Nigeria’s electric power distribution network is faced with high technical power losses arising mainly from the radial nature of distribution systems, long length of feeders and poor voltage profile. This work estimates the financial implication of the technical losses in a typical Nigerian distribution network and proposes ways to reduce it. The existing Benin Electricity distribution company (BEDC) Asaba government core area injection substation distribution network comprising of a 15MVA 33/11KV power transformer and its two number radially connected 11KV feeders – SPC and Anwai road with their aggregate of ninety six (96) number secondary distribution 11/0.415KV transformers was modelled with ETAP 7.0.0 software, and a load flow analysis was carried on the modelled network using Newton-Raphson method deployed in the ETAP 7.0 software.  This was done to determine bus voltages, real and reactive power losses in the network. Data used for the study were obtained from BEDC Asaba business district between June and August, 2017. Analysis of the load flow results show that using the current multi-year tariff order (MYTO) for BEDC with the cost of a KWh of energy at N31.27 for residential customers as base, N 1 , 065,569,028.00 worth energy will be lost in the network within a ten-year period. Further analysis shows that a savings of N 640,742,713.10 will be made within 10 years if the distribution network is compensated  by optimally locating reactive power compensating devices. Key words: Compensating Devices, Financial Implication, Technical Losses, Financial Implication.

https://jeeeccs.net/index.php/journal/article/download/102/87

Technical loss estimation and reduction in a typical nigerian distribution system: a case study.

The invention discloses a twin-well model state of charge (SOC) estimation method based on a rate capacity and recovery characteristics. Based on a KiBaM twin-well model, the relationship between a discharge rate and the state of charge is deduced; then, a discrete model for the KiBaM twin-well state of charge is built; in order to enhance the state of charge estimation error correction ability, the traditional Thevenin model and the discrete model are combined, and a discrete state space comprehensive model is built; recursive least-square and nonlinear Sigma point Kalman filter algorithms are adopted to carry out online recognition on parameters of the discrete state space comprehensive model and estimation on the state of charge. The state of charge of a lithium-ion battery under different discharge rates can be accurately estimated, and partial capacity recovery characteristics after discharge of the lithium-ion battery can be reflected. According to different discharge rates and different initial SOC conditions of the battery, SOC estimation is carried out, errors are corrected, and an accurate result is acquired.

Twin-well model state of charge (SOC) estimation method based on rate capacity and recovery characteristics

Abstract Microgrids (MGs) have emerged as a promising solution for providing reliable and sustainable electricity, particularly in underserved communities and remote areas. Integrating diverse renewable energy sources into the grid has further emphasized the need for effective management and sophisticated control strategies. This review explores the crucial role of control strategies in optimizing MG operations and ensuring efficient utilization of distributed energy resources, storage systems, networks, and loads. To maximize energy source utilization and overall system performance, various control strategies are implemented, including demand response, energy storage management, data management, and generation‐load management. Employing artificial intelligence (AI) and optimization techniques further enhances these strategies, leading to improved energy management and performance in MGs. The review delves into the control strategies and their architectures, and highlights the significant contributions of AI and emerging technologies in advancing MG energy management. 

A review of control strategies for optimized microgrid operations

The invention relates to a regional new energy power supply structure optimization prediction method and system, and a "total amount-structure-component" three-phase comprehensive optimization prediction model is established. The method includes: predicting a new energy power supply on-grid electric quantity total amount by employing an improved grey prediction model, optimizing a prediction result of the power supply on-grid electric quantity total amount, and obtaining a prediction result X of the new energy power supply on-grid electric quantity total amount; predicting a new energy on-gridelectric quantity structure by employing a dynamic planning prediction model based on error optimization, and obtaining a structure prediction result F of the new energy power supply branch power supply type; and obtaining a component prediction result R of the new energy power supply branch power supply type by employing the obtained prediction result X of the new energy power supply on-grid electric quantity total amount and the structure prediction result F of the new energy power supply branch power supply type. According to the method and system, optimized prediction of a regional new energy power supply structure can be realized, the application range is wide, and the prediction precision is high.

