Transmission Line Expansion Research Articles

Source‐storage‐transmission planning method considering carbon emission responsibility allocation

AbstractFair sharing of carbon responsibility is crucial to achieve the goal of low‐carbon transformation and dual‐carbon power system. In response to the current issue of a certain proportion of joint responsibility between source and load, it does not comply with the principle of “who causes who bears”. This thesis proposes a source storage transport coordinated planning method for allocating carbon responsibility from a planning perspective. Firstly, based on the basic principle of “who causes, who bears”, it classifies and holds accountable various stakeholders, establishes reasonable and fair allocation principles including reward and punishment indicators, and a dual carbon responsibility cost allocation rule for electricity balance and power balance in the power system; Secondly, based on the previous works, a source storage network joint planning model which comprehensively considers the investment cost of conventional thermal power installation, energy storage investment, wind abandonment penalty cost, transmission line expansion cost, and carbon emission responsibility cost is constructed. Finally, taking the Garver‐6 node system as an example, the effectiveness and feasibility of the proposed method were verified by comparing it with the source storage and transportation planning method that does not consider carbon responsibility allocation.

Autonomous Control of Voltage and Frequency in Parallel Inverters of Microgrid

Integration of Distribution Generations (DGs) provides flexibility in power transmission. DGs reduce expenditure, expansion of transmission lines and transmission loss. DGs can work separately from the main grid with local loads and form a microgrid. In grid-connected mode, the voltage and frequency of the microgrid are regulated by the main grid. Voltage and frequency regulation in the islanding microgrid are crucial. This paper presents voltage and frequency control techniques for parallel inverters in microgrid. The proposed model works on close loop control of inverters and it can be used for plug-and-play operation of microgrid. The Microgrid model is developed in MATLAB/Simulink and the performance of the system is analyzed in grid-connected mode and isolation mode.

Energy expansion planning with a human evolutionary model

This study presents a novel method for planning the expansion of transmission lines and energy storage systems while considering the interconnectedness of electricity and gas networks. We developed a two-level stochastic planning model that addresses both the expansion of transmission and battery systems in the electrical grid and the behavior of the gas network. This research explores the challenges and effects of integrating high levels of renewable energy sources while ensuring security within both networks. Our model uses a stochastic mixed-integer non-linear programming approach. To solve this complex model, we applied the Human Evolutionary Model (HEM). We tested our approach on two case studies: a simple 6-node network and the more complex IEEE RTS 24-bus network for the electricity grid, combined with 5-node and 10-node gas networks, respectively. The results demonstrate the effectiveness of our model, particularly in scenarios where connections in the power and gas networks are disrupted, preventing load shedding even when integrated network connections are cut.

Synergies and competition: Examining flexibility options in the European electricity market

The electricity market transitions from a market clearing in which flexible generation meets inflexible demand to one in which inflexible generation meets flexible demand. Consequently, new types of flexibility are needed to balance generation and demand. This paper mainly aims to analyse competition and synergy between various flexibility options in the electricity market. The developed European electricity market model maximises the joint socio-economic welfare of the electricity and the hydrogen market. Transmission grid,- storage expansion, electric vehicle demand side flexibility and hydrogen sector coupling are flexibility options. This work examines the implementation of different flexibility options in the bidding zones Austria and Germany. Austria, with a very high storage capacity in the alpine arc and Germany, with massive wind turbine capacities serve as representative case study. Results show that the storage location heavily influences the corresponding socio-economic welfare increase. Hence, location-dependent synergy and competition between storage and transmission line expansion can occur. In contrast, sector coupled hydrogen production and storage expansion compete with each other as both will reduce very low electricity prices. Demand-side flexibility primarily benefits end-users while producer surplus reduces. In combination with storage expansion, further positive synergistic effects for end-users occur. The combination of storage expansion and demand-side flexibility can replace transmission line expansion and vice versa if used comprehensively. Further efforts could address the evaluation of these effects if the individual flexibility providers aim for something other than a system-wide but individual optimum.

