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This voltage imbalance in four-wire, three-phase distribution networks gives rise to negative-sequence and zero-sequence voltage components which increases the total apparent power received from the network. This also increases the energy losses from the network. Traditional methods employed for load compensation provide partial fixes at the local area without any form of system-wide solution. This work presents a new decentralized control strategy for the inverter of a photovoltaic-based three-phase power source (DPS) aimed at instantaneously correcting phase voltage imbalances. The method does not require load current measurement because it depends entirely on real-time voltage measurements at the point of common coupling (PCC). The capability to mitigate the unbalance depends on the available power of the DPS. To test how effective the proposed method is, simulations have been conducted using MATLAB/SIMULINK on a distribution network with a four-leg inverter connected to a line with cascading single and three-phase loads, where a four-leg inverter enables independent phase control and mitigation of neutral current disturbances. The results show that this control enables the comparison of balancing for three-phase powers with a 96.4% improvement. The phase-to-phase voltage deviation was also reduced by around 8 V (3.6% of nominal voltage). Furthermore, the total harmonic distortion (THD) of the output current from the inverter did not rise about 3.75%, hence improving the power quality. Its real-time applicability in decentralized renewable energy integration is possible due to the method’s effectiveness in reducing voltage imbalances even when network conditions are extremely distorted.

Energy demand is continuously increasing, leading to yearly expansions in low-voltage (LV) distribution systems integrated with PVs to deliver electricity to users with techno-economic considerations. This study proposes and compares different topology planning strategies with and without PVs in a rural area of Cambodia over 30 years of planning. Firstly, the optimal radial topology from a distribution transformer to end-users is provided using the shortest path algorithm. Secondly, two different phase balancing concepts (i.e., pole balancing and load balancing) with different phase connection methods (i.e., power losses and energy losses) are proposed and compared to find the optimal topology. Then, the integration of centralized (CePV) and decentralized PV (DePV) into the optimal topology is investigated for three different scenarios, which are zero-injection (MV and LV levels), no sell-back price, and a sell-back price. Next, the minimum sell-back price from CePV and DePV integration is determined. To optimize phase balancing, including the location and size of PV, an optimization technique using a water cycle algorithm (WCA) is applied. Finally, an economic analysis of each scenario based on the highest net present cost (NPC), including capital expenditure (CAPEX) and operational expenditure (OPEX) over the planning period, is evaluated. In addition, technical indicators, such as autonomous time and energy, and environmental indicator, which is quantified by CO2 emissions, are taken into account. Simulation results validate the effectiveness of the proposed method.

Several research efforts are conducted towards the impact of wind power variability on the operating reserve requirements of power systems. In most systems, reserve capacity is determined by means of a heuristic or statistical analysis of the different drivers for system imbalances. This contribution puts forward a dynamic reserve approach in which the operating reserve capacity is modified on hourly basis, based on expected wind power conditions. This would improve the current methodologies where the capacity is fixed for longer periods, avoiding expensive overestimations. By means of a decentralised approach, the suggested methodology conforms with an unbundled and liberalised market framework. Results show how the average upward and downward capacity reductions are reduced with at least 36% and 16%, compared to the corresponding static reserve strategy. System simulations integrating this dynamic reserve strategy reveal substantial reductions in operational costs. The average cost of withholding reserve capacity is observed to decrease from 4.5, 5.1, 17.1 and 51.2 to 3.1, 4.8, 7.9 and 14.6 €/MWh wind energy injected, respectively, for an installed capacity representing 6, 12, 18 and 24% of the annual electricity demand. In conclusion, the results of this contribution encourage transmission system operators to evolve towards dynamic reserve strategies.