dispatch

With the increasing expansion of the power grid, economic dispatch problems have received considerable attention. A multi-agent coordinated deep reinforcement learning algorithm is proposed to deal with distributed nonconvex economic dispatch problems. In the algorithm, agents run independent reinforcement learning algorithms and update their local Q-functions with a newly defined joint reward. The double network structure is adopted to approximate the Q-function so that the offline trained model can be used online to provide recommended power outputs for time-varying demands in real-time. By introducing the reward network, the competition mechanism between the reward network and the target network is established to determine a progressively stable target value, which achieves coordination among agents and pledges the losses of the Q-networks to converge well. Theoretical analysis is given and case studies are conducted to prove the advantages compared with existing approaches.

A Novel Doubly-Green Stand-Alone Electric Vehicle Charging Station in Saudi Arabia: An Overview and a Comprehensive Feasibility Study

In Saudi Arabia, the energy sector is presently the most significant contributor to carbon emissions, followed by the transportation sector, which contributes about 26% of the gross greenhouse gas emissions. The adoption of electric vehicles (EVs) in the transportation sector worldwide is one way to bring about a global green solution that can support the decarbonization of the environment, which now constitutes a new electric power demand for the utility grid network. To preserve the environment, and reduce the pressure on the existing grid network, we propose the utilization of EV charging stations (EVCSs) in off-grid locations. It is essential to have an alternative stand-alone renewables-based electrification framework to secure the charging demand needed for the electric vehicles. The present study performs a techno-economic investigation of a novel off-grid scheme that combines renewable energy resources to provide clean electricity for EV charging stations. The optimized system for the EVCS is compared with the alternative option of grid extension using economic criteria evaluation metrics and distance limitations. The optimization and comparative analysis results reveal that the option of an optimum stand-alone hybrid charging station is an economical, sustainable, and eco-friendly alternative to the option of grid expansion.

The Investment Effects of Market Integration: Evidence From Renewable Energy Expansion in Chile

We study the investment effects of market integration on renewable energy expansion. Our theory highlights that market integration not only improves allocative efficiency by gains from trade but also incentivizes new investment in renewable power plants. To test our theoretical predictions, we examine how recent grid expansions in the Chilean electricity market changed electricity production, wholesale prices, generation costs, and renewable investments. We then build a structural model of power plant entry to quantify the impact of market integration with and without the investment effects. We find that the market integration in Chile increased solar generation by around 180%, saved generation costs by 8%, and reduced carbon emissions by 5%. A substantial amount of renewable entry would not have occurred in the absence of market integration. Our findings suggest that ignoring these investment effects would substantially understate the benefits of market integration and its important role in expanding renewable energy.