Due to the widespread deployment of distributed energy resources (DERs) and the liberalization of electricity market, traditional distribution networks are undergoing a transition to active distribution systems (ADSs), and the traditional deterministic planning methods have become unsuitable under the high penetration of DERs. Aiming to develop appropriate models and methodologies for the planning of ADSs, the key features of ADS planning problem are analyzed from the different perspectives, such as the allocation of DGs and ESS, coupling of operation and planning, and high-level uncertainties. Based on these analyses, this comprehensive literature review summarizes the latest research and development associated with ADS planning. The planning models and methods proposed in these research works are analyzed and categorized from different perspectives including objectives, decision variables, constraint conditions, and solving algorithms. The key theoretical issues and challenges of ADS planning are extracted and discussed. Meanwhile, emphasis is also given to the suitable suggestions to deal with these abovementioned issues based on the available literature and comparisons between them. Finally, several important research prospects are recommended for further research in ADS planning field, such as planning with multiple micro-grids (MGs), collaborative planning between ADSs and information communication system (ICS), and planning from different perspectives of multi-stakeholders.

Optimal power flow (OPF) objective functions involve minimization of the total fuel costs of generating units, minimization of atmospheric pollutant emissions, minimization of active power losses and minimization of voltage deviations. In this paper, a fuzzy multi-objective OPF model is established by the fuzzy membership functions and the fuzzy satisfaction-maximizing method. The improved artificial bee colony (IABC) algorithm is applied to solve the model. In the IABC algorithm, the mutation and crossover operations of a differential evolution algorithm are utilized to generate new solutions to improve exploitation capacity; tent chaos mapping is utilized to generate initial swarms, reference mutation solutions and the reference dimensions of crossover operations to improve swarm diversity. The proposed method is applied to multi-objective OPF problems in IEEE 30-bus, IEEE 57-bus and IEEE 300-bus test systems. The results are compared with those obtained by other algorithms, which demonstrates the effectiveness and superiority of the IABC algorithm, and how the optimal scheme obtained by the proposed model can make systems more economical and stable.

A fuzzy multi-objective bi-level optimization problem is proposed to model the planning of energy storage system (ESS) in active distribution systems (ADS). The proposed model enables us to take into account how optimal operation strategy of ESS in the lower level can affect and be affected by the optimal allocation of ESS in the upper level. The power characteristic model of micro-grid (MG) and typical daily scenarios are established to take full consideration of time-variable nature of renewable energy generations (REGs) and load demand while easing the burden of computation. To solve the bi-level mixed integer problem, a multi-subgroup hierarchical chaos hybrid algorithm is introduced based on differential evolution (DE) and particle swarm optimization (PSO). The modified IEEE-33 bus benchmark distribution system is utilized to investigate the availability and effectiveness of the proposed model and the hybrid algorithm. Results indicate that the planning model gives an adequate consideration to the optimal operation and different roles of ESS, and has the advantages of objectiveness and reasonableness.

The power fluctuations of grid-connected photovoltaic (PV) systems have negative impacts on the power quality and stability of the utility grid. In this study, the combinations of a battery/supercapacitor hybrid energy storage system (HESS) and the PV power curtailment are used to smooth PV power fluctuations. A PV power curtailment algorithm is developed to limit PV power when power fluctuation exceeds the power capacity of the HESS. A multi-objective optimization model is established to dispatch the HESS power, considering energy losses and the state of charge (SOC) of the supercapacitor. To prevent the SOCs of the HESS from approaching their lower limits, a SOC correction strategy is proposed to correct the SOCs of the HESS. Moreover, this paper also investigates the performances (such as the smoothing effects, losses and lifetime of energy storage, and system net profits) of two different smoothing strategies, including the method of using the HESS and the proposed strategy. Finally, numerous simulations are carried out based on data obtained from a 750 kWp PV plant. Simulation results indicate that the proposed method is more economical and can effectively smooth power fluctuations compared with the method of using the HESS.

To solve the economic dispatch (ED) problem of multiple distributed generations in the microgrid, this paper proposes a fully distributed method by using the exact diffusion strategy which can achieve exact convergence under sparse communication network. Firstly, a multi-agent hierarchical control architecture for the microgrid is designed. The microgrid central controller (MGCC) agent does not act as centralized control but instead participates in the distributed optimization between the bottom layer agents. Furthermore, an economic dispatch optimization model is established which aims at minimizing the operation cost, optimizing the active power of all dispatchable agents including distributed generators and flexible loads on demand side, and realizing the economic utilization of resources. A modified diffusion algorithm supporting full distributed optimization is proposed to solve it, which does not depend on the “leader unit” and is applicable to the actual problem. The modified algorithm has faster convergence speed, higher stability and stronger expansibility than consensus algorithm. Six scenarios are adopted to verify the proposed method. The result shows that the agent framework and the algorithm can cope with changing of communication topology and realize the “plug and play”. The output will converge to the optimal dispatch solution even if communication fails.