Regional new energy power supply structure optimization prediction method and system

The invention discloses a hybrid energy dispatching management method for a battery microgrid, comprising the following steps: 1) designing a photovoltaic current equivalent circuit model of a photovoltaic power generation system; 2) establishing a maximum work output rate model of that photovoltaic power generation system; ...; 5) establishing photovoltaic-battery microgrid system total economicbenefit model; 6) establishing photovoltaic-battery microgrid system maximum economic benefit NPV and maximum self-supply rate SSR Model; 7) establishing the following energy scheduling management strategy to controlthe energy storage battery unit composed of lithium battery in the photovoltaic-battery microgrid system to be switched between the following states. The invention fully considers theseasonal characteristics of the user load and the photovoltaic power source, and combines the photovoltaic power source with the photovoltaic power source. The energy dispatching management strategy of battery micro-grid adopts the mixed mode of the two strategies, which makes full use of the energy storage system and realizes the real-time seamless switching of the two strategies, so as to improve its economic benefits and at the same time give attention to the reliability and environmental protection of the system.

Hybrid energy dispatching management method for photovoltaic-cell microgrid based on demand side response

A wind-photovoltaic-energy-storage power generation system capacity optimizing method based on a wind-photovoltaic hybrid characteristic belongs to the technical field of a wind-photovoltaic-energy-storage power generation system. According to the wind-photovoltaic-energy-storage power generation system capacity optimizing method, through controlling the hybrid power generation system, island-mode operation and grid-connected-mode operation of the hybrid power generation system can be realized. According to the wind-photovoltaic-energy-storage power generation system capacity optimizing method, a capacity optimizing model which is suitable for the wind-photovoltaic-energy-storage power generation system is presented, wherein system cost minimizing is used as an optimizing target, and furthermore the wind-photovoltaic hybrid characteristic, a grid-connected power fluctuation condition and a system load loss rate are comprehensively considered. The wind-photovoltaic-energy-storage power generation system capacity optimizing method has advantages of sufficiently utilizing the wind-photovoltaic hybrid characteristic, ensuring high reliability in power supplying of the system just through a relatively low storage battery capacity, and reducing system cost.

Wind-photovoltaic-energy-storage power generation system capacity optimizing method based on wind-photovoltaic hybrid characteristic

Study on Power Loss Reduction Considering Load Variation with Large Penetration of Distributed Generation in Smart Grid

A hybrid energy storage capacity optimization configuration method based on chance-constrained programming belongs to the wind and light storage hybrid power generation system energy storage configuration optimization technology field. In the invention, based on a power capacity and an energy capacity which are required by a hybrid energy storage system and are acquired through calculation, a chance constrained programming algorithm is used to calculate optimal capacity configuration of a storage battery and a super capacitor in the hybrid energy storage system under different confidence levels. By using the optimization method, an optimized target is that total cost is least. By using the method of the invention, technology rationality and economic practicality of a constructed optimization model are high, and a theory support and a technology support are provided for programming and designing of a wind and light storage hybrid power generation system.

Hybrid energy storage capacity optimization configuration method based on chance-constrained programming

With the increase of penetration of distribution in distribution systems, the problems of power loss increase and short-circuit capacity beyond the rated capacity of the circuit breaker will become more serious. In this paper, a methodology (modified BPSO) is presented for network reconfiguration which is based on the hybrid approach of Tabu search and BPSO algorithms to prevent the local convergence and to decrease the calculation time using double fitness to consider the constraints. Moreover, an average load simulated method (ALS method) considering load variation is proposed such that the average load value is used instead of the actual load for calculation. Finally, from a case study, the results of simulation certify that the approaches will decrease drastically the losses and improve the voltage profiles obviously; at the same time, the short-circuit capacity is also decreased into smaller shut-off capacity of the circuit breaker. The power losses will not be increased too much even if the short-circuit capacity constraint is considered; voltage profiles are better with the constraint of short-circuit capacity considered. The ALS method is simple and the calculation time is fast.

/pdf/control-strategy-for-power-loss-reduction-considering-load-uc69f2k73t.pdf

Control Strategy for Power Loss Reduction considering Load Variation with Large Penetration of Distributed Generation

The invention discloses an online identification method for electromechanical oscillation modal characteristic parameters of an electric power system, and belongs to the technical field of electric power system state analysis. On the basis that random data generated due to uncertain factor interference in the environment where the power system is located is selected, the application of a new analysis method of O3KID-ERA/DC is provided to carry out small interference on-line calculation and analysis of the power system. Analysis of small interference of electric power system is carried out through example simulation calculation verification. The ERA/DC algorithm has good applicability; in addition, compared with a traditional classic SSI algorithm, the method has higher robustness. According to the method, more excellent capability is shown on the precision and stability of modal parameter identification, a new and reliable solution is provided for real-time online monitoring and analysis of the small interference stability level based on random data in the operation process of the power system, and the method has high practical application value.

Online identification method for electromechanical oscillation modal characteristic parameters of electric power system

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