No abstract

No abstract

There is an increasing interest in low voltage direct current (LVDC) distribution grids due to advancements in power electronics enabling efficient and economical electrical networks in the DC paradigm. Power flow equations in LVDC grids are non-linear and non-convex due to the presence of constant power nodes. Depending on the implementation, power flow equations may lead to more than one solution and unrealistic solutions; therefore, the uniqueness of the solution should not be taken for granted. This paper proposes a new power flow solver based on a graph theory for LVDC grids having radial or meshed configurations. The solver provides a unique solution. Two test feeders composed of 33 nodes and 69 nodes are considered to validate the effectiveness of the proposed method. The proposed method is compared with a fixed-point methodology called direct load flow (DLF) having a mathematical formulation equivalent to a backward forward sweep (BFS) class of solvers in the case of radial distribution networks but that can handle meshed networks more easily thanks to the use of connectivity matrices. In addition, the convergence and uniqueness of the solution is demonstrated using a Banach fixed-point theorem. The performance of the proposed method is tested for different loading conditions. The results show that the proposed method is robust and has fast convergence characteristics even with high loading conditions. All simulations are carried out in MATLAB 2020b software.

In this paper, a model is proposed for the optimal operation of multi-energy microgrids (MEMGs) in the presence of solar photovoltaics (PV), heterogeneous energy storage (HES) and integrated demand response (IDR), considering technical and economic ties among the resources. Uncertainty of solar power as well as the flexibility of electrical, cooling and heat load demand are taken into account. A p-efficient point method is applied to compute PV power at different confidence levels based on historical data. This method converts the uncertain PV energy from stochastic to deterministic to be included in the optimization model. The concept of demand response is extended and mathematically modeled using a linear function based on the quantized flexibility interval of multi-energy load demand. As a result, the overall model is formulated as a mixed-integer linear program, which can be effectively solved by the commercial solvers. The proposed model is implemented on two typical summer and winter days for various cases. Results of case studies show the important benefits for maximum PV utilization, energy efficiency and economic system operation. Moreover, the influence of the different confidence levels of PV power and effectiveness of IDR in the stochastic circumstances are addressed in the optimization-based operation.

Industrial sector is of great significance for the economic growth of every country. The energy crisis in Pakistan has become the prime stumbling block in the economic development of the country. There are many industrial processes that need uninterrupted supply; even a trivial outage can cost millions of dollars. The main cause of "load shedding" in Pakistan is that it produces a major portion of its energy from fossil fuels, whose price and demand is constantly increasing. Most of the customers at industrial and commercial level use Diesel Generator (DiG) as a reliable alternative source of electrical power when grid supply is unavailable. The use of DiG during loading shedding hours would increase the Cost of Energy (COE) per kWh and also enhance environmental emissions. Pakistan has a wide range of renewable power sources like bioenergy, wind, solar, hydel, geothermal etc. The distinct emphasis on the implementation of an industrial microgrid in Faisalabad, Pakistan has been specified in this paper. The prospective benefits of the microgrid fall into three major kinds: cost reduction, fuel saving, and improved environmental emissions. The optimized objective of this work is to maximize these benefits. Moreover while designing the hybrid microgrid system it encounters many design challenges like sizing of the components, system feasibility, COE, system reliability etc. This study contributes to the ongoing studies about hybrid microgrid system and draws attention to the optimal design and sizing considering several techno-economic factors including Net Present Cost (NPC), COE, supply reliability, capacity shortage constraint, battery state of charge (SOC), dispatch strategy, PV power generation and PV array tracking systems. Different cases are studied; microgrid sizing, techno-economic exploration, sensitivity analysis and environmental effects are addressed using (Hybrid Optimization Model for Electric Renewables) HOMER. The results show that COE and environmental emissions have been significantly reduced for the proposed system.