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Risk-Based Stochastic Unit Commitment
Published in Ning Zhang, Chongqing Kang, Ershun Du, Yi Wang, Analytics and Optimization for Renewable Energy Integration, 2019
Ning Zhang, Chongqing Kang, Ershun Du, Yi Wang
The market clearing of major generators is performed one day ahead before the renewable energy output can be accurately forecasted. Thus, the uncertainty of renewable energy must be considered together with the generation-demand balance and transmission congestion management [1–3]. Traditionally, spinning reserves are scheduled using deterministic and static criteria, e.g., by a fixed amount or a fixed ratio of the load. Such criteria are not suitable for coping with the uncertainty of renewable energy because the predictability of renewable energy is much poorer and more variable than the load demand and the use of deterministic and static criteria may not be economical or reliable for limiting the risk of uncertainty [4]. Transmission congestion management should also be reconsidered when incorporating large-scale renewable energy [5].
Multi-Objective Optimization Algorithms for Deregulated Power Market
Published in Sawan Sen, Samarjit Sengupta, Abhijit Chakrabarti, Electricity Pricing, 2018
Sawan Sen, Samarjit Sengupta, Abhijit Chakrabarti
Transmission congestion occurs when there is insufficient transmission capacity to simultaneously accommodate all requests for transmission service within a region. Historically, vertically integrated utilities managed this condition by constraining the economic dispatch of generators with the objective of ensuring security and reliability of their own or neighbouring systems. Electric power industry restructuring has moved generation investment and operation decisions into the competitive market, but has left transmission as a communal resource in the regulated environment. This mixing of competitive generation and regulated transmission makes congestion management difficult. The difficulty is compounded by the increase in the amount of congestion resulting from increased commercial transactions and the relative decline in the amount of transmission. Transmission capacity, relative to peak load, has been declining in all regions of the power network for over a decade. This decline is expected to continue.
Optimal Decision Making under Uncertainty Using Heuristic Approach in Restructured Power System
Published in Baseem Khan, Om Prakash Mahela, Sanjeevikumar Padmanaban, Hassan Haes Alhelou, Deregulated Electricity Structures and Smart Grids, 2022
In the real-time balancing market, LMPs are calculated at 5-min intervals based on actual grid operating conditions. If the lowest-priced electricity can reach all locations, prices are the same across the entire grid. When there is transmission congestion, power cannot flow freely to certain locations. In that case, more-expensive generators are asked to meet that demand. As a result, the LMP is higher at those locations. All qualified Gencos and Load Serving Entities are paid the LMP at their locations. Congestion charges for bilateral transactions are equal to the difference between the source and the sink LMPs. In PJM, zonal LMPs are load-weighted nodal LMP within predefined load zones. Figure 1.4 provides the market time line in PJM.
A Hybrid bVAR-NARX Wind Power Forecasting Model Based on Wind and Load Demand Correlation: A Case Study of ERCOT’s System from an ISO’s Perspective
Published in Electric Power Components and Systems, 2018
Leena Heistrene, Poonam Mishra, Makarand Lokhande
Generation of wind power is dependent on the existing weather conditions. But this is not the only driving factor that decides the quantity of wind power generated in the system. Transmission congestion in the network, too, affects the total wind power pumped into the system [40, 41]. Either through forced curtailments or through market initiated conditions, generation of wind power is restricted if the transmission network is congested. Transmission congestion is the result of the total load of the system, spatial distribution of load and generation in the network, and the network configuration. Hence, the change observed in the pattern of cross correlation between wind power generated and total load demand, as shown in Table 1, is attributed to transmission congestion of the network. Network congestion alters the dependency relation between the total wind power generated and the total load on the system. In conclusion, it can be said that in order to develop a wind power forecasting structure, a multivariate model consisting of total load demand of the system as one of the variables, ensures that the model captures a wider essence of the given ensemble. This could be physically modeled but such a scenario would pose as a computational challenge for its formulation and application. It is worthwhile to note that the above explanation cannot be considered if the wind speed ensemble is considered since wind speed is totally independent of the transmission conditions.
Transmission congestion management considering EV parking lots and demand response programmes
Published in International Journal of Ambient Energy, 2021
Amin Mohsenzadeh, Chengzong Pang, Lin Yang
Congestion in transmission systems is one of the key issues for secure and reliable system operations (Afkousi-Paqaleh, Noory, and Rashidinejad 2010). Transmission congestion occurs when there is inadequate transmission capacity to meet the demands of all customers and overloads in transmission lines or transformers are appeared (Afkousi-Paqaleh, Rashidinejad, and Lee 2010). In order to supply local demands, more expensive generating units have to be brought on-line. This situation can create ‘market power’ for some of the market participants and may lead to electricity price spikes in restructured power systems (Afkousi-Paqaleh, Rashidinejad, and Lee 2010). In recent years, many studies have been carried out to develop congestion management in the restructured electricity market. In (Afkousi-Paqaleh, Noory, and Rashidinejad 2010) a model for optimal planning of distributed generation (DG) for congestion management in the restructured electricity market is proposed. Also, a cost/worth analysis approach for optimal sizing of DGs to mitigate congestion and increase the security of the system is proposed in (Afkousi-Paqaleh, Rashidinejad, and Lee 2010). A computational method for power dispatch considering transmission congestion is discussed in (Panyakaew and Damrongkulkamjorn 2012). In (Chen and Shu 2005), optimal rescheduling of generation and transmission switching is proposed to reduce line loading in a congested transmission system. Due to increasing electrical vehicles in power system, PHEVs parking lots utilisation has been extended in order to improve reliability, loss and security of network (Amini and Islam 2014). Charging and discharging ability of PHEVs persuaded utilities to employ parking lot as an effective energy resource in transmission network and power energy market (Ahmadi and Moghadam 2012). O’Connell et al. calculated a dynamic day ahead tariff to EV operators bidding into the day-ahead market (O’Connell et al. 2012). In (Lopez et al. 2013) EVs can stop their charging or even inject energy to the grid aiming for congestion management issues.