A multi-scenario evaluation of the energy transition mechanism in the Philippines towards decarbonization

The Philippines relies heavily on fossil fuels for energy, posing environmental issues. To counter this, the study suggests increasing the use of renewable energy sources like wind and solar power. By optimizing the electricity supply mix, the study shows that coal usage can be reduced by 37.23%, with solar power accounting for 20.07% and wind power accounting for 8.83% without using Battery Energy Storage System (BESS). By incorporating Battery Energy Storage Systems (BESS) and scaling up the utilization of solar and wind power, which is aligned with the country's 2030 target, coal consumption can be reduced by 30.44%. However, transmission expansion may have limited effects due to the country's archipelagic nature. Therefore, a decentralized approach is necessary to minimize coal usage and encourage renewable energy sources. The study uses linear programming optimization methods to explore scenarios that can mitigate climate change by increasing solar and wind power use, reducing coal usage, and investigating the benefits of transmission line expansion and energy storage integration for enhancing grid flexibility.

Assessment of Environmental and Social Impact of Benin-delta Power Transmission line Expansion Project

This study examined the environmental and social impacts and household vulnerability of the 107 km Benin-Delta (Ughelli) 330 kV power transmission line (TL) expansion project right of way (ROW). Questionnaires were administered to 56 communities and 344 households to obtain information on their livelihood and the perceived environmental and social impacts of the TL expansion. Results revealed the TL on land use, community socio-cultural and health Status, employment and opportunities, community agitation and social economic status, they were found to be high, low, beneficial, medium and low in that order. Loss of land and economic trees were identified as the highest impacts of the project. All communities within the sphere of influence of the project had encroached on the existing ROW. The most vulnerable groups affected by the project are the non-indigenous elderly, widows and female-headed households, children, herdsmen, unemployed and those that have lost their lands and are now without means of livelihood. The valuation of assets and losses suffered suggests the need for resettlement and compensation. Specific mitigation measures which could help ameliorate suffering of the economically vulnerable households should be put in place.

Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach

AbstractIntegrated generation, transmission, and storage expansion planning (IGT&SP) is the cornerstone to realize low‐carbon transition considering security constraints in the long run. A novel IGT&SP planning scheme is proposed to balance the planning cost, i.e. renewable energy sources (RESs) and energy storage systems, based on the distributionally ambiguity sets. A novel decision‐dependent ambiguity set is proposed to capture the relation between the uncertainties of RES output and long‐term planning. A two‐stage risk‐averse distributionally robust optimization is formulated, where the RESs, energy storage systems, and transmission line expansion are optimized in the first stage and a unit commitment problem is proposed in the second‐stage optimization to assess the performance of the expanded system. This problem is reformulated into a two‐stage optimization problem with complete mixed‐integer recourse, where the state variable is binary. A novel enhanced Benders decomposition algorithm is proposed to solve the IGT&SEP efficiently, where the cutting planes are generated by a primal‐dual relaxation of the recourse problem. Simulations are conducted on the modified IEEE‐30 test system and modified IEEE‐118 test system. Compared with adjustable robust optimization and L1‐norm Wasserstein distance‐based distributionally robust optimization, numerical results verify the effectiveness of the proposed IGT&SP, together with the solution algorithm.

Secure expansion of energy storage and transmission lines considering bundling option under renewable penetration

This paper presents a multi-stage expansion model for the co-planning of transmission lines, battery energy storage (ES), and wind power plants (WPP). High penetration of renewable energy sources (RES) is integrated into the proposed model concerning renewable portfolio standard (RPS) policy goals. The possibility of bundling existing transmission lines to uprate power flow capacity is considered. Renewable energy curtailment and load shedding are included in the model to assess the system operation more precisely. Battery ES devices are co-planned to defer transmission expansion and renewable management. To make the time complexity of the problem tractable and capture the uncertainties of load and RES in an hourly resolution, a chronological time-period clustering algorithm is used to extract the representative hours of each planning stage. Additionally, the flexible ramp reserve is utilized to handle the uncertainty of RES. An accelerated Benders dual decomposition (BDD) algorithm is developed to solve the proposed model mixed-integer linear programming (MILP) formulation. The N-1 security criterion is evaluated by considering a designed contingency screening (CS) algorithm to identify higher risk contingencies. The effectiveness of the proposed co-planning model is evaluated using IEEE RTS 24-bus and IEEE 118-bus test systems.

