It is broadly trusted that effective scheduling of flexible demand and energy storage operation will offer opportunities for reduced investment in transmission and distribution assets together with the associated lower environmental footprint and avoidance of long delays in connecting renewable generation. Expected demand migration from transport and heat sectors in few next decades is going to give additional stress to the electricity networks as this load is characterized with relatively low diversity factors restricting the amount of demand growth that can be accommodated into existing networks. The potential benefits of using Demand Side Response (DSR) and Storage technologies for network applications have not been fully explored due to a lack of rigorous methodology for quantification of the effects of these technologies on network operation and development. In this context, this work focuses on the investigation of the potential benefits of utilization of DSR, Storage and Electric Vehicles (EV) as potential means for network congestion management and for maximizing the system capability to employ renewable energy sources. To this purpose, novel methodologies are developed based on a multi-period Optimal Power Flow (OPF), where DSR, Storage and EV are modelled as a part of the optimisation constraints. The proposed optimisation methodologies and techniques are applied to estimate a magnitude of order of potential value of DSR, Storage and EV for alternative development of the electricity systems. Without loss of generality, DSR principle explained is based on a batch of wet appliances (composed by dishwashers, washing machines, and tumble dryers). The benefits are evaluated by comparing scenarios without and with these enabling technologies. The expected outcome of the research is to identify trends and characteristic conditions in which the enabling technologies are likely to have a high value, and also to determine the key driving factors for the value of these technologies in the context of releasing latent network capacity.