Impact of local emergency demand response programs on the operation of electricity and gas systems

With increasing attention to climate change, the penetration level of renewable energy sources (RES) in the electricity network is increasing. Due to the intermittency of RES, gas-fired power plants could play a significant role in backing up the RES in order to maintain the supply–demand balance. As a result, the interaction between gas and power networks are significantly increasing. On the other hand, due to the increase in peak demand (e.g., electrification of heat), network operators are willing to execute demand response programs (DRPs) to improve congestion management and reduce costs. In this context, modeling and optimal implementation of DRPs in proportion to the demand is one of the main issues for gas and power network operators. In this paper, an emergency demand response program (EDRP) is implemented locally to reduce the congestion of transmission lines and gas pipelines more efficiently. Additionally, the effects of optimal implementation of local emergency demand response program (LEDRP) in gas and power networks using linear and non-linear economic models (power, exponential and logarithmic) for EDRP in terms of cost and line congestion and risk of unserved demand are investigated. The most reliable demand response model is the approach that has the least difference between the estimated demand and the actual demand. Furthermore, the role of the LEDRP in the case of hydrogen injection instead of natural gas in the gas infrastructure is investigated. The optimal incentives for each bus or node are determined based on the power transfer distribution factor, gas transfer distribution factor, available electricity or gas transmission capability, and combination of unit commitment with the LEDRP in the integrated operation of these networks. According to the results, implementing the LEDRP in gas and power networks reduces the total operation cost up to 11% and could facilitate hydrogen injection to the network. The proposed hybrid model is implemented on a 24-bus IEEE electricity network and a 15-bus gas network to quantify the role and value of different LEDRP models

Investing in flexibility in an integrated planning of natural gas and power systems

The growing interdependencies between natural gas and power systems, driven by gas-fired generators and gas compressors supplied by electricity, necessitates detailed investigation of the interactions between these vectors, particularly in the context of growing penetration of renewable energy sources. In this research, an expansion planning model for integrated natural gas and power systems is proposed. The model investigates optimal investment in flexibility options such as battery storage, demand side response, and gas-fired generators. The value of these flexibility options is quantified for gas and electricity systems in GB in 2030. The results indicate that the flexibility options could play an important role in meeting the emission targets in the future. However, the investment costs of these options highly impact the future generation mix as well as the type of reinforcements in the natural gas system infrastructure. Through deployment of the flexibility options up to £24.2b annual cost savings in planning and operation of natural gas and power systems could be achieved, compared to the case that no flexibility option is considered

A fuzzy-logic-based control methodology for secure operation of a microgrid in interconnected and isolated modes

Due to the global concerns regarding the climate change, integration of renewable energy sources is considered as a mitigation approach in electric power generation. This requires advanced frequency and voltage control methodologies to overcome the challenges especially in microgrids. This paper presents a 2-step frequency and voltage control methodology for microgrids with high penetration of variable renewable energy sources. An optimized Proportional-Integral controller is designed for a Superconductor Magnetic Energy Storage System to minimize the transient frequency deviations. In cases that the Superconductor Magnetic Energy Storage System cannot stabilize the microgrid frequency in the isolated mode, the microgrid controller activates the next level of the frequency control. In the second level, an intelligent fuzzy-logic frequency controller is designed to adjust controllable loads, controllable generation units as well as perform load shedding. In the interconnected mode, the microgrid controller is able to activate the second level to contribute to the system frequency control. Finally, an intelligent fuzzy-logic voltage controller, realized through distribution static synchronous compensator, is devised to control the voltage magnitude of the main feeders of the microgrid. In this work, a real-time operation algorithm for frequency as well as voltage control is proposed and has been tested by set of simulations on a low voltage benchmark network