Analyzing congestion surplus distribution based on social welfare optimization

The distribution of congestion surplus affects not only the short-term economic interests of stakeholders in the power spot market, but the improvement of social welfare in the long run. At present, the congestion surplus in mature electricity spot markets of developed countries is usually returned to the power users or power generation enterprises according to established proportions. Although this method helps achieve rational distribution of congestion surplus, it does not offer a solution to the congestion problem and cannot achieve maximized social welfare. In light of the principles of welfare economics, we propose in this paper injecting the congestion surplus into the capital pool of the power grid as a transmission line expansion fund to fundamentally solve the power transmission congestion problem. Modeling results and case studies presented in our work verified that our proposed distribution model could achieve Pareto optimization. Finally, combining the power transmission and distribution (PTD) pricing and supervision method, this paper puts forward the method for use and supervision of congestion surplus on the power spot market to reach optimal allocation of resources.

Expansion of high-voltage overhead transmission lines to remote areas

<span>Delivering electrical energy to remote areas is one of the essential things in our modern world. Choosing the optimal route is one of the most critical factors contributing to reducing the power transmission system's cost. Other influencing factors such as the optimum alloy of the conductor wires are difficult to change, so only the aforementioned factor was adopted. In this paper, the optimized potential field algorithm is employed to determine the sub-optimum path that the transmission line should be installed. The best line for the towers is not necessarily the shortest or the cheapest one. Sometimes the best locations for the towers of the transmission lines coming according to the safety regards. It can be said that the best trajectory is a combination of several factors, including the length of the track in addition to other influencing factors depending on the work environment.</span>

APPLICATION OF VEGETATION INDEXES TO ASSESS CARBON STOCK

This was objectively conducted to estimate the carbon stock, to show the relation between carbon stock and indices and to assess the factors affecting carbon stock in community forests. Three community forests (CFs) namely Gumalchowki, Mahakalsthan and Mahalaxmi of Chandragiri Municipality in Nepal were selected as research sites. Altogether 135 plots were randomly established to collect data from the field. The biomass was calculated using Chave et al., equation which was converted into carbon stock multiplying by default value 0.47. The values of Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI) and Infrared Percentage Vegetation Index (IPVI) were calculated and regression equation between the indices and carbon stock was performed. The result showed that total above ground carbon stock was highest in Mahalaxmi CF with 30.42 ton/ha, followed by Mahakalsthan CF with 22.62 ton/ha and comparatively lowest with 21.55 ton/ha in Gumalchowki CF. The regression analysis between carbon stock and indices showed significantly and positive correlation. The R2 value of NDVI of Gumalchowki, Mahakalsthan and Mahalaxmi CF were found to be 0.51, 0.54 and 0.58, also, RMSE value of CFs were 1.41, 1.36 and 1.91 respectively. Principal component analysis showed that road construction, transmission line expansion, soil erosion, encroachment, disease, weeds, recreation, illegal logging are the major factors affecting carbon stock in all three community forests. Keywords: Carbon, Nepal, Community Forests.

Joint expansion planning of distribution network with uncertainty of demand load and renewable energy

Rational planning plays a key role in developing and improving operation security and stability of distribution networks (DNs). This paper proposes a novel method to solve the expansion of transmission lines (TLs) and the allocation of distributed generators (DGs) considering the uncertainty of load demand and renewable energy. The spanning-tree is a theoretical method specifically tailored to guarantee the radiality operation of distribution networks. Also, to guarantee the stability and reliability of the network, the probability function is used to describe the stochastic nature of load behavior and renewable sources fluctuation. Thus, the most proper installation location and time for TL and DG assets can be identified by modeling the joint expansion planning. The objective of the proposed model is minimizing the present value of the total social costs, including the cost of investment, purchasing energy, and environmental benefits. This mixed-integer nonlinear problem (MINLP) optimization model is solved based on GAMS environment. The effectiveness and scalability of this model is validated and illustrated based on the IEEE RTS-24 system.

