Power System Expansion Research Articles

Optimal replacement of coal with wind and battery energy storage

Abstract Electric utilities are considering replacing their coal power plants with renewables and energy storage to reduce emissions. However, they have also expressed concerns about operational changes and system reliability brought by these replacements. Utilities in remote rural areas face more challenges as they also face energy insecurity while having limited interconnections to wider systems and reliance on imported fuels. Therefore, it is critical for remote utilities to understand different coal replacement approaches and their impacts on system expansion, operation and energy security. In this paper, we define and investigate three approaches to replace coal using wind and batteries: 1) replacing exact coal generation, 2) replacing at least coal generation, and 3) replacing total energy provided by coal. We develop a case study inspired by the small remote grid in Fairbanks, Alaska, which has a single limited interconnection with the grid south of it. We utilize a power system expansion and economic dispatch model that co-optimizes the capacities of wind and batteries required for each approach and the hourly dispatch of energy and reserves for one year. We further analyze the operational cost variability under fixed and fluctuating fuel prices. We find that replacing the exact coal generation requires minimal operational changes, but also significantly more wind and battery capacities. In contrast, replacing total energy provided by coal induces more cycling in other resources, challenging grids with limited flexibility-providing resources. However, replacing total energy provided by coal allows more generation variability in response to fuel price fluctuations, enhancing energy security.

Future Consumption Scenarios of Power Sector in Bangladesh

Future electricity demand is an essential prerequisite for planning the expansion of a power system. The purpose of this paper is to provide a forecast of electricity consumption in Bangladesh. Forecast is done here total as well as sector-wise consumption up to 2040 considering the base year 2009. The time series analysis to find the trend line by the method of Least Squares (LS) is applied in this study. We accumulated data from the annual reports of the Bangladesh Power Development Board for the years 2009 to 2023 and used that for forecasting purposes. For the convenient and policy purposes, the forecast is presented for every five years interval. The findings have significant implications with respect to energy conservation and economic development. As the study differentiated sector-wise projected growth of electricity consumption in Bangladesh, it has implications for the planners related to electricity distribution system. The findings can create awareness among the planners of power system expansion in Bangladesh to meet the continuous future development demand.

Integrated Long‐Term Expansion Planning and Short‐Term Operation Assessment in Brazil Considering Utility‐Scale Storage

ABSTRACTLong‐term power system expansion planning aligned with current sustainable development policies plays a pivotal role in achieving global targets for energy transition, particularly in developing countries. This paper presents a comprehensive long‐term expansion planning model for Brazil, taking into account decarbonisation pathways using OSeMOSYS integrated with Flextool. Four scenarios explore the potential benefits of increasing the share of variable renewable energy (VRE), specifically photovoltaic (PV) and offshore wind, to 40% of the total energy produced, both with and without a storage system. Results indicate that policies better aligned with net‐zero strategies do not impose a significant cost burden.

Bi-level expansion planning of power system considering wind farms based on economic and technical objectives of transmission system operator

Planning for the expansion of generation and transmission infrastructure, with a focus on integrating wind farms is presented in this study according to the goals of economic efficiency, operational performance, security, and reliability of the transmission system operator. The approach incorporates a bi-level optimization framework, with the upper level outlining the formulation of power system expansion planning to reduce construction and operational costs while adhering to the investment budget limits. In the lower-level model, which economic reliable-secure functioning is formulated for the transmission network. The objective function of the problem aims to minimize operational costs, energy losses, and anticipated energy not supplied, and the voltage security index. The constraints of this problem include AC optimal power flow model, security, and reliability limits. Scheme extracts a convex-linear model for the formulation using the conventional linearization technique. Pareto optimization driven by the aggregation of weighted functions results in a single-objective framework for the lower-level problem, and the Karush-Kuhn-Tucker technique presents a single-level model for the scheme. The approach utilizes stochastic optimization has been adopted to model load, wind farms, and network equipment availability uncertainties. Finally, the study cases yielded numerical findings that showcase the efficacy of the proposed scheme in achieving the desired economic, operational, security, and reliability status within the transmission network. This is particularly true in situations where there is appropriate generation and transmission expansion.

