Optimization solvers: missing link for fully open-source energy system modeling

Not everyone wants to optimise energy to the same outcome. Some bad actors are optimising for pure profit and screw the environment, not public utility function outcomes.

Re: Optimization solvers: missing link for fully open-source energy system modeling

#5

Post by rwlincoln » Sat, Apr 30, 2022, 10:10 AM UTC

I am surprised not to see any mention of the OSQP (Operator Splitting Quadratic Program) solver. It is the most impressive open source solver of this type that I have seen published in recent years. It appears to have been developed as a collaboration between Princeton, ETH Zurich, Oxford, Stanford and some other prestigious names. The benchmarks show that it compares favorably with leading proprietary solvers:

https://github.com/osqp/osqp_benchmarks

The problem described seems to be an ideal use-case for Machine Learning. The MATPOWER Optimal Scheduling Toolkit (MOST) can already solve:

"a stochastic, security-constrained, combined unit-commitment and multiperiod optimal power flow problem with locational contingency and load-following reserves, ramping costs and constraints, deferrable demands, lossy storage resources and uncertain renewable generation."

Much more and it becomes a global optimization problem where you can never really be sure you are not just stuck in a local optimum. The L2RPN (Learning to Run a Power Network) challenge, from RTE-France, is the most interesting effort I have seen applying Machine Learning to energy system management.

https://l2rpn.chalearn.org/

https://github.com/rte-france/l2rpn-baselines

The competition has been renewed for 2022 and has been accepted for the IEEE World Congress on Computational Intelligence in July.

https://wcci2022.org

Re: Optimization solvers: missing link for fully open-source energy system modeling

#6

Post by wenc » Sat, Apr 30, 2022, 10:42 AM UTC

rwlincoln wrote: post #5

I am surprised not to see any mention of the OSQP (Operator Splitting Quadratic Program) solver. It is the most impressive open source solver of this type that I have seen published in recent years. It appears to have been developed as a collaboration between Princeton, ETH Zurich, Oxford, Stanford and some other prestigious names. The benchmarks show that it compares favorably with leading proprietary solvers: https…

I’m in the optimization space and have never heard of this. Thanks. I recognize many of the names behind it.

I think part of the reason it’s not more popular is because QPs aren’t the most popular problem type. They’re used in MPC problems and any number of L2-loss function problems like ML problems, but these already have custom methods for solving the QP. Doesn’t meant they can’t adopt a standard high performance solver — I think this is very promising.

Also I’m not sure if there’s any political issues that limits them from listing this on COIN OR. That’s usually most folks go to site for discovering new solvers.

Re: Optimization solvers: missing link for fully open-source energy system modeling

#7

Post by quanto » Sat, Apr 30, 2022, 10:44 AM UTC

>even the current interior point implementation in HiGHS can be unacceptably slow relative to Gurobi (60-100 times slower). Considering that even Gurobi requires a couple of days to solve huge practical problems illustrates that the use of current open source solvers is totally impractical. The aim of this proposal is to identify key solver enhancements in the short, medium and long term that will help to bridge the significant gap in performance between HiGHS and the major commercial solvers.

It's a great need in the scientific community. Gurobi is the leading commercial solution with a strict license and a high price tag. As the proposed open-source project is only focused on linear programming (as opposed to a general nonlinear optimization), the goal may as well be achievable. Best wishes for the authors.

Re: Optimization solvers: missing link for fully open-source energy system modeling

#8

Post by thesz » Sat, Apr 30, 2022, 10:48 AM UTC

rwlincoln wrote: post #5

I am surprised not to see any mention of the OSQP (Operator Splitting Quadratic Program) solver. It is the most impressive open source solver of this type that I have seen published in recent years. It appears to have been developed as a collaboration between Princeton, ETH Zurich, Oxford, Stanford and some other prestigious names. The benchmarks show that it compares favorably with leading proprietary solvers: https…

The problem is not solution per se, but scalable solution.

Re: Optimization solvers: missing link for fully open-source energy system modeling

#9

Post by algo_trader » Sat, Apr 30, 2022, 11:30 AM UTC

rwlincoln wrote: post #5

I am surprised not to see any mention of the OSQP (Operator Splitting Quadratic Program) solver. It is the most impressive open source solver of this type that I have seen published in recent years. It appears to have been developed as a collaboration between Princeton, ETH Zurich, Oxford, Stanford and some other prestigious names. The benchmarks show that it compares favorably with leading proprietary solvers: https…

Can you recommend a go-to library to start solving a charging network problem?

The domain is somewhat unique since our charging points are mobile and stochastic, but charging demand is scheduled in advance

Re: Optimization solvers: missing link for fully open-source energy system modeling

#10

Post by jvanderbot » Sat, Apr 30, 2022, 3:19 PM UTC

Where's Scip? it's performance relative to CPLEX was pretty good for the problems I threw at it.