수요자원 인센티브를 통한 태양광발전 출력제한 대응 ESS 최적운영스케줄링에 관한 연구

The installation of energy storage system (ESS) is increased to solve the instability of the transmission system due to variable renewable energies such as Photovoltaic power generation (PV) and wind power generation. Meanwhile, recently, PV output is frequently curtailed since PV output produced after the ESS charging is finished causes transmission line congestion. For this congestion, it is common to increase line capacity or allocate the output curtailment for each power plant. However, since the unsettled loss occurs due to the output curtailment, the power plant operator should be given an incentive to induce the output curtailment for a specific time. Therefore, in this paper, the ESS optimal operation scheduling using the demand response transaction mechanism as an incentive is presented. From the perspective of PV operator with ESS, the charge/discharge capacity is determined in units of 15 minutes reflecting the PV curtailment and the demand response trading mechanism through mixed-integer linear programming. Uncertainty in the D-Day actual PV power output is considered as three scenarios such as Day-ahead forecasting PV power output and Day-ahead forecasting PV power output scenario with mean absolute percentage errors. Through optimal operation scheduling of ESS, transmission line overload and system congestion are suppressed by ESS charging and PV operators can secure additional benefits through the demand response trading mechanism without PV curtailment. Namely, total expected benefits can be maximized by the proposed method. As a result, an additional expansion of transmission lines or the introduction of a new incentive system can be avoided by the flexibility of PV operators.

Analysis of Environmental Impacts Caused by the Construction of Power Transmission Lines in Brazil

A country's energy production, transmission and distribution systems are directly linked to its technological advances and economic growth. In Brazil, the creation and expansion of several transmission lines are planned. Such ventures often come up against environmental aspects, as they advance over forest and conservation areas. In this context, the objective of this research was to study the main environmental impacts caused by the implementation of transmission lines in forest areas in order to have a better understanding of the subject, thus being able to minimize or extinguish them. After gathering information, it was found that most of the environmental impacts are due to the deforested area around the transmission lines, called the right of way, which creates a corridor that alters the vegetation. Other serious impacts are related to the type of foundation most used: the micropile, which uses a toxic stabilizing mud in its drilling. The results of this research can be used as a basis to minimize such impacts that can cause damage to the environment and delays in the construction of the lines.

Does Electricity Drive Structural Transformation? Evidence from the United States

Electricity is a general purpose technology and the catalyst for the second industrial revolution. Developing countries are currently making huge investments in electrification, with a view to achieving structural change. What does history say about its impact on the structure of employment? We use U.S. Census data from 1910 to 1940 and measure electrification with the length of higher-voltage electricity lines. Instrumenting for electrification using hydroelectric potential, we find that the average expansion of high-voltage transmission lines between 1910 and 1940 increased the share of operatives in a county by 3.3 percentage points and decreased the share of farmers by 2.1 percentage points. Electrification can explain 50.5% of the total increase in operatives, and 18.1% of the total decrease in farmers between 1910 and 1940. At the industry level, electrification drove 15.7% of the decline in the share of agricultural employment and 28.4% of the increase in the share of manufacturing employment between 1910 and 1940. Electrification was thus a key driver of structural transformation in the U.S. economy.

A real-world investigation into usage patterns of electric vehicles in Shanghai

Abstract The usage patterns of EVs is a great concern in Shanghai as the city with the largest number of EVs. Their usage patterns are investigated based on time series association and segmentation of historical static EV data from the real world. The results show that both BEV and PHEV are mostly used as commuting vehicles with an average speed of EVs of less than 25 km/h and about 80% of EVs travel within 60 km per day. Although there is no big difference between the speed of EVs and other models during the morning and evening rush hours, low-speed EVs have a significant environmental advantage over fuel vehicles. About 30% EVs have a relatively concentrated charging time between 21:00–24:00 while PHEVs with small battery capacity still present a small charging peak at about 9:00 in the morning in order to continue to travel with electricity on the way home. The charging locations in urban center are more intensive than those in suburban areas and EVs are charged more frequently in summer than in winter. It is necessary to optimize the layout of charging piles and orderly charging of EVs in the case of no capacity expansion of power transmission and distribution lines. The actual electricity consumption per 100 km of BEV or PHEV is greater than that provided by the manufacturer due to air conditioning energy consumption and complex driving conditions. The results are helpful to promote the development of EVs and layout of charging piles.