Secure operation of integrated natural gas and electricity transmission networks

The interaction between natural gas and electricity networks is becoming more significant due to the projected large penetration of renewables into the energy system to meet the emission targets. This is due to the role of gas-fired plants in providing backup to renewables as the linkage between these networks. Therefore, this paper proposes a deterministic coordinated model for the secure and optimal operation of integrated natural gas and electricity transmission networks by taking into account the N-1 contingency analysis on both networks. In order to reduce the computational burden and time, an iterative algorithm is proposed to select the critical cases and neglect other contingencies, which do not have a significant impact on the energy system. The proposed integrated mixed-integer nonlinear programming operational model is evaluated and compared to another enhanced separated model on the IEEE 24-bus and 15-node gas test systems. The results emphasize the importance and effectiveness of the proposed framework (up to 6.7% operational costs savings are achieved)

Information-Gap Decision Theory for Robust Operation of Integrated Electricity and Natural Gas Transmission Networks

Natural gas consumption and the share of renewable energy in meeting global energy demand has grown dramatically in the recent years. On the other hand, the rapid growth of gas-fired generating units (GFU) (i.e., producing lower carbon dioxide emissions compared to coal-fired generating units), could play a key role in more integration of renewable energy sources (RESs) into the system due to their high flexibility. Therefore, the interaction between the electricity and natural gas networks (ENGN) becomes more challenging. This paper proposes a robust multi objective integrated mixed integer nonlinear optimization model, utilizing information-gap decision theory (IGDT), for secure and optimal operation of ENGN considering security constraints as well as gas and electricity load demand uncertainties. This bi-objective optimization problem is modified using normalization in the weighted sum method in order to ensuring the consistency of the optimal solutions. The proposed framework is validated on the modified IEEE 24-bus power system with a 15-node natural gas system

Co-optimization of resilient gas and electricity networks; a novel possibilistic chance-constrained programming approach

Gas-fired power plants are commonly employed to deal with the intermittency of renewable energy resources due to their flexible characteristics. Therefore, the intermittency in the power system transmits to the gas system through the gas-fired power plants, which makes the operation of these systems even more interdependent. This study proposes a novel possibilistic model for the integrated operation of gas and power systems in the presence of electric vehicles and demand response. The model takes into account uncertainty in demand prediction and output power of wind farms, which is based on possibility and necessity theories in fuzzy logic through modeling uncertain parameters by Gaussian membership function. Moreover, a contingency analysis algorithm based on maximin optimization is developed to enhance the resiliency in the integrated operation of these systems by finding the worst-case scenario for the outage of components. The proposed model is implemented on a Belgium gas network and IEEE 24-bus electricity network. It is demonstrated that the possibilistic model allows the gas network to respond to the demand variations by providing a sufficient level of linepack within the pipelines. As a result, gas-fired power plants are supposed to commit more efficiently to cope with the intermittency of wind farms, which reduce the wind curtailment by 26%. Furthermore, it is quantified that through applying the contingency analysis algorithm in presence of demand response and electrical vehicles, the costs of operation and load shedding is reduced up to 17% and 83%, respectively

Displasia fibrosa do clivus: relato de caso Fibrous dysplasia of the clivus: case report

Relatamos o caso de uma paciente de 43 anos com história de cefaléia crônica e diplopia. O exame neurorradiológico demonstrou aumento de volume e alteração na densidade óssea do clivus. Foi submetida a cirurgia e o exame anatomopatológico evidenciou displasia fibrosa. Foram relatados na literatura outros 14 casos de displasia fibrosa envolvendo o clivus. Discutimos essa rara apresentação da doença segundo o quadro clínico, exames de imagem, histologia e tratamento.<br>We describe the case of a 43 year-old woman with chronic headache and diplopia. The neurorradiologic exam showed volume increase and alteration in the bone density of the clivus. She was submitted to surgery and the anatomopathologic evidenced fibrous dysplasia. Other 14 of about fibrous dysplasia involving the clivus are related in the literature. We discuss clinical aspects, image exams, histology and treatment of this rare presentation of the disease