Green hydrogen exports in New Zealand and Chile can improve electricity supply security if configured as local energy insurance

Extreme weather events, for example, prolonged droughts, are increasingly stressing electricity systems and threatening the achievement of energy transition goals. At the same time, countries such as Chile and New Zealand are developing strategies to export renewable energy through green hydrogen. This paper economically evaluates the use of future green hydrogen exports as strategic storage under the logic of energy insurance, based on the assumption that Chile and New Zealand will adopt a hydrogen economy. Our first contribution is to compare the marginal costs of re-electrified green hydrogen, for different scenarios, to the value of lost load in New Zealand and Chile. We then determine the marginal cost of energy produced from green hydrogen based on projected production, transportation, and re-electrification costs for the year 2030. Finally, we estimate the eventual penalties that exporters would incur in the case of breaking their contracts and the overall resulting system costs of using hydrogen for system security. We found that re-electrifying hydrogen can be competitive with conventional technologies at 3 USD/kg. At 1.5 USD/kg, hydrogen is more competitive than fossil fuel-based technologies, for both New Zealand and Chile. Thus, in 2030, it could make economic sense for New Zealand and Chile to use hydrogen as a strategic reserve. The system cost of the proposed insurance scheme in 2030 ranges from 0.53 to 1.76 USD/MWh, which is small compared to total electricity costs. These values can be used for power system expansion and operation planning.

Interstate power interconnection along with carbon dioxide emission constraint collaboration: Effective tool for low-carbon electric power expansion in Northeast Asia

Interstate electric power integration with the formation of interstate electric ties and power interconnection in Northeast Asia has been studied for several years. Research has examined the directions, indicators, costs, and systemic (integration) benefits (technical, economic, environmental, etc.) of forming such ties and grids. Studies conducted in different Northeast Asia countries have shown that despite the significant investments required to create an interstate electric ties infrastructure, which serves as the basis for interstate power grids and electricity markets development, participants of these interstate power grids and markets gain substantial benefits. These include reduced needs for installed and reserve generation capacity, lower electricity prices, increased overall flexibility of power resources, and accordingly, greater capability to integrate renewable energy sources. This results in reduced carbon dioxide (CO2) emissions from fossil fuel power plants. The latter undoubtedly contributes to achieving the sustainable development goals set by the United Nations and reducing anthropogenic climate impact, which many countries globally (including Northeast Asia) have targeted via announced carbon neutrality by 2050–2060. The main target of the article is to conduct and present new multi-scenario study on forming a potential Northeast Asia’s interstate power grid under national and grid-wide (for the entire power system interconnection) carbon emission constraints. The mathematical model of electric power system expansion and dispatching was modified to account for carbon dioxide emission constraints and used for the study. The results of the study showed that the creation of interstate power grid in Northeast Asia accompanied by climate change collaboration among countries to control carbon dioxide emission would lead to effectively constraining of carbon dioxide emission in the subregion, which is the novelty of the study. The results of the study are useful and applicable for choosing particular ways, options, stages of formation and expansion of low-carbon power system interconnection in Northeast Asia.

An online dynamic security assessment integrated scheme for power systems based on sparse multinomial naive bayes and canonical correlation forest

With the expansion of power systems and renewable energies, the security of power systems is confronted with severe situations. In this research, an online integrated DSA scheme based on sparse multinomial naive Bayes (SMNB) and canonical correlation forest (CCF) is proposed. The SMNB-based feature selection process selects the key features according to the correlations between the system operating variables and the DSA classification labels. Then, the DSA model is obtained by training CCFs with the key features. Finally, the results of DSA can be provided by the model on the basis of the real-time data of phasor measurement units (PMUs) in the wide area measurement system (WAMS). The online DSA integrated scheme is tested on the IEEE 39-bus system and a practical 1648-bus system provided by PSS/E software. The test results show that the proposed scheme is suitable for online application with providing satisfactory assessment accuracy. Furthermore, topology change, data noise and missing data are also taken into account for the robustness tests of the integrated scheme.

