add MindOpt solver

[fneum]

https://solver.damo.alibaba.com/doc/en/html/index.html

https://opt.alibabacloud.com/portal?lang=en

does not require special license setup

Free for personal and commercial end-users, but not open-source as far as I can see.

Performed quite well in benchmarks: https://plato.asu.edu/ftp/lpopt.html

Tested locally and passed all tests. However, quadratic problems are not supported yet.

import pypsa

n = pypsa.examples.ac_dc_meshed()
n.optimize(solver_name='highs')
n.buses_t.marginal_price["London"]
n.generators_t.p
n.optimize(solver_name='mindopt')
n.generators_t.p
n.buses_t.marginal_price["London"]

[codecov[bot]]

Codecov Report

Attention: 7 lines in your changes are missing coverage. Please review.

Comparison is base (b91f08d) 89.25% compared to head (29ce758) 89.18%. Report is 2 commits behind head on master.

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```diff @@ Coverage Diff @@ ## master #188 +/- ## ========================================== - Coverage 89.25% 89.18% -0.07% ========================================== Files 15 15 Lines 3182 3228 +46 Branches 731 738 +7 ========================================== + Hits 2840 2879 +39 - Misses 237 243 +6 - Partials 105 106 +1 ``` | [Files](https://app.codecov.io/gh/PyPSA/linopy/pull/188?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PyPSA) | Coverage Δ | | |---|---|---| | [linopy/solvers.py](https://app.codecov.io/gh/PyPSA/linopy/pull/188?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PyPSA#diff-bGlub3B5L3NvbHZlcnMucHk=) | `89.52% <84.78%> (-0.59%)` | :arrow_down: |

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