A Long-Term Evaluation on Transmission Line Expansion Planning with Multistage Stochastic Programming

The purpose of this paper is to apply multistage stochastic programming to the transmission line expansion planning problem, especially when uncertain demand scenarios exist. Since the problem of transmission line expansion planning requires an intensive computational load, dual decomposition is used to decompose the problem into smaller problems. Following this, progressive hedging and proximal bundle methods are used to restore the decomposed solutions to the original problems. Mixed-integer linear programming is involved in the problem to decide where new transmission lines should be constructed or reinforced. However, integer variables in multistage stochastic programming (MSSP) are intractable since integer variables are not restored. Therefore, the branch-and-bound algorithm is applied to multistage stochastic programming methods to force convergence of integer variables.In addition, this paper suggests combining progressive hedging and dual decomposition in stochastic integer programming by sharing penalty parameters. The simulation results tested on the IEEE 30-bus system verify that our combined model sped up the computation and achieved higher accuracy by achieving the minimised cost.

Transmission costs and the value of wind generation for the CREZ project

This paper analyzes the recent expansion of transmission lines in Texas, essentially completed in 2013 at a cost of approximately $7 billion. This project was intended to improve access to areas with high wind generation potential and the resulting increase in wind generation reduced fuel costs and emissions from the displaced fossil fuel generators. I find that the value of the resulting emissions reduction from additional wind generation is approximately twice that of the fuel savings. Additionally, when incorporating the value of reduced emissions, increased generation from already existing wind turbines alone could offset about half of the annualized cost of this transmission expansion while using only 2% of the new transmission capacity. Incorporating the value of emissions reductions could make extending transmission lines to access high quality wind resources more viable, especially if production from already-existing wind turbines in the area are being non-trivially curtailed, as was true in this case.

Role of Big Data Analytics in Power System Application

Power system sector is the back bone for any country economic growth. In current years, electric power systems have experienced various challenges and technological innovations and have become digitalized with the introduction concept of smart grids. Power systems are being operated in a stressed condition mainly due to the ever increasing load demand, depleting energy resources and environmental constraints on Transmission line expansion. This article focus mainly role of Big Data in various industrialization in brief and specifically applied in the power system studies along with other sectors. Also focuses on using very large data collections, which are difficult to access in standard database systems and also refers to as big data, to manage and monitor the power system. System stability is an significant goal for power engineers to use this huge amount of data to run the system in their rated capacity, power sector can beneficial of various potential solicitation of power system by the use of large-scale data analysis that can help improve the optimization process and helps for the power system to operate in the effective manner.

Optimally Coordinated Expansion Planning of Coupled Electricity, Heat and Natural Gas Infrastructure for Multi-Energy System

Gas generation and heat storage are playing a prominent role to multi-energy systems (MES), and coordinated planning of integrated electricity, heat and gas infrastructures can highly benefit MES. In this context, a coordinated planning model of MES is proposed to determine the optimal expansion of conventional generators, transmission lines, gas boilers, combined heat and power units, and gas pipelines. In the model, the one-off investment cost of MES devices in the planning phase plus the operation cost and energy not served cost in the operation phase are considered in the objective, while the energy supply reliability, coupled operational security of multiple energy carriers, as well as the electricity, gas, and heat demand balance are comprehensively taken into account as the constraints. Afterwards, the Benders Decomposition method is adopted to solve the proposed expansion planning model in a divide and conquer manner. Finally three case studies on a 14-bus MES are conducted to demonstrate the effectiveness of the proposed expansion planning model. Simulation results indicate that the total cost of the proposed model in case 3 is saved by 9% and 2.8% compared with the separately planning scheme in case 1 and the coordinated planning scheme without candidate gas pipelines in case 2. Therefore, the proposed coordinated expansion model is very effective for MES Infrastructure planning.