Experimental analysis of a multi-phase resonance-based fault current limiter prototype under symmetrical and asymmetrical faults

Expansion of power systems and involving more distributed generation cause to increase in fault current levels. This paper presents a three-phase resonance-based solid-state fault current limiter (FCL) prototype that has series and parallel resonance modes developed to suppress fault currents of power systems. The laboratory-scaled prototype is located on a three-phase test circuit and has been examined with the fault types of three-phase, three phase-to-ground, two phase-to-ground, and phase-to-ground. The performance and effectiveness of the proposed series-parallel resonance-type fault current limiter (SPRFCL) are validated with the comparison of Matlab/Simulink simulations and experimental test results. Fault currents in different types of faults are limited to an allowable value at high rates and experimental results are considerably close to current values obtained from each fault simulation. Fault currents of faulted phases are restricted with the limiting rates ranging from 75 % to 85 % concerning prospective fault currents in the non-FCL situations. Short-circuit test results of the prototype of SPRFCL that is supplied from a 380 V grid revealed that it acts stable and successful operation regardless of fault type. Accordingly, it has a favorable circuit design for power system applications.

A Coordinated Control Strategy of Multi-Type Flexible Resources and Under-Frequency Load Shedding for Active Power Balance

With the increasing expansion of power systems, there is a growing trend towards active distribution networks for decentralized power generation and energy management. However, the instability of distributed renewable energy introduces complexity to power system operation. The active symmetry and balance of power systems are becoming increasingly important. This paper focuses on the characteristics of distributed resources and under-frequency load shedding, and a coordinated operation and control strategy based on the rapid adjustment of energy storage power is proposed. The characteristics of various controllable resources are analyzed to explore the rapid response capabilities of energy storage. The energy storage types are categorized based on the support time, and the final decision is achieved with power allocation and adjustment control of the energy storage system. Additionally, a comprehensive control strategy for under-frequency load shedding and hierarchical systems is provided for scenarios with insufficient active support. The feasibility of the proposed model and methods is verified via a multi-energy system case.

Towards CSP technology modeling in power system expansion planning

Power systems with a high level of renewable energy penetration face challenges due to the inherent properties of some renewable energy sources, such as their variability and uncertainty. These systems require reliable technologies capable of handling large ramps and flexibility needs. Concentrating Solar Power (CSP) has been identified as one solution, which has been researched and implemented in several countries. This paper presents a novel analysis and evaluation of the impacts of choosing an inadequate representation of CSP technology in power system planning tools. The current state of CSP in power system expansion planning in the literature is examined, providing a classification for the modeling of investment and operation of CSP plants. Based on a proposed analysis framework, different models and configurations for CSP plants are evaluated and applied to a 5-bus test system. One of the key findings is that the selected model highly impacts the computational effort (150% more processing time), the quality of the planning decision (14% more overall costs), and the total emissions (up to 52% more emissions). A storage-based model proves to be the most suitable option, considering the operation and investment costs, as well as computational burden. The selected model achieves a 1% error compared to the results obtained with a reference model, while also requiring 40% less computation effort. The proposed framework can be applied to other power system structures by choosing the best suited CSP modeling.

Enhanced proportional integral controller for DSTATCOM with particle swarm optimization algorithm in power system

