Generation Expansion Planning with Energy Storage Systems Considering Renewable Energy Generation Profiles and Full-Year Hourly Power Balance Constraints

Abstract

This paper proposes a methodology to develop generation expansion plans considering energy storage systems (ESSs), individual generation unit characteristics, and full-year hourly power balance constraints. Generation expansion planning (GEP) is a complex optimization problem. To get a realistic plan with the lowest cost, acceptable system reliability, and satisfactory CO2 emissions for the coming decades, a complex multi-period mixed integer linear programming (MILP) model needs to be formulated and solved with individual unit characteristics along with hourly power balance constraints. This problem requires huge computational effort since there are thousands of possible scenarios with millions of variables in a single calculation. However, in this paper, instead of finding the globally optimal solutions of such MILPs directly, a simplification process is proposed, breaking it down into multiple LP subproblems, which are easier to solve. In each subproblem, constraints relating to renewable energy generation profiles, charge-discharge patterns of ESSs, and system reliability can be included. The proposed process is tested against Thailand’s power development plan. The obtained solution is almost identical to that of the actual plan, but with less computational effort. The impacts of uncertainties as well as ESSs on GEP, e.g., system reliability, electricity cost, and CO2 emission, are also discussed.

A Deep Learning-Based Approach for Generation Expansion Planning Considering Power Plants Lifetime

“…In the BLSTM networks, X t n×r is the mini-batch input data in a time step t, → H t n×nh and ← H t n×nh are forward and backward hidden states which calculated based on Equations ( 14) and (15), respectively. Hidden state in a time step t is H t n×2nh , and output is O f n n×no which is calculated based on Equation (16).…”

“…In [14], a comprehensive and deep review has been performed about the GEP problems such as uncertainties, energy policies, low carbon economy requirements, renewable sources, electricity market, demand-side programs, distributed generation, and so on. A review of the GEP problems, which include renewable energy power plants, has been carried out in [15,16] and the operational flexibility issues have been investigated and several ways have been proposed for solving this challenge. In [17], a review has been performed about adding renewable power plants to the GEP model and three issues of optimization models, general/partial equilibrium models, and alternative models, have been studied.…”

Stochastic Modeling of Renewable Energy Sources for Capacity Credit Evaluation

“…In Thailand, the capacity credit is called dependable capacity. It is used to evaluate the reserve margin, which is a reliability index for generation expansion planning [39]. The capacity credit can be calculated by approximation and reliability-based methods [40][41][42][43].…”

A Game Theory Approach Using the TLBO Algorithm for Generation Expansion Planning by Applying Carbon Curtailment Policy

“…Because of the penetrating the renewable power plants in power systems considering the energy storage systems in networks is necessary [9]. In [10], the GEP problem is considered with hourly variability of the wind and solar power.…”