The electricity industry faces the challenge of adapting to new circumstances where environmental concerns and the optimal use of resources are crucial. In this scenario, Distributed Energy Resources (DER) are recognised as one of the possible solutions for sustainable economic development. The optimal integration of DER in the distribution networks is essential to maximise DER benefits and minimise the cost of DER integration. An adequate DER planning method is required to obtain valuable information for the best deployment of these resources. The integration of DER has several drivers, such as the minimisation of cost, the reduction of carbon emission and the reduction of energy losses, among others. At the same time, several stakeholders are involved in DER research, development and management. Consequently, a flexible and multi-objective planning method that considers technical, environmental and economic impacts of DER integration can provide a deep insight into the advantages and drawbacks of DER, and can reflect the different perspectives on the problem. Most renewable DER have a variable output. Hence, the planning of DER integration must consider the stochastic nature of DER. Likewise, the active management of DER and the network has been recognised recently as one of the new paradigms for the integration of larger penetrations of DER. As a result, an appropriate planning technique for DER integration must consider the simultaneous interaction of controllable and stochastic DER to provide an adequate evaluation of DER impacts and benefits. Novel multi-objective optimisation techniques, known as Multi-objective Evolutionary Algorithms (MOEA), have been developed recently. MOEA are able to analyse complex objective functions and offer a “true” multi-objective approach. Consequently, MOEA are able to handle complex multi-objective problems such as DER planning effectively. This thesis proposes to use multi-objective planning to analyse the optimal integration of stochastic and controllable DER. It presents the design, development and demonstration of a planning framework based on a state-of-the-art MOEA. Results from two relevant case studies show that the multi-objective planning method proposed is a novel and valuable tool for the analysis of DER integration. The framework proposed is generic and can be applied to other energy planning problems.