Power system expansion planning is supported by using distributed generation (DG) instead of installing new main power system generators. The portability and autonomous operation of the DG make it capable of integrating into the distribution system. Power electronics devices for home loads, mainly electric vehicles, mobile phones, and laptops, introduce harmonics and related power quality issues to the distribution system. This load creates power quality issues like an increase in total harmonic distortion (THD) and a reduction in power factor. This paper uses the DG to supply important power electronics devices for the mitigation of power quality problems in distributed systems with non-linear loads, such as electric vehicles, called the “distributed static compensator (DSTATCOM)”. Wind and photovoltaic (PV) generators supply power to a common DC source. To improve power quality D-STATCOM powered by PV and wind energy systems at the DC link is incorporated. The direct axis/quadrature axis method (DQ method) controls the real and reactive components of the power. Proportional integral (PI) and particle swarm optimization (PSO) based PI controller parameter estimation are developed, and results are compared for power quality performance. In terms of improving power quality, the PSO-based parameter estimate of the PI controller performs better than the traditional PI controller.<br /><div class="extension_reset_css AnnotateNet_widget AnnotateReviewNotesButton" style="display: none; z-index: 2147483644;" data-id="ExtensionWidget"><div class="extension_reset_css AnnotateNet_widget annotateclickable" style="z-index: 8; display: none;" title="Resize" data-id="Widget"> </div></div>

Distributed Generation (DG) system using COPRAS method

Distributed Generation (DG) system. Distributed Generation (DG) power systems, Expansion of power systems in remote areas, and Very recently as a sustainable way of electrification popular. Depletion of conventional fossil fuels, Fuel price volatility, and emissions Awareness environment about reduction, Due to this its demand is increasing. DG systems have additional power quality challenges. There are many types of DG power sources that produce electrical power with different voltages at various frequencies. RES-Based Distributed Generation (DG) Systems are conventional energy systems In finding new modern solutions for planning have contributed Widespread use of DG is old and Defines new views, Current delivery system The only way to deal with the project Calling for more complex defenses. COPRAS (Complex Proportionality Assessment) is very Multiple criteria used in decision-making methods is one. This technique is different Decision making by researchers Used to solve problems. Investment cost, operating cost, Primary energy consumption, CO2 emissions. Energy storage system, fuel system, Wind Solar Hybrid System, Conventional System, PV energy storage system. Involvement of Distributed Generation (DG) system PV energy storage system ranked 1st, and the Conventional system also got 5th position.

Multifaceted Functionalities of Bridge-Type DC Reactor Fault Current Limiters: An Experimentally Validated Investigation

With the ongoing expansion and interconnection of electrical power systems, alongside the rapid proliferation of renewable distributed generations (DGs), the short-circuit extent in the power grid is experiencing a significant rise. Fault current limiters (FCLs) have been introduced in an effort to address this issue, ensuring the robustness and sustainability of expensive power system components when confronted with short-circuit faults. Among the various types of FCLs, bridge-type DC reactor fault current limiters (BDCR-FCLs) have emerged as one of the most promising options. While BDCR-FCLs have shown excellent properties in limiting harmful short-circuit currents, they are also advantageous in other respects. This paper investigates the supplementary functionalities of BDCR-FCLs as a multifaceted device towards the enhancement of the quality of supplied energy in terms of total harmonic distortion (THD) reduction, power factor (PF) correction, peak current reduction for nonlinear loads, and soft load variation effects, as well as their capability to limit fault current. To this aim, the capabilities of BDCR-FCLs have been studied through various simulated case studies in PSCAD/EMTDC software V5.0.1, in addition to experimental tests considering an AC microgrid connected to a DC system. The experimental and simulation investigations verify the superior multifaceted functionalities BDCR-FCLs introduce in addition to their excellent fault current-limiting capabilities. The results show that PF improved by 6.7% and 7%, respectively, in simulation and experimental tests. Furthermore, the current THD decreased by 20% and 18% in the simulation and experiment, respectively.

Multiobjective Stochastic Power System Expansion Planning Considering Wind Farms and Demand Response

In recent years, due to the increase in electricity consumption and environmental problems, power system expansion planning requires new technologies. In this regard, the incorporation of renewable energy sources (RESs) and utilization of demand response (DR) programs need disruptive variations in the present power system configurations. This paper proposes a mixed-integer linear robust multiobjective model for generation and transmission expansion planning (GEP-TEP) taking into account wind farms (WFs) and a DR program based on time-of-use pricing. The suggested model is presented via mixed-integer nonlinear programming (MINLP) at the first stage and then transformed into mixed-integer linear programming (MILP) using the Big M linearization technique. Moreover, long- and short-term uncertainties of load demand and WFs are incorporated into the recommended model to achieve more accurate results. The interval-based method is applied for taking into account long-term uncertainties while the scenario-based stochastic model is applied for modeling short-term uncertainties in the recommended GEP–TEP model. Lastly, the suggested model is investigated on various standard test systems to evaluate the effectiveness of the GEP-TEP model.

Developing a new flexibility-oriented model for generation expansion planning studies of renewable-based energy systems

This paper presents a flexibility-oriented generation expansion planning (GEP) model with the goal of increasing renewable energy penetration. The model incorporates GEP and unit commitment while considering improved reserve requirements. Utilizing GEP and unit commitment results in considering short-term operational constraints. Furthermore, given the increase in renewable portfolio standards (RPS) and the need for accurate reserve requirements determination, it is essential to consider improved reserve requirements in the proposed model. Moreover, this model utilizes a metric that measures power system flexibility deficiency and leads to flexible power system expansion by integrating it into the objective function. The flexibility-oriented GEP model is developed using mixed-integer linear programming and applied to a scaled-sized case study representing the national power system of Iran with a twenty-year planning horizon. The results show that neglecting improved reserve requirements leads to plans short on flexibility, and considering these requirements substantially declines the upward flexibility violation costs by 68% under the base scenario and 87% under increasing non-hydro RPS scenario. Furthermore, using the flexibility metric coupled with improved reserve requirements changes the optimal path for power system expansion and reduces the risk of flexibility deficiency. Also, increasing RPS by 35% would strongly depend on developing fast-response dispatchable generation units in the years before renewable energy resources expansion; however it doesn’t impose a significant extra cost of planning and the total cost will increase just by 9.43%.

InfrastructureModels: Composable Multi-infrastructure Optimization in Julia

In recent years, there has been an increasing need to understand the complex interdependencies between critical infrastructure systems, for example, electric power, natural gas, and potable water. Whereas open-source and commercial tools for the independent simulation of these systems are well established, frameworks for cosimulation with other systems are nascent and tools for co-optimization are scarce—the major challenge being the hidden combinatorics that arise when connecting multiple-infrastructure system models. Building toward a comprehensive solution for modeling interdependent infrastructure systems, this work presents InfrastructureModels, an extensible, open-source mathematical programming framework for co-optimizing multiple interdependent infrastructures. This work provides new insights into methods and programming abstractions that make state-of-the-art independent infrastructure models composable with minimal additional effort. To that end, this paper presents the design of the InfrastructureModels framework, documents key components of the software’s implementation, and demonstrates its effectiveness with three case studies on canonical co-optimization tasks arising in interdependent infrastructure systems. History: Accepted by Ted Ralphs, Area Editor for Software Tools. Funding: The work was funded by Los Alamos National Laboratory’s Directed Research and Development project “The Optimization of Machine Learning: Imposing Requirements on Artificial Intelligence” and the U.S. Department of Energy’s Office of Electricity Advanced Grid Modeling projects “Joint Power System and Natural Gas Pipeline Optimal Expansion Planning” and “Coordinated Planning and Operation of Water and Power Infrastructures for Increased Resilience and Reliability.” This work was carried out under the U.S. DOE contract no. [DE-AC52-06NA25396]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0118 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0118 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Incorporating externalities when optimising power system expansion plans

Power system expansion planning has traditionally been conducted in two phases: optimisation of the future generation system to satisfy forecast demands, followed by that of a complementary transmission system. However, it is now computationally realistic to optimise both aspects simultaneously, even for large and complex systems. At the same time, the range of candidate generation plant types to be considered has widened considerably, with the technical and economic characteristics of wind, solar and biomass plants now having to be compared with those of conventional thermal and hydro plants. It is also becoming increasingly important to take explicit account, within the planning process, of the so-called ‘externalities’ such as emission limits, budget constraints and demand-management measures, in addition to the environmental costs and secondary benefits associated with individual projects. This paper describes the results of a study to demonstrate the feasibility of explicitly considering a range of externalities when mathematically optimising integrated generation and transmission system expansion plans, using the Vietnamese power system as an example.

