Network flexibility regulation by renewable energy hubs using flexibility pricing-based energy management

This article presents the energy management of electrical and thermal networks in the presence of renewable energy hubs to regulate the flexibility of these networks based on flexible pricing services. Hubs consist of renewable sources and bio-waste units in addition to energy storage and responsive loads. The bio-waste unit produces electrical and thermal energy simultaneously. The proposed scheme minimizes the difference between the network's energy cost and the hub's flexibility income. It is subject to the optimal power flow equations and flexibility limitation in networks, operation model of resources, storage, and responsive loads in form of energy hub, and hub flexibility model. Unscented transformation-based stochastic optimization models uncertainties of load, renewable power, and energy price. Finally, the numerical results demonstrate the capability of the pro-posed scheme in extracting the optimal state of flexibility, operation, and economic situation of electric and thermal networks with optimal energy management of renewable hubs based on flexible pricing services. The inclusion of renewable resources, storage generators, and responsive loads into a renewable hub improves the economic situation by 32.9% and the status of operation indicators of the energy networks by 22.4-42% in condition of 100% flexibility.

Automated summary

This article presents a scheme for energy management in electrical and thermal networks with renewable energy hubs, which utilize flexible pricing services to regulate network flexibility. The scheme includes renewable energy sources, bio-waste units, energy storage, and responsive loads in the hubs. It aims to minimize the difference between network energy cost and hub flexibility income. The proposed scheme considers optimal power flow equations, flexibility limitations, operation models, and uncertainty in load, renewable power, and energy price using stochastic optimization methods. Numerical results demonstrate the effectiveness of the scheme in optimizing flexibility, operation, and economic situation of the networks with renewable hubs.