Moth flame optimization for the maximum power point tracking scheme of photovoltaic system under partial shading conditions

The dwindling reserves of fossil fuels have spurred the expansion of photovoltaic power systems, widely regarded as an alluring solution. Yet, a formidable challenge arises when it comes to optimizing the output of PV systems exposed to irregular irradiance stemming from external environmental factors. Consequently, this research endeavors to advocate the use of the Moth Flame Optimization (MFO) algorithm to search for the highest power output of a solar energy harvesting system. The distinctive behavior of moths proves instrumental in thorough searching of the feasible space, mitigating the risk of entrapment in local optima. To evaluate its efficacy, this algorithm’s performance is validated by comparing its outcomes with those of the Butterfly Optimization Algorithm (BOA). Both algorithms are subjected to experimentation to search for the Global Maximum Power Points (GMPPs) of the PV system under two distinct Partial Shading Condition (PSC) scenarios: Case 1 and Case 2. The results indicate that BOA tends to produce outcomes with a broader data dispersion range relative to the mean, unlike MFO. Specifically, for Case 1, the standard deviation values for MFO and BOA are 2.327040E−02 and 5.777913E−02, respectively, while for Case 2, they are 5.0567340E−02 and 8.519362E−02, respectively. Hence, the proposed approach demonstrates faster and more precise convergence.

Methods to improve reliability and operational flexibility by integrating hybrid community mini-grids into power systems

Decarbonization and decentralization are major trends in the transformation of conventional power systems. The increase of the penetration of renewable electricity generation into generation mix contributes to the reduction of greenhouse gas emissions. At the same time, one has to ensure that the reliability and operational flexibility as measured by respective metrics meet specified standards. This calls for a solution of a set of engineering, economic, and institutional problems, the list of which depends on the features specific to countries and regions in question. This is due to differences in the requirements established by technical regulations, the rules governing wholesale and retail electricity and capacity markets, the mix of electricity consumption, as well as the principles underpinning the management of capacity expansion and operation of power systems. The purpose of this article is to provide the rationale for the feasibility and efficacy of integrating hybrid community mini-grids into power systems. The balance of community mini-grids in terms of power and capacity allows them to operate both in the grid-connected and islanded modes without disrupting power supply to consumers. The main sources of electricity in hybrid community mini-grids are distributed generation (DG) facilities, including those based on renewables as well as energy storage systems (ESS). Load dispatching of community mini-grids is performed by an intelligent automatic control system (ACS) governed by decentralized algorithms, which provides coordinated operation of emergency control and power flow automatics. Integration of community mini-grids into power systems can be accomplished through several transmission lines that form an interconnection. The controlled flow of power through such an interconnection allows for significant system-wide technical and economic effects. We propose a technique to provide the rationale for the efficacy of creating community mini-grids. The technique is based on calculations of reliability metrics. The integration of hybrid community mini-grids into power systems makes it possible to increase the availability and uninterrupted supply of electricity to consumers, as well as the lifetime of power grid equipment.

Implementation of Renewable Energy and Nuclear-Hydrogen Plants in Local Power Systems (on the Example of the Republic of Sakha (Yakutia))

The ORIRES model of expansion and operation of electric power systems is modified to factor in electrolysis hydrogen plants as electricity consumers with variable demand, which improve operating conditions of the electric power systems and produce hydrogen. The modified model is used in optimization calculations of the implementation of nuclear-hydrogen plants and renewable energy sources in the local power systems of Yakutia (Western, Central, and Southern) in the context of their expansion up to 2035. The calculations showed the technical and economic feasibility of these plants in local power systems of Yakutia, and the performance capabilities of these systems themselves. The scope of implementation of renewable and nuclear-hydrogen plants into the power systems of Yakutia was identified, their daily and seasonal load was calculated, and the conditions for such an implementation and the necessary levels of incentives to